Levels and Patterns of Genetic Diversity in Wild Populations and … · 2010-06-09 · Levels and...
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Levels and Patterns of Genetic Diversity in Wild Populations and Cultured Stocks of Cherax quadricarinatus (von Martens, 1868)
(Decapoda: Parastacidae)
Natalie Baker B. App. Sci. (Hons)
Queensland University of Technology
Submitted in fulfilment of the requirement of the degree of Doctor of Philosophy, October 2005
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Keywords
Cherax quadricarinatus, mitochondrial DNA, microsatellites, population genetics,
phylogeography, aquaculture.
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Abstract Studying species at the molecular level can provide insights into how ecological and
biological processes interrelate resulting in the diversity we see today. This
information can be applied to conserve species at risk of extinction, or to better
manage genetic diversity in species of economic importance. Species that inhabit
freshwater riverine systems commonly exhibit population structures that are related
to their relative dispersal capability, contemporary stream structure and/or historical
stream structure. This thesis examined the populations genetic structure of wild and
cultured stocks of the commercially farmed freshwater crayfish, C. quadricarinatus
(von Martens), using genetic markers characterized by different modes of
inheritance. C. quadricarinatus is distributed naturally in riverine systems in
northern Australia, and southern Paupa New Guinea (PNG) and inhabits a variety of
freshwater ecosystems ranging from ephemeral to permanent. Life history
characteristics of C. quadricarinatus suggest a high level of genetic structuring
among wild stocks might exist. However, seasonal flooding coupled with low
topography across its distribution in northern Australia may promote sufficient gene
flow among rivers to produce genetic homogeneity. Historical gene flow may also
influence modern genetic structure as many distinct riverine catchments that C.
quadricarinatus inhabits, were once connected at times of lower sea level. Insight
into genetic relationships among C. quadricarinatus populations will allow for better
management practices of wild populations in the future.
The study investigated phylogenetic relationships among C. quadricarinatus
representing 17 discrete natural drainages across the natural range in Australia and
PNG, using 16s and COI gene sequences. Sequence analysis of both genes
resolved two distinct genealogical lineages in Australia and three in PNG. The two
divergent Australian lineages concur with original taxonomic descriptions of Reik
(1969) based on external morphological differences. The three C. quadricarinatus
populations sampled in PNG were all genetically distinct from each other, with one
exhibiting a close association with an Australia lineage. The immense physical
barriers (rugged mountain ranges) to gene flow in PNG will almost certainly have
reduced dispersal capabilities for C. quadricarinatus. During times of lowered sea
levels in the past, Australia and southern PNG were a single landmass with
terrestrial and freshwater organisms theoretically able to disperse over associated
land and via freshwater connections. The close genetic relationship between PNG
and Australian C. quadricarinatus support a recent freshwater connection and hence
gene flow between northern Australia and PNG C. quadricarinatus populations.
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Genetic differentiation among some C. quadricarinatus lineages exhibit as much
genetic divergence at 16s RNA sequences as taxonomically recognised sub-species
in the Cherax genus. Since C. quadricarinatus was originally described as different
species based on external morphological differences (Reik, 1969), it is
recommended that the taxonomy of C. quadricarinatus in Australia and PNG be re-
evaluated.
C. quadricarinatus specific microsatellite markers were developed for this study.
Five variable loci were employed to investigate the extent of contemporary gene
flow among fourteen C. quadricarinatus wild river populations in northern Australia.
High FST and genetic distance estimates observed among pair wise comparisons of
C. quadricarinatus populations are consistent with limited or no gene flow occurring
among drainages. Speculation that C. quadricarinatus may disperse between
adjacent or nearby drainages at times of flood, either across floodplains, or via flood
plumes therefore seems highly unlikely among the populations examined in the
current study. No significant correlation was observed between geographic distance
and genetic distance among C. quadricarinatus populations here. C. quadricarinatus
populations most closely resemble an island-like model, where gene flow is
independent of geographic distance among populations and where genetic
divergence occurs to a greater or lesser extent as a result of genetic drift within
otherwise isolated populations.
A significant number of C. quadricarinatus populations showed deviations from
expected Hardy-Weinberg equilibrium (HWE). Samples sizes may not have been
sufficiently large to reflect a true representation of genotypic proportions present in
the sampled populations due to the highly variable nature of microsatellite loci.
Deviations from HWE equilibrium, however, can also result from null alleles. Null
allele estimates suggested a large proportion of null alleles were present in the C.
quadricarinatus populations analysed. This may be a result of C. quadricarinatus
populations confined to discrete drainages experiencing independent evolution,
resulting in mutations in primer binding sites.
The growing economic potential of C. quadricarinatus culture, both domestically and
internationally, prompted expanding the current study to examine genetic diversity
levels in commercial C. quadricarinatus stocks. The study employed five
microsatellite markers to quantify genetic diversity in four Australian and three C.
quadricarinatus culture stocks from overseas. Many C. quadricarinatus culture
stocks also showed deviations from HWE expectations. This was not a surprising
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result given that the wild populations also deviated and domestication can also
influence HWE. Relatively high levels of genetic diversity were observed. This
probably results from intentional mixing of discrete river strains for production of the
first commercial stock. Genetic differentiation estimates among culture stocks and
assignment tests indicated that overseas culture stocks are most likely derived from
the first commercial culture stock developed in Australia and then disseminated
widely (the Hutchings stock). Robin Hutchings was a known supplier of live C.
quadricarinatus to many international culture initiatives. Assignment of culture stocks
back to their wild origins indicated that all C. quadricarinatus culture stocks sampled
possess alleles that originate from the Flinders River (proportions ranged from 33-
94%).
Domestication of C. quadricarinatus to date has not resulted in significant reductions
in levels of genetic diversity (heterozygosity or alleles richness) when compared to
wild populations sampled in this study. Comparing culture stocks to wild populations
to gauge their ‘genetic health’ may not be a suitable scale for evaluating genetic
diversity in culture stocks. Wild populations are essentially evolving independently,
are subjected to harsh seasonal environmental fluctuations resulting in periodic
population crashes (genetic bottlenecks), with little or no recruitment from
neighbouring drainages (gene flow). This study does however indicate that there is a
large amount of genetic diversity distributed among wild populations that has yet to
be exploited in culture. Genetic diversity in wild populations provides a resource for
future stock improvement programs for C. quadricarinatus culture and thus requires
careful conservation and appropriate management.
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Table of Contents Keywords.................................................................................................................... ii Abstract ...................................................................................................................... ii Statement of Original Authorship .............................................................................. xi Acknowledgements .................................................................................................. xii 1 .0 General Introduction............................................................................................1
1.1 Australian aquaculture – an overview...............................................................1 1.2 Domestication of aquatic species: lessons from agriculture .............................3
1.2.1 Genetic improvement of aquaculture species ............................................4 1.3 Evolution of genetic variation in wild populations..............................................8
1.3.1 Population structure in riverine systems...................................................10 1.4 Culture of Australian freshwater crayfish species ...........................................11
1.4.1 C. quadricarinatus culture ........................................................................12 1.4.2 C. quadricarinatus taxonomy ...................................................................14
1.5 Research Objectives.......................................................................................16 1.6 Research Plan ................................................................................................17 1.7 Thesis structure ..............................................................................................17
2 .0 General Methods...............................................................................................19 2.1 Sample Collection and Storage ......................................................................19 2.2 Genetic Markers .............................................................................................22
2.2.1 Mitochondrial DNA ...................................................................................22 2.2.2 Microsatellite DNA....................................................................................23
2.3 Geographic distance among sampled wild populations..................................24 3 .0 Phylogenetic relationships among wild C. quadricarinatus populations ............23
3.1 Introduction .....................................................................................................23 3.2 Mitochondrial DNA Methodology ....................................................................26
3.2.1 Samples ...................................................................................................26 3.2.2 DNA Extraction.........................................................................................26 3.2.3 Mitochondrial DNA Extraction ..................................................................27 3.2.4 PCR Analysis ...........................................................................................27 3.2.5 Sequencing of mtDNA Haplotypes...........................................................28
3.3 Statistical Analysis ..........................................................................................28 3.3.1 Neutrality Tests ........................................................................................28 3.3.2 Testing for saturation ...............................................................................28 3.3.3 Phylogenetic reconstruction of wild C. quadricarinatus populations ........28 3.3.4 Isolation by distance.................................................................................29 3.3.5 Molecular clock estimates ........................................................................29
3.4 Mitochondrial Results .....................................................................................30 3.4.1 Analysis of 16s Sequence diversity..........................................................30
3.4.1.1 Neutrality tests .............................................................................32 3.4.1.2 16s saturation plots......................................................................32 3.4.1.3 Phylogenetic analysis of 16s sequences.....................................34 3.4.1.4 Isolation by distance ....................................................................34 3.4.1.5 16s molecular clock estimates.....................................................35
3.4.2 Analysis of COI haplotype diversity..........................................................36 3.4.2.1 COI Neutrality Test ......................................................................38 3.4.2.2 COI Saturation Plot......................................................................38 3.4.2.3 Phylogenetic analysis of COI.......................................................40 3.4.2.4 Isolation by distance ....................................................................42 3.4.2.5 COI molecular clock estimates ....................................................42
3.5 Discussion ......................................................................................................43 3.5.1 Reconstruction of the evolution of modern C. quadricarinatus lineages ..46
4 .0 The Extent of Contemporary Gene Flow among Wild Australian C. quadricarinatus Populations .....................................................................................49
4.1 Introduction .....................................................................................................49 4.2 Microsatellite Methods ....................................................................................51
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4.2.1 Sample sites.............................................................................................51 4.2.2 DNA Extraction.........................................................................................51 4.2.3 Microsatellite Isolation and Characterisation............................................52 4.2.4 Radioisotope Analysis of C. quadricarinatus Microsatellites ....................53 4.2.5 Fluorescent Analysis of C. quadricarinatus Microsatellites ......................54 4.2.6 Statistical Analysis ...................................................................................56
4.2.6.1 Linkage disequilibrium .................................................................56 4.2.6.2 Tests for Hardy-Weinberg Equilibrium (HWE) .............................56 4.2.6.3 Molecular diversity .......................................................................56 4.2.6.4 Null allele analysis .......................................................................56 4.2.6.5 Population differentiation .............................................................57 4.2.6.6 Genetic distance..........................................................................57 4.2.6.7 Isolation by distance measures ...................................................58 4.2.6.8 AMOVA analysis of molecular variance.......................................59 4.2.6.9 Detection of recent population bottlenecks..................................59 4.2.6.10 Shannon-Weaver Index of genetic diversity ................................60
4.3 Results............................................................................................................61 4.3.1 Microsatellite analyses of Eastern Populations ........................................61
4.3.1.1 Linkage Disequilibrium.................................................................61 4.3.1.2 Hardy Weinberg Departures ........................................................61
4.3.2 Molecular Diversity ...................................................................................61 4.3.3 Null Alleles ...............................................................................................62 4.3.4 Population differentiation..........................................................................64 4.3.5 Genetic Distance......................................................................................64 4.3.6 Isolation by Distance ................................................................................65
4.3.6.1 Mantel tests .................................................................................65 4.3.6.2 FST values graphed against geographic distance ........................65
4.3.7 AMOVA ....................................................................................................66 4.3.8 Bottleneck analysis ..................................................................................66 4.3.9 Genetic Diversity Estimates .....................................................................67 4.3.10 Microsatellite Analysis of Western Populations......................................67
4.3.10.1 Linkage Disequilibrium.................................................................67 4.3.10.2 Hardy Weinberg Departures ........................................................67 4.3.10.3 Molecular Diversity ......................................................................67
4.3.11 Null Alleles .............................................................................................68 4.3.12 Population differentiation........................................................................68 4.3.13 Genetic Distance....................................................................................69 4.3.14 Isolation by Distance ..............................................................................69
4.3.14.1 Mantel tests .................................................................................69 4.3.14.2 FST values graphed against geographic distance ........................69
4.3.15 AMOVA ..................................................................................................70 4.3.16 Bottleneck analysis.................................................................................70 4.3.17 Genetic Diversity Estimates ...................................................................71 4.3.18 Gene Flow Estimates .............................................................................71
4.4 Discussion ......................................................................................................72 5 .0 Genetic diversity in cultured C. quadricarinatus stocks compared with wild populations ...............................................................................................................78
5.1 Introduction .....................................................................................................78 5.1.1 Current status of C. quadricarinatus culture stocks..................................79
5.2 Methods ..........................................................................................................81 5.2.1 Sampling of cultured stocks .....................................................................81 5.2.1 Analysis of genetic diversity in cultured C. quadricarinatus stocks ..........83
5.2.1.1 DNA extraction and microsatellite analysis..................................83 5.2.2 Statistical analyses...................................................................................83
5.2.2.1 Molecular diversity of cultured stocks ..........................................83 5.2.2.2 Linkage disequilibrium of cultured stocks ....................................83 5.2.2.3 Hardy-Weinberg Equilibrium (HWE) of cultured stocks ...............83 5.2.2.4 Testing for bottlenecks.................................................................84
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5.2.2.5 Shannon-Weaver Index of genetic diversity ................................84 5.2.2.6 Origins of culture stocks – assignment testing ............................84 5.2.2.7 Comparison of culture stocks and wild populations.....................84
5.3 Results............................................................................................................85 5.3.1 Molecular diversity of culture stocks.........................................................85 5.3.2 Linkage Disequilibrium .............................................................................85 5.3.3 Hardy Weinberg Equilibrium ....................................................................87 5.3.4 Genetic distance among cultured stocks..................................................87 5.3.5 Testing for genetic bottlenecks.................................................................88 5.3.6 Genetic diversity estimates: Shannon’s Index..........................................88 5.3.7 Comparing genetic diversity between Australian and overseas culture stocks ................................................................................................................89
5.3.7.1 Number of alleles per locus .........................................................89 5.3.7.2 Levels of heterozygosity ..............................................................89 5.3.7.3 Shannon Index estimates ............................................................89
5.3.8 Assignment of C. quadricarinatus stocks to wild populations sampled ....89 5.4 Discussion ......................................................................................................91
6 .0 General Discussion ...........................................................................................95 6.1 Significance for wild populations.....................................................................96 6.2 Significance for aquaculture/fisheries policy ...................................................97
6.2.1 Aquaculture ..............................................................................................97 6.2.2 Fisheries...................................................................................................98
6.3 Recommendations for C. quadricarinatus culture industry .............................98 6.4 Future research ..............................................................................................99
7 .0 Conclusions.....................................................................................................101 8 .0 Appendix 1 ......................................................................................................103 9 Bibliography.........................................................................................................105
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Table of Figures Figure 1-1: Reik’s (1969) classification based on morphological differences of Cherax in northern Australia and southern PNG……………………………………..15 Figure 2-1: Shaded areas illustrate the natural distribution of C. quadricarinatus in Australia and New Guinea (Austin, 1986). ..……….………………………………...20 Figure 3-1: 1) Ancient river system at -120m sea level contour, 2) Lake Carpentaria shown at the-75m sea level contour…………………………………………………..24 Figure 3-2: Neighbour joining tree for 16s sequences of C. quadricarinatus, with C. destructor as an outgroup………………………………………………………………35 Figure 3-3: Parsimony network for C. quadricarinatus 16s haplotypes constructed in TCS……………………………………………………………………………………….36 Figure 3-4: Neighbour joining tree of Australian COI C. quadricarinatus haplotypes………………………………………………………………………………..40 Figure 3-5: Parsimony network for C. quadricarinatus COI haplotypes constructed in TCS reveals evolutionary relationships among haplotypes………………………41 Figure 4-1: Graphical representation of genetic differentiation, estimated by FST and geographic distances (km) of eastern population pairs……………………………..65 Figure 4-2: Graphic relationship between genetic differentiation FST and geographic distances (km) of western population pairs…………………………………………..70
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Table of Tables Table 1-1 Improvement programs applied to aquaculture species ………………….5 Table 2-1 Sampling sites, drainage system, number of individuals analysed for mtDNA and microsatellites and date collected for the present study. ………..21 Table 2-2 Stock name, location, sample size and date collected of farmed C. quadricarinatus stock sampled in this study. ………………………………………. 22 Table 3-1: Site Location, river drainage, abbreviation used in following tables and sample size for 16s and COI mtDNA gene analysis. ……………………………….26 Table 3-2: Informative sites among sampled C. quadricarinatus river populations from 482bp of 16s mtDNA identified by sequencing. ………………………………31 Table 3-3: Relationship among sampled populations based on 16sRNA sequences. ………………………………………………………………………………………………33 Table 3-4: Informative sites among C. quadricarinatus COI haplotypes …………..37 Table 3-5: Relationship among sampled populations based on COI sequences …39 Table 4-1: Site Location, river drainage, abbreviation, sample size of C. quadricarinatus populations used for microsatellite analysis ……………………..51 Table 4-2: Locus name, primer sequences (5’ to 3’ direction), repeat type and size, and PCR conditions for microsatellite loci used in this study ……………………53 Table 4-3: Locus name, repeat type/size, annealing temperature, magnesium chloride concentration and amplification success of C. quadricarinatus microsatellite loci used in this study ………………………………………………………………..53 Table 4-4: Common indices for eastern C. quadricarinatus populations…………..63 Table 4-5: Population differentiation for eastern C. quadricarinatus populations. ..64 Table 4-6: Chord distance estimates using data from five microsatellite loci for ‘eastern’ C. quadricarinatus populations. ……………………………………….…….65 Table 4-7: AMOVA showing the partitioning of variation within and among eastern populations of C. quadricarinatus. ……………………………………………………. .66 Table 4-8: Evidence for recent bottlenecks was indicated by significant heterozygosity excess or an allele distribution ‘mode shift’ ………………………….66 Table 4-9: Shannon's Information index (Shannon and Weaver 1949) of eastern C. quadricarinatus populations for five microsatellite loci, their mean value and standard deviation. ……………………………………………………………………… 67 Table 4-10: Common indices for western C. quadricarinatus populations.….……. 68 Table 4-11: Population differentiation for western C. quadricarinatus populations. 69 Table 4-12: Chord distance estimates using data from three microsatellite loci for western C. quadricarinatus populations. ………………………………………….….. 69
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Table 4-13: AMOVA showing the partitioning of variation within and among western populations of C. quadricarinatus.………………………………………………..…… 70 Table 4-14: Evidence for recent bottlenecks was indicated by significant heterozygosity excess or an allele distribution ‘mode shift’. …………….…………. 71 Table 4-15: Shannon's Information index (Shannon and Weaver 1949) of western C. quadricarinatus populations for three microsatellite loci………………………………71 Table 5-1: Five C. quadricarinatus microsatellite loci were successfully used to determine the levels of genetic variability in C. quadricarinatus cultured stocks. ….83 Table 5-2: Common indices for cultured C. quadricarinatus stocks. ……………….86 Table 5-3: Results of Hardy-Weinberg equilibrium exact tests. …………………….87 Table 5-4: Genetic distance measures of C. quadricarinatus culture stocks using Chord distance algorithm. ……………………………………………………….………87 Table 5-5: Evidence for recent bottlenecks was indicated by significant heterozygosity excess or an allele distribution ‘mode shift’. …………………………88 Table 5-6: Shannon Index of genetic diversity of cultured populations for five microsatellite loci and their mean. ……………………………….…………………….89 Table 5-7: Proportion of C. quadricarinatus culture individuals assigned a river drainage based on 5 microsatellite loci performed in GENECLASS. …………..… 90
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Statement of Original Authorship The work contained in this thesis has not been previously submitted for a degree or diploma at any other higher education institution. To the best of my knowledge and belief, the thesis contains no material previously published or written by another person except where due reference is made. Signed: Date:
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Acknowledgements “She who asks a question is a fool for a minute; she who does not remains a fool forever” (Chinese Proverb) My minute lasted many years, along the way I gained strength, motivation, encouragement and support from many people I need to thank. Special thanks to my supervisors, Peter Mather and John Wilson, especially Peter - without your support and belief in me I would not have taken on or completed this challenge. Thank you to colleagues at the School of Natural Resource Sciences; to friends who have kept me sane, given encouragement and motivation along the way, in particular: Andrew Baker, Sam Bremner, Amanda Dimmock, Angela Duffy, Martin Elphinstone, Lia Gill, Kerrilee Horskins, Maria Hughes, Rosaleen Hynes, Corinna Lange, Julie Macaranas, Justin Meager, Juanita Renwick, Monique and Nigel Wray. For reading drafts, maps and statistical advice - Andrew Baker, Mark de Bryun, Sally Dillon, Amanda Dimmock, Angela Duffy, Adam Liedloff, Peter Mather, Peter Prentis, Juanita Renwick, Alicia Toon. And lastly, my internal examiners Tony Clarke and Susan Fuller for improvements, suggestions and encouragement. I dedicate this thesis to my parents, for without their support and encouragement, I would not have started or completed this thesis. I would like to thank the following people for their help collecting samples: Wild C. quadricarinatus samples: C. quadricarinatus from the Flinders, Gilbert and Mitchell Rivers were provided by Clive Jones from the Queensland Department of Primary Industries and Fisheries, Walkamin Station, Queensland. Tracey and David Kostecki collected and sent crayfish from an undisclosed location near Weipa. Mr Peter Hurley in Darwin collected and sent Adelaide and Howard River populations. Field trips to northern Australia were made by myself and fellow QUT students: Amanda Dimmock, Shaun Meredith, Steve Caldwell, Sonja Parsonage, Mark de Bruyn, Kerrilee Horskins, Craig Streatfeild and David Elmoutie. Ian Middleton provided C. quadricarinatus samples from the Bensbach River in PNG. Jim Belford collected samples from the Oriomo River, PNG. Peter Davies at the Queensland Museum generously allowed me to remove a small portion of tissue from C. quadricarinatus specimens in their collection. Cultured stocks: Three C. quadricarinatus farms local to the Brisbane area were sampled personally. Overseas culture C. quadricarinatus samples were obtained in 2002 from with generosity from Ilan Karplus (Israel), Anthony Garcia (Mexico) and Xavier Romero (Ecuador). And thanks to Dean Jerry (CSIRO) for providing Cherax destructor and Cherax tenuimanus tissue samples as outgroup references.
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1.0 General Introduction 1.1 Australian aquaculture – an overview Aquaculture is one of Australia’s fastest growing rural industries (AFFA, 2002).
Demand for farmed aquatic species has increased significantly as wild fish stocks
decline worldwide due to unstainable fishing practices (Carey, 1998; Pauly &
Watson, 2003). Harvesting of many aquatic species is currently at, or above, their
maximum capacity. As demand for aquatic foodstuffs rises beyond the capacity of
wild fisheries to supply markets, the Food and Agriculture Organisation (FAO)
predicts that any further increases in global consumption of seafood will need to be
met by increased production from aquaculture (FAO, 2002). In response to growing
world demand, there has been a concerted and coordinated effort by the Australian
government and industry to develop and promote aquaculture production. In doing
so, government and industry are working together to promote Australia’s clean
waters image, encourage aquaculture investment and to identify possible
alternatives for future expansion including offshore aquaculture, the use of inland
saline waters and the re-use of irrigation waters (AFFA, 2002).
Cultured pearls and bluefin tuna dominate Australian aquaculture exports.
Production of these two species represents nearly 60% of the total current value of
aquaculture production in Australia (AFFA, 2002). Other key aquaculture products
include Atlantic salmon, edible oysters, farmed prawns and trout. The Australian
pearl industry is an example of a lucrative sustainable aquaculture venture with a
promising future. The industry is based on Pinctada maxima, a pearl oyster native to
the waters of northern Australia. Although collection of wild pearl oysters occurs, the
industry has developed and operates a centralised hatchery, distributing spat to
producers for grow out on pearl farm leases. Strong investment in research and
development and ongoing technological advances ensures that the P. maxima
industry in Australia produces the highest quality cultured pearls in the world (AFFA,
2002).
Southern Bluefin tuna (Thunnus thynnus) is another economically important
Australian culture species (AFFA, 2002), but this industry may not have the capacity
to sustain long term economic growth like the pearl industry. Currently, wild juvenile
Southern Bluefin tuna are caught in the Southern Ocean and towed in special
purpose-built cages to offshore farms in South Australia where they are placed in
floating sea pontoons in coastal waters. Tuna are fed wild pilchards, jack mackerel
and squid (Holland & Brown, 1999) a practice that places additional pressure on wild
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fish stocks and challenges the sustainability of culture production industries. With
little potential for developing improved culture breeds or the ability to adapt to culture
environments and a reliance on wild stocks to provide juveniles for grow out, the
long term viability of this species in culture is potentially compromised.
Exotic salmonids are Australia’s third most valuable culture species, first imported
during the late 1800s for the purpose of farming or recreational fishing (Ovenden et
al, 1993. Rainbow trout, (Oncorhynchus mykiss) and Atlantic salmon (Salmo salar)
are cultured in fresh and seawater respectively to supply local and international food
markets. Brown trout (S. trutta) and to a lesser extent brook trout (Salvelinus
fontinalis) are sustained by natural spawning for recreational fishing in temperate
areas in southern Australia (ABARE, 2002). In 2000-2001, the Australian salmon
industry was valued at $95.3 million (third in value after tuna, $263.8 mil; and pearl
oysters, $171.5 mil) (ABARE, 2001). Studies of salmonid genetic diversity in
Tasmania however, have found no variation in mitochondrial DNA in Atlantic
salmon, rainbow trout or brown trout and only two mitochondrial haplotypes were
found in brook trout samples (Ovenden et al., 1993). Quarantine policies are now in
place to ensure Australia remains disease free and this means farmers are not able
to access new germplasm from overseas to improve existing salmonid culture
stocks. The lack of genetic diversity in cultured salmonids is a concern, as high
levels of genetic diversity allow populations to adapt to and resist environmental
change and disease. Currently, a marine protozoan pathogen Neoparamoeba pemaquidensis, occurs seasonally in Atlantic salmon in Tasmania, and is regarded
as a major problem that costs the industry $10m to $15m annually (State of the
Environment, 2001). With little genetic diversity remaining the long term viability of
the salmonid industry is challenged by the inability to introduce new germplasm or
the availability of an improved stock with disease resistance.
Aquatic pest species (native or exotic) have the potential to adversely affect native
fish stocks and their environment when they escape from captivity. Escaped fish
can, for instance, interbreed with wild fish, and this may have detrimental effects on
the genetic integrity and viability of wild stocks (McConnell et al., 1997); (McGinnity
et al., 2003); (Holland & Brown, 1999). Escaped fish may also contribute to the
transfer of disease or may be in direct competition for preferred habitat with wild
individuals (Youngson & Verspoor, 1998). Farmed fish commonly escape into the
wild as a result of human error, storm and/or predator damage to net cages or
inadvertent release during transport. Australia has a unique aquatic fauna and
ecosystems and introductions of foreign aquatic or terrestrial species is not
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permitted due to the risk of escapees becoming established in our waterways and
endangering native species. Thus, essentially, Australia is restricted to developing
aquaculture industries based on indigenous species, and we must use existing wild
genetic resources to improve culture stocks.
Given these limitations, Australian aquaculture producers are still well placed to
capitalise on increasing world demand for high quality seafood. Due to strict
quarantine policies, Australia remains relatively disease free, and has not been
affected by many of the diseases that have decimated aquaculture industries
overseas (AFFA, 2002). For example, Australia is free of crayfish plague, a disease
that has decimated European and Asian crayfish culture industries (Holdich, 1993).
Technologies for efficient production and rearing have also been developed for
many native aquatic species. The future application of genetic breeding programs
are likely therefore to contribute significantly to increasing productivity of a number
of Australian native aquatic cultured species.
1.2 Domestication of aquatic species: lessons from agriculture As aquaculture of most native Australian aquatic species is relatively new, much can
be learned from advances made in agriculture. Terrestrial plants and animals of
agricultural importance have been subjected to intense domestication and artificial
selection for more than 10 000 years. Improvement in growth rates, yield and
disease resistance have been dramatic and were achieved largely through
application of artificial selection and appropriate genetic management practices
(Johnson, 1997; Gjedrem, 2000; Hulata, 2001). Improved culture stocks of terrestrial
plants and animals have been achieved in a number of ways: selection and
breeding of superior individuals or families (Daud & Ang, 1995; Bentsen et al., 1998;
Garduno-Lugo et al., 2004), the production of hybrids (Wada, 1994; Lawrence,
2004; Senanan et al., 2004) and more recently, the development and use of genetic
mapping studies that aid in the early detection of genetic loci that are linked to
desired quantitative traits (Lee & Kocher, 1996; Martinez et al., 1999; Davis &
Hetzel, 2000; Su et al., 2002; Fjalestad et al., 2003a; Li et al., 2003). Even though
the farming of aquatic species dates back nearly 4 000 years (Hulata, 1995a), most
aquaculture industries until recently, have been based on broodstock that were
essentially wild or only recently brought into captivity (eg. European carp stocks
Vandeputte, 2003). Unimproved stocks cannot guarantee productivity over time,
since captive populations may lose productivity due to inbreeding and genetic drift
effects over generations, because effective population sizes are generally low
(Lymbery, 2000; Doyle et al., 2001).
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It is widely recognised, however, that prospects for significant genetic gains in
aquaculture species are more promising than for most terrestrial species (Gjedrem,
1997). The basic theory underlying the development of breeding plans for
aquaculture production was summarised by Gall (1991). The high reproductive
potential of most aquatic species allows high genetic gains to be achieved over a
relatively short period of time via application of intense selection. This means that
potentially a very small number of individuals can make a large contribution to the
genetic make up of successive generations, increasing the rate of inbreeding.
Consequently, restrictions on inbreeding to limit potential negative effects need to be
considered when implementing any selective breeding programme on aquatic
species. Inbreeding potential is high, due to high fecundity and short generation
times in most aquatic species (Wilkins, 1981). In contrast to the situation in
terrestrial livestock, a potential disadvantage of the high fecundity of aquatic species
is that they can be maintained from a relatively small number of broodstock (a small
effective population size). Low numbers of broodstock are often capable of
producing a large number of offspring, which can lead to loss of genetic variation by
chance (genetic drift).
1.2.1 Genetic improvement of aquaculture species
Significant and sustained genetic improvement of any domesticated species simply
exploits the natural genetic variation present in a population. Genetic gains are
obtained by increasing the proportion of desirable allelic forms of genes for desirable
quantitative trait loci (QTL) in the target populations. Many breeding programs and
selection strategies have proven highly successful in many aquatic species (see
Table 1-1 for examples).
Success in breeding programs does not necessarily translate into sustained
improvement if broodstock are not managed correctly. Poor genetic management
practices including small broodstock numbers or kinship among breeders can
quickly erode levels of genetic diversity in captive stocks over time, and this poses a
significant threat to the long term success of any culture industry (Wolfus et al.,
1997; Lymbery, 2000; Doyle et al., 2001).
5
Table 1-1 Improvement programs applied to aquaculture species
Method Species Outcome Mass selection Atlantic Salmon
Salmo salar Up to 18% increase in body weight after a single generation
(Dunham & Smitherman, 1983; Gjedrem, 1985)
Channel catfish, Ictalurus punctatus
Increases in disease resistance and cold tolerance
(Dunham & Brummett, 1999; Vandeputte, 2003)
Kuruma, Penaeus japonicus
14% increase in weight (Preston et al., 2004)
Marker assisted selection
Kuruma, Penaeus japonicus
AFLP markers for pedigree identification
(Moore et al., 1999)
Ranbow trout, Oncorhynchus mykiss
Temperature tolerant QTLs identified
(Jackson et al., 1998; Danzmann et al., 1999)
Rainbow and cutthroat trout hybrids
Markers associated with IHN virus resistance
(Palti et al., 1999)
Catfish (Ictalurus sp.) QTL Linkage mapping (Liu et al., 1999) Hybridisation of strains
Nile tilapia, Oreochromis niloticus L
10% increase in body weight (Eknath et al., 1993; Bentsen et al., 1998; Longalong et al., 1999);
Chinese big-belly x European common carp
Positive culture qualities of the European strain and the hardiness of the Chinese strain
(Hulata, 2001)
Common carp crossbreds About 20% better performance than parental lines and other control strains.
(Hulata, 1995b; Bakos & Gorda, 2001)
Pearl oyster strains, Pinctada fucata
Improvements in shell width and survival rate.
(Wada, 1994)
Hybridisation of species
Female channel catfish x male blue catfish.
Superior for commercial culture
(Smitherman & Dunham, 1985)
Female Oreochromis mossambicus x male O. hornorum
All-male offspring. Male channel catfish outperform female growth rate
Female white bass (Morone chrysops Rafinesque) x male striped bass (M. saxatilis Walbaum)
Grows faster and higher thermal tolerance, improved resistance to stress and disease
(Van Olst & Carlberg, 1990)
Female Cherax rotundus, and male C. albidus
All male offspring; monosex hybrid grew nearly twice as fast as mixed sex C. albidus
(Lawrence, 2004)
6
Studies of inbreeding in fish have been few, but reduced growth, lower viability
and/or survival and an increase in frequency of abnormalities in inbred fish stocks
has been reported (Tave, 1991; Gjerde et al., 1996; Nakadate et al., 2003). Studies
of poor performing culture stocks have often been correlated with relatively low
levels of genetic diversity when compared to the wild relatives from which culture
stocks were derived eg Salmo salar (Norris et al., 1999); Penaeus monodon (Xu et
al., 2001); Crassostrea gigas (Hedgecock & Sly, 1990). A number of strategies can
be employed to combat detrimental effects of inbreeding; one common practice is to
add new germplasm periodically from unrelated individuals. However, many
hatchery managers are unwilling to incorporate new wild individuals into their
hatcheries as it can increase the risk of introducing new diseases, parasites or
pathogens (Davis & Hetzel, 2000; Gjedrem, 2000; Knibb, 2000).
Crossing divergent inbred lines or closely related species has been practiced to
produce offspring with hybrid vigour, however, crossing genetically divergent strains
or species can also result in offspring with reduced fitness (productivity) of F1 or
later generation hybrids (Gharrett et al., 1999). This phenomenon is known as
outbreeding depression and occurs when introgression of divergent gene pools
disrupt locally co-adapted gene complexes resulting in lowered fitness. Evidence of
outbreeding depression has been reported in a variety of species where genetically
divergent strains were crossed; Drosophila (Deng & Lynch, 1996); plants (Waser &
Price, 1989), and fish (Leberg, 1993; Gharrett et al., 1999). Second generation
offspring of crosses between even and odd year pink salmon (Oncorhynchus
gorbuscha) exhibited reduced survival, when compared to pure lines. Outbreeding
depression may not occur until the second, subsequent or even backcross
generations following assortment of alleles at different loci (Templeton, 1986;
Gharrett et al., 1999). The potential for the delay of the effect until subsequent
generations makes this phenomenon often difficult to detect and perhaps impossible
to reverse.
An important lesson learned from some early aquaculture ventures is the
importance of developing a founder stock with diverse genetic attributes. For
sustainable genetic improvement it is essential to maximise genetic diversity in
founding populations. Characterising genetic diversity, by directly measuring levels
and patterns of genetic variation using appropriate genetic markers, provides the
best possible starting point for achieving this goal (Lymbery, 2000; Rao & Hodgkin,
2002; Silverstein et al., 2004). In economic terms, maximizing diversity can provide
insurance against changes in production circumstances, a new disease, or changes
7
in market demands (Oldenbroek, 1999; Rao & Hodgkin, 2002). Diversity also has an
ecological value: environmentally well-adapted breeds (e.g., trypanotolerant cattle)
allow sustainable food production in lower-input farming systems (Reist-Marti et al.,
2003), which have a reduced impact on the environment. Diversity is also a basic
prerequisite for genetic improvement of economically important traits such as
disease resistance, or livestock productivity (Frankham, 1994; Rao & Hodgkin,
2002; Gao, 2003). Wild stocks can provide the genetic resource needed for
successful and sustainable culture industries, therefore conserving wild progenitors
of domesticated breeds should warrant a high conservation priority (Frankham,
1994).
Conserving the genetic resources of wild species for domestic plants and animals
can be achieved both in situ and ex situ. Theoretically, in situ conservation is the
best method for conserving wild genetic resources (Heywood, 1992) and has many
advantages, the most notable of which is that it is dynamic and permits natural
populations of the species concerned to continue to evolve. However, this practice
may not necessarily conserve the genetic resources of the species adequately.
Many horticultural and agricultural sectors do not rely on in situ conservation now,
but focus on ex situ methods. Horticulture has practised conservation of genetic
diversity of domesticated plants by actively collecting germplasm from wild relatives
that have resulted in comprehensive gene banks for seed, tissue or pollen, or as
growing collections in plantations, field gene banks and/or botanic gardens (van
Vuren & Hedrick, 1998). In livestock production, live animals are the most common
and best known method for conserving genes, but can also be supplemented with
frozen semen and frozen embryos. Frozen tissue has the advantage that the risk of
genetic drift, inbreeding and genetic contamination from other populations is absent,
but regenerating a breed can take a long time from frozen material. Aquaculture
industries are also investing in live gene banks. For example, the Fish Culture
Research Institute, Hungary, established a live gene bank for domesticated carp in
1963. Common carp strains were collected and are maintained and supplemented
periodically with additional wild collections. This gene bank contributes significantly
to the preservation of unique gene pools of an important cultured aquatic species
(Gorda et al., 1995).
For many domesticated terrestrial livestock species nearly all wild relatives have
been lost over time (Small, 1997; Gao, 2003; Long et al., 2003). As a consequence,
unique breeds and feral stock (eg cattle, pigs and goats) now offer the only potential
sources of new genetic variation for domesticated breeds for many such species.
8
Many wild stocks of aquatic organisms are under threat from unmonitored fishing
efforts, translocation of species, introduction of exotic species and habitat
degradation (Allendorf et al., 1997; Cross, 2000; Crozier, 2000; Bakos & Gorda,
2001). Some wild stocks of aquatic species used in culture are near extinction (eg
Atlantic salmon, trout, cod (Ferguson et al., 1995; Allendorf & Waples, 1996;
Allendorf et al., 1997; Nielsen, 1998; Shaklee et al., 1999)). For example, the
Atlantic salmon Salmo salar L. is now extinct, or in critical condition, in over 27% of
rivers, and endangered or vulnerable in a further 30% of rivers in the North Atlantic
region (WWF, 2001). Like extinctions of species, the loss of wild genetic resources
is irreversible. This is a concern as this genetic variation is not only the raw material
for evolution, but is also an important resource for future improvement of domestic
animals and cultivated plants.
The extent to which individual traits or sets of attributes can be improved for
economic gain will depend on the extent of genetic variation that exists for the trait/
trait complex. In theory, populations with the highest levels of genetic diversity
possess the greatest adaptive potential and should respond best to artificial
selection programs (Wilkins, 1981; Davis & Hetzel, 2000). Wild populations, the
primary source of genetic variation, are therefore important resources for many
culture industries. The distribution of genetic resources in natural populations
depends on the interaction of life history processes, such as fecundity, social
structure and dispersal potential in present and past environments and; on genetic
processes such mutation, drift and selection (Slatkin, 1994). Understanding the
levels and patterns of genetic variation in wild populations is therefore an integral
part of any sustainable stock improvement program.
1.3 Evolution of genetic variation in wild populations Species are rarely panmictic. Rather, they are often structured into individual demes
or subpopulations of randomly interbreeding population units (Frankel & Soulé,
1981). Partial reproductive isolation coupled with restricted distributions of
subpopulations of aquatic species in time and space provides the basis for local
adaptation via selection. Thus, overall productivity and evolutionary potential of a
species will depend on maintaining the abundance and diversity of its component
subpopulations or demes. This perspective, known as the ‘stock concept’, was
initially developed for Pacific salmon Oncorhynchus spp. and is now a central theme
in the management and study of most fish and shellfish species (Berst & Simon,
1981; Dizon et al., 1992).
9
Evolutionary and biological processes combine to shape the population structure of
any organism. Evolutionary processes including natural selection, mutation, gene
flow and genetic drift largely determine the genetic structure of organisms while
biological processes associated with reproduction, life history, mating systems and
dispersal affect their demographic structures (Slatkin, 1994).
Two demographic factors, effective population size and migration rate (gene flow),
have a major impact on the degree of divergence that can develop among local
populations of most freshwater organisms (Bunn & Hughes, 1997; Costello, 2003).
Populations diverge from one another as a consequence of local selection
pressures, mutation and random genetic drift; with drift alone capable of causing
considerable divergence among populations (Galvin et al., 1996; Loertscher et al.,
1998). The rate of divergence due to drift in turn will depend largely on the genetic
effective size of local populations (Ne). Ne represents the number of breeding adults
contributing to the next generation and is affected by sex ratio, mating patterns and
individual variance in reproductive output (Crow & Kimura, 1970). Gene flow by
means of migration (m, or the proportion of individuals exchanged between
populations per generation) maintains genetic variation within populations and
retards divergence among populations. Divergence occurs as a product of Ne and
m. If Ne is small, populations tend to diverge rapidly as a result of random processes
(eg. genetic drift). However, gene flow (m) can counteract local effects of drift that
lead to divergence (Slatkin, 1987; 1994).
Two major classes of population genetic structure have been identified. The first is
found in most species with continuous distributions and the second in those
composed of discrete populations. Genetic structure of continuously distributed
populations generally takes the form of (1) panmixia, which is the free genetic
interchange of individuals across the population or (2) isolation by distance, where
interchange is local and is a function of individual lifetime dispersal distance (Slatkin
1985, Richardson et al. 1986). Levels of gene flow in continuous distribution models
are defined by the geographical spread of lifetime dispersal distances. Discrete
subpopulation models do not have an inherent geographic structure; what is more
important is the extent of gene flow among subpopulations (Slatkin, 1985). Models
of gene flow include the Island Model (Wright, 1931), which in more recent usage
represents a situation where a particular subpopulation is equally likely to send or
receive individuals from a finite number of other subpopulations (Slatkin, 1985). The
Stepping Stone model of Kimura (Kimura, 1953) describes a set of subpopulations
arranged in a one-, two-, or three- or more dimensional lattice in which individuals
10
can only move among adjacent subpopulations. These models of genetic structure
are based on the assumption that populations are dispersed geographically as if
they were islands in a matrix and gene flow can occur equally among all islands
(Kimura, 1953). However, for most freshwater organisms, riverine habitats are likely
to impose a more complex population structure.
1.3.1 Population structure in riverine systems
Recognition that obligate freshwater species often show high levels of genetic
structuring among drainages has been attributed to the isolating effects of drainage
structure, and to their relatively small populations sizes (Ward et al., 1994). High
levels of population structuring have been reported in many organisms that inhabit
freshwater systems including, fish (Waters & Burridge, 1999; McGlashan & Hughes,
2002), insects (Hughes et al., 1999; Chapman et al., 2003), molluscs (Hughes et al.,
2004) and crustaceans (Hughes, 1996; Bohonak, 1998; Cook, 2002). This has
usually been attributed to the level of fragmentation and isolation of discrete riverine
systems.
Meffe and Vrijenhoek (1988) proposed the Stream Hierarchy Model (SHM) as a
means for summarising the relationships among populations within and among
freshwater drainages. Due to the hierarchical nature of river drainages they
proposed that the probability of connectivity was related to the location of a
population in a particular drainage, such that populations within the same stream are
more likely to be genetically similar than populations in different subcatchments
irrespective of geographical distance, with most differentiation occurring at the level
of discrete drainages.
Freshwater species are inherently vulnerable to extinction when local habitat
destruction and impoundments etc erode population connectivity (Meffe and
Vrijenhoek, 1988). Reduced dispersal and gene flow will eventually change the
genetic architecture within and among natural populations. Genetic drift will cause a
progressive loss of diversity within isolated populations and increase the extent that
genetic differentiation develops among them. Local populations may go extinct in
drought years and habitats may be recolonised from more permanent populations.
Depending on the pattern of recolonisation, diversity may also decline rapidly within
and among populations. If local extinction and recolonisation events are frequent,
11
the populations will coalesce rapidly, and differences within and among populations
will be lost as Ht1 approaches zero (Meffe and Vrijenhoek, 1988).
Thus, natural populations of freshwater aquatic species are likely to show population
structuring related to the architecture and connectivity of the natural drainage
systems they occupy. This natural genetic diversity is seldom considered when new
species are brought into culture and this may limit the potential for a long term
sustainable industry. New culture industries can benefit from understanding the
levels and patterns of natural genetic diversity that are present in wild stocks, such
knowledge of population genetic structuring and the distribution of genetic diversity
can aid culturists when sourcing broodstock or new germplasm.
1.4 Culture of Australian freshwater crayfish species Australian freshwater crayfish are decapod crustaceans belonging to the Family
Parastacidae (Riek, 1969). Four species of the genus Cherax are suitable for
culture, Cherax tenuimanus or ‘marron’, one of the largest freshwater crayfish in the
world, is native to the rivers of southwest Western Australia. C. albidus and C.
destructor are collectively known by the common name of ‘yabby’ and are found in
south eastern and central Australia, respectively (Austin, 1987; Holdich, 1993;
Ackefors, 1994). C. quadricarinatus or ‘redclaw’ is found in rivers of northern
Australia, east of Darwin flowing into the Timor Sea and Gulf of Carpentaria and
southern rivers in Paupa New Guinea (PNG) and Irian Jaya (Austin, 1996). The
increase in popularity of Australian freshwater crayfish in culture in Australia, and
overseas, in recent years has prompted research into improving existing culture
stocks of those species.
The high degree of morphological variability exhibited by many Cherax species has
led to problems with their systematics that, until recently, has been based largely on
comparisons of external morphological characteristics (Riek, 1969; Austin, 1986). A
comprehensive morphometric and allozyme study of C. destructor revealed two
distinct morphotypes that corresponded with significant genetic divergence,
supporting subspecies status for C. albidus (Campbell et al., 1994). Similarly, two
genetically distinct allopatric forms of C. tenuimanus have been described recently
(Austin, 1986; Nguyen et al., 2002), although these findings are currently being
questioned. The existence of discrete forms within what was previously considered
to be a single species of C. destructor, and potentially C. tenuimanus, has important
implications for the conservation management of these species, and the design of 1 Ht = Hs + Dsr + Drt (where Hs is the average gene diversity (heterozygosity) within; Dsr is the variance between tributaries within rivers, and Drt is the variance between different rivers)
12
aquaculture improvement programs. The taxonomy of C. quadricarinatus, the focal
species of the present study, is also uncertain and requires resolution so that wild
and culture stocks can be managed appropriately.
1.4.1 C. quadricarinatus culture
C. quadricarinatus has been farmed in Australia since the mid 1980s. The culture
potential of this species has also been recognised outside Australia and C.
quadricarinatus is now also cultured in the United States, South Africa, New
Zealand, China, Israel and Ecuador (Rubino, 1992; Karplus et al., 1995; Macaranas
et al., 1995; Rouse, 1995).
C. tenuimanus was the primary freshwater crayfish farmed in Queensland during the
1980s (pers. comm. Hutchings). However, C. tenuimanus proved unsuitable for the
tropical summers of southeast Queensland and many stocks were lost to heat stress
during one unusually hot summer (pers. comm. Hutchings). C. tenuimanus stocks
were quickly replaced with the tropical species C. quadricarinatus, that was being
cultured on a single farm. Originating from northern Australia, C. quadricarinatus are
well suited to tropical environments in Queensland and the Northern Territory. Only
limited C. quadricarinatus numbers of broodstock were collected from two southern
Gulf of Carpentaria rivers and crossed in the hope of producing hybrid vigour to
produce the original founding culture stock (pers. comm. Hutchings). The precise
natural origin of C. quadricarinatus broodstock and the degree to which they were
hybridised, however, remains unknown.
Variation in morphology, behaviour, habitat preference and some quantitative traits,
such as maximum body size, growth rate, and salinity tolerance, have been reported
among wild C. quadricarinatus stocks in Australia (Austin, 1986). Gu et al. (1995)
demonstrated significant variation for growth performance and differences in body
weight of juveniles at post-release ages among inbred lines developed from discrete
wild populations from three geographically discrete Gulf river stocks. He also
demonstrated that this variation was genetically based and could potentially be of
commercial value to the culture industry if the variation could be exploited in
systematic ways in culture (Gu et al, 1995). In parallel, there have been reports of
reduced productivity and physical abnormalities in cultured C. quadricarinatus
stocks in Israel which may be indicative of inbreeding depression resulting from low
genetic diversity caused by exposure to successive genetic bottlenecks (pers.
comm. Hulata). While industry development has occurred rapidly overseas
(compared to the Australian industry), there is little ability for international producers
13
to access new genetic material from the wild, so genetic resources in their culture
industries are likely to remain depauperate (and to depend on availability of
Australian culture stocks). In contrast, if genetic variation is high in wild populations,
then the Australian industry could benefit from a systematic resampling of wild
stocks for culture.
C. quadricarinatus has responded well to genetic selection programs. In 1993 a
limited selective breeding program for C. quadricarinatus was implemented at the
QDPI Freshwater Fisheries and Aquaculture Centre, Walkamin (Jones et al., 2000).
Strains were chosen from the five major catchments at the base of the Gulf of
Carpentaria. From east to west, these included stocks from the Mitchell, Gilbert,
Flinders, Leichhardt and Gregory rivers. Captive reproduction and pond grow out
revealed substantial variation in culture traits within strains, but little variation among
them. Flinders and Gilbert River stocks were chosen to develop a synthetic
‘Walkamin’ strain. Subsequent combined family selection of the Walkamin strain has
realised a significant improvement in growth rate (~9.5% increase) when compared
to existing culture stocks (Jones et al., 2000). The improved strain is currently being
evaluated under commercial farm conditions. This project deliberately targeted wild
stocks for the breeding program as levels of genetic variation in culture stocks were
unknown but considered likely to be deficient.
Ogden (2000) investigated juvenile growth performance among inbred lines of
divergent wild C. quadricarinatus stocks and their crosses under experimental tank
conditions. Although results were not conclusive due to a low number of replicates,
Ogden (2000) reported the potential for better performance of offspring of Flinders
and Weipa crosses and relatively poor performance in offspring of Flinders and
Howard crosses. Although crossing divergent individuals can result in heterosis,
introgression of divergent populations can also disrupt locally co-adapted gene
complexes resulting in unwanted outcomes. The breakdown of these complexes
may not be seen until the second or later generations when assortment of alleles at
different loci takes place. Ogden (2000) also reported that attempted crosses
between C. quadricarinatus from extreme ends of the species natural distribution
were unsuccessful, as no Weipa/Howard crosses were produced in his trials. While
this result is preliminary, one possible interpretation of this result may be that this
could be evidence for outbreeding depression.
14
1.4.2 C. quadricarinatus taxonomy
C. quadricarinatus as it is known currently was originally described as three taxa
(see Figure 3.1), based on external morphology (Reik, 1969). Eastern populations in
Queensland were classified as C. quadricarinatus (von Martens), western
populations in the Northern Territory were classified as C. bicarinatus (Gray, 1845)
and PNG populations as C. albertisii (Nobili, 1901), based on small differences in
the male genitalia, cephalothorax, number of rostral spines, chelae and body shape
(Reik, 1969). C. bicarinatus differed from C. quadricarinatus in the shape of the
areola and length of the rostral carinae combined with a slight difference in the
number of rostral spines (Reik, 1969). C. albertisii was described as possessing
narrower claws relative to the other two ‘species’ (Nobili, 1901). The natural
distributions of the three taxa were considered to be disjunct, and this was used to
support their recognition as discrete species.
Reik’s (1969) classification remained unchallenged until Austin (1996) carried out an
allozyme study of the three taxa. The 23 variable allozyme loci Austin used could
not distinguish between C. bicarinatus, C. albertsii and C. quadricarinatus and so he
regarded them as belonging to a single morphologically variable species (Austin,
1996). Austin (1996) concluded that morphological differentiation observed among
the species was most likely a reflection of morphological plasticity in response to
difference in regional environmental conditions, rather than evidence for discrete
species.
One important discovery since Reik’s (1969) classification is that the allopatric
‘species’ distributions he described (Figure 3.1) were not accurate. C.
quadricarinatus are found almost ‘continuously’ across many of the rivers flowing
into the Gulf of Carpentaria and the Timor Sea east of Darwin and the southern
rivers of PNG (Austin, 1996). Since only low levels of genetic differentiation were
evident among allopatric crayfish species, Austin argued that the three species
described by Reik (1969) should be reclassified under the single name C.
quadricarinatus.
15
Figure 1-1: Reik’s (1969) classification based on morphological differences of Cherax in northern Australia and southern PNG.
Macaranas et al. (1995) subsequently identified a single fixed allelic allozyme
difference, at the Carbonic Anhydrase locus (CA), between ‘western’ and ‘eastern’
C. quadricarinatus populations across northern Australia. Austin did not examine
this locus. Detection of a fixed allozyme difference contrasts with Austin’s
suggestion that C. quadricarinatus was genetically homogenous across its natural
range in northern Australia. Carbonic anhydrase catalyses the hydration of CO2 to
provides H+ and HCO3- for use in sodium and chloride uptake (Henry, 1988). This is
an important metabolic process during ion exchange in freshwater crayfish,
especially during crayfish intermoult stages (Wheatly and Gannon 1995).
Macaranas et al. (1995) suggested that the fixed difference was related to
differences in local water chemistry (pH) experienced by western (alkaline water)
versus eastern (acidic water) populations in northern Australia. Whether this
difference reflects historical isolation and independent evolution, or is the result of
extreme selection on pH regulation associated with environmental water chemistry,
is still unresolved, but it would be unwise to use this difference (in isolation) to
endorse the existence of discrete biological species.
As phenotype can be affected by environment, taxonomic delineations based solely
on morphometrics need to be interpreted with caution. Since allozyme studies of
most decapod crustaceans have generally revealed low levels of genetic variation
(Busack, 1988) even among discrete taxa, the use of allozyme data to characterise
AUSTRALIA
PAPUA NEWGUINEA
C. albertsii C. bicarinatus C. quadricarinatus
16
systematic relationships among decapods also needs to be treated with caution.
There now exists a vast body of literature that has demonstrated the ability of
molecular data (DNA) to delineate species boundaries (Avise, 1994; Bouchon et al.,
1994; Horovitz & Meyer, 1995) for sympatric taxa that display little or limited
morphological variation (Moritz & Joseph, 1993; Daniels et al., 2003; Gouws et al.,
2004).
A large amount of direct and indirect evidence suggests that extensive genetic
diversity may be present in wild C. quadricarinatus populations. However, it is not
currently known how much genetic variation has been exploited in existing culture
stocks, or how much genetic diversity is distributed among wild populations. The C.
quadricarinatus culture industry could benefit substantially from the application of
genetic diversity studies and this information could also assist in design of detailed
management policies for conservation of wild genetic resources for the species in
Australia.
Commercial culture of C. quadricarinatus, like many aquaculture ventures, began in
a haphazard way, without a systematic analysis of wild populations to generate a
genetically diverse founding culture stock. Furthermore, many C. quadricarinatus
farms have obtained their stocks from other farms, a process that exposes culture
stocks to sequential bottlenecks that could negatively impact on genetic diversity
levels. Ideally, development of a healthy commercial C. quadricarinatus culture
stock would have involved the evaluation of wild stocks under culture conditions,
initiation of large broodstock populations and a centrally based hatchery that
monitored and maintained genetic diversity in stocks from which new farms could
obtain high quality broodstock. At this stage the industry has little knowledge of the
genetic diversity in wild or cultured C. quadricarinatus stocks. As most C.
quadricarinatus farmers began as hobby farmers and husbandry practices are still
being optimised, long term issues of genetic diversity were of little concern at the
time. The C. quadricarinatus industry is now expanding in Australia, so low genetic
diversity in C. quadricarinatus culture stocks could represent a major impediment to
productivity for farmers both domestically and internationally in the future.
1.5 Research Objectives The current study is the first comprehensive evaluation of genetic diversity in wild
populations of an economically important Australian native aquaculture species. A
detailed genetic inventory and description of stocks is essential for meaningful stock
management and conservation programs. Optimal long term management and
17
conservation of wild C. quadricarinatus will depend on knowing the distribution of
genetic resources for culture so that their integrity and diversity can be sustained.
The study aims to provide a detailed description of the levels and patterns of genetic
diversity in wild C. quadricarinatus populations and to compare them with the
genetic diversity in representative commercial stocks in Australia and from
overseas.
1.6 Research Plan Collection of wild C. quadricarinatus population were carried out across the species’
natural distribution in Australia and PNG by field collections, samples obtained by
collaborators and by access to museum collections. Sampling was hierarchical in
nature and assessed variation broadly across the species range, among major
drainage basins, among rivers within major drainage basins, and within single major
river systems. Cultured populations of C. quadricarinatus were also sourced from
Australian and overseas farms, allowing for comparisons of genetic diversity levels
to be made between wild and domesticated stocks. The analysis was also
structured to identify the likely wild origins of sampled culture stocks. Genetic
markers were also used to assess the likely effects of past culture practices on
genetic diversity levels in this species.
1.7 Thesis structure General methodologies are described in Chapter 2, where information regarding the
sampling design, location of collection sites and genetic markers used are
presented. Before new germplasm can be sourced from wild stocks, C.
quadricarinatus systematics requires clarification. Since, results of morphometric
and allozyme studies have proven contradictory and ineffective for unambiguous
systematic designation, mitochondrial DNA markers were employed to investigate
phylogenetic relationships among wild C. quadricarinatus populations; the results of
this analysis are presented in Chapter 3. The identification of evolutionary significant
lineages is essential if new germplasm is likely to be sourced systematically for use
in culture in the future, especially when the taxonomy of C. quadricarinatus is in
doubt.
Knowledge of stock structure is an important prerequisite for developing a diverse
founder stock that will have the necessary genetic attributes and diversity to respond
positively to artificial selection programs. Although mtDNA markers are powerful
tools for determining historical relationships among C. quadricarinatus populations,
contemporary gene flow can also influence stock structure. Microsatellite markers
18
are ideal candidates for quantifying population genetic structure of wild C.
quadricarinatus populations; results of this analysis are presented in Chapter 4.
The process of domestication can sometimes rapidly compromise levels of genetic
diversity resulting in reduced fitness of culture stocks that may affect productivity.
Chapter 5 investigates the levels of genetic diversity in Australian and overseas
cultured C. quadricarinatus stocks, these data were compared to levels of genetic
diversity detected in wild populations. Microsatellite markers can be used routinely
to monitor levels of genetic diversity. Chapter 6 provides a general discussion of the
major findings of the study and discusses their consequences and applications for
the C. quadricarinatus culture industry in the future.
Chapter Two: General Methods
19
2.0 General Methods
2.1 Sample Collection and Storage Wild C. quadricarinatus populations occur in rivers flowing into the Gulf of
Carpentaria and the Timor Sea east of Darwin, (Figure 2-1), and unconfirmed
reports suggest C. quadricarinatus may also occur naturally in some rivers to the
west of Darwin. Wild populations are also found in some southern flowing rivers in
Papua New Guinea (Austin, 1986). A large population of C. quadricarinatus found
outside the described natural range in Australia was also included from the Ord
River (Kununurra, WA). The remoteness of rivers in the Northern Territory and the
Ord River in WA means that wild C. quadricarinatus populations in this region may
have remained undocumented until recently. However, there has been potential for
translocations of C. quadricarinatus populations among rivers in recent times. Due
to the popularity of C. quadricarinatus as a recreational fishing species, some
populations have been translocated intentionally to waterways and impoundments
where they do not occur naturally. Therefore, while presence of populations in the
Ord may be natural, they may also have resulted from translocation events
associated with efforts to develop the species in culture in the region or as bait used
by recreational fisherman for freshwater sport fishing (eg barramundi).
Wild populations of C. quadricarinatus from across the natural range in northern
Australia were collected according to the following criteria: 1) they consisted of
essentially natural, undisturbed populations, 2) major regions/drainage systems
across the natural distribution were represented and 3) in order to identify the
distribution of genetic variation at various levels of scale, a hierarchical method of
sampling was employed to investigate genetic variation among sites within individual
drainages, among major drainages within a region and among regions in northern
Australia and PNG.
C. quadricarinatus in the wild have a large natural distribution, however, much of this
region consists of ephemeral rivers. Finding significant permanent water bodies in
some river systems proved difficult during field trips. Also, large numbers of
Macrobrachium rosenbergii (the giant freshwater prawn) were observed at many
sites where C. quadricarinatus were apparently absent. In general, field
observations found that where M. rosenbergii were present, C. quadricarinatus were
often absent and vice versa.
Chapter Two: General Methods
20
Figure 2-1: Shaded areas illustrate the natural distribution of C. quadricarinatus in Australia and New Guinea (Austin, 1986). Rivers shown here have been sampled for this study; please note these are not all rivers in this region and those shown may be ephemeral.
Crayfish were caught in two ways; 1) Traps were set in the late afternoon, left
overnight and checked first thing the next day. At least ten ‘Opera House’ traps
baited with dry dog biscuits (pers. comm. Clive Jones) were used at each location,
placed 10 – 20m apart. If no crayfish were caught over two consecutive nights, the
site was abandoned. 2) Shallow water bodies with little vegetation near the edge
were also sampled with a cast net. This method proved successful in obtaining a
complete sample from a shallow pool in the Norman River. After tail clips were
taken, individuals were returned live to the their catch site. C. quadricarinatus tissue
(muscle tissue or tail clips) were preserved in 70% ethanol. Table 2-1 describes
location, population size and collection date for sampled wild C. quadricarinatus
populations.
Chapter Two: General Methods
21
Table 2-1 Sampling sites, drainage system, number of individuals analysed for mtDNA and microsatellites and date collected for the present study. Sample sites are listed from west to east. *Samples supplied from the Queensland Museum. ^Refer to acknowledgements for collectors.
Population Name
Site Location Drainage n (mtDNA)
n (microsat)
Date Collected
Kununurra Kununurra Dam, WA^ Ord 2 22 June, 2002 Howard Near Howard Springs, NT^ Howard 2 30 Dec, 1996 Adelaide 50km east of Humpty Doo, Adelaide
River, NT^ Adelaide 2 24 Dec, 1996
Roper Mataranka, Roper River, NT Roper 2 11 Oct, 1999 McArthur Cape Crawford, McArthur River, NT McArthur 2 25 Oct, 1999 Calvert ‘Pungalina’, Calvert River, NT Calvert 2 23 Oct, 1999 Gregory ‘Gregory Downs’, Gregory River,
QLD Gregory 2 33 Oct, 1999
Louie Louie Creek, QLD* Gregory 2 - June, 1995 Leichhardt Near Leichhardt Falls, Leichhardt
River, QLD Leichhardt 2 - Nov, 2002
Flinders Near Richmond, Flinders River, QLD^ Flinders 2 32 Aug, 1996
Norman Croydon, Norman River, QLD Norman 2 32 Sept, 2002 Gilbert Developmental Road Crossing,
Gilbert River, QLD^ Gilbert 2 34 Aug, 1996
Einsleigh Einsleigh, Einsleigh River, QLD Gilbert 2 - Sept, 2002 Elizabeth Mount Surprise, Elizabeth River,
QLD Gilbert 2 18 Sept, 2002
Mitchell ‘Lake Mitchell’, Mitchell River, QLD^ Mitchell 2 34 Aug, 1996 Chillagoe Chillagoe, Chillagoe River, QLD Mitchell 2 32 Sept, 2002 Weipa 50km east of Weipa, QLD^ Mission 2 30 Aug, 1996 Lockerbie Lockerbie River, QLD* Jardine 2 - Oct, 1990 Bensbach Bensbach River, PNG^ Bensbach 2 - Sept, 1999 Oriomo Oriomo River, PNG^ Oriomo 2 - Dec, 1999 MtBosavi MtBosavi, PNG* Kikori 2 - Oct, 1995
Three C. quadricarinatus culture stocks, Yandina, Parkridge and Hutchings, and the
DPI improved hybrid strain ‘Walkamin Strain’ were sampled as representatives of
southeast Queensland culture stocks. Table 2-2 describes farm location, population
size and collection date for farmed C. quadricarinatus stocks.
The Hutchings farm at Aratula in south-east Queensland was the first C.
quadricarinatus farm in Queensland and this farm has subsequently supplied stock
to many other farms. Robin Hutchings (pers comm) developed a farmed stock from
a mixture of wild stock collected from at least two Queensland rivers – Flinders and
Gilbert Rivers. C. quadricarinatus has become a popular culture species overseas
and is now farmed in the USA, South Africa, China, Israel, Mexico and Ecuador
(Karplus et al., 1995; Macaranas et al., 1995; Rouse, 1995). C. quadricarinatus
producers overseas were contacted and tail clip samples preserved in 70% ethanol
were obtained from them.
Chapter Two: General Methods
22
Table 2-2 Stock name, location, sample size and date collected of farmed C. quadricarinatus stock sampled in this study. Please see acknowledgements for collaborators.
Stock Name Location n Date Collected
Yandina 1996 South East Qld, Australia 30 1996 Yandina 2002 South East Qld, Australia 30 2002 Parkridge South East Qld, Australia 30 1996 Walkamin North East Qld, Australia 25 2002 Hutchings South East Qld, Australia 30 2002 Israel Israel 25 2002 Mexico Mexico 40 2002 Ecuador Ecuador 25 2002
Reference samples of closely related Cherax taxa to be used as outgroups for
phylogenetic analyses - C. destructor and C. tenuimanus were obtained from Dean
Jerry at CSIRO and C. rhynchotus was sourced from the Queensland Museum
courtesy of Peter Davies.
2.2 Genetic Markers Two classes of genetic marker (mitochondrial and microsatellite DNA markers) have
dominated the field of population genetics since the development of the polymerase
chain reaction (PCR). MtDNA has proven to be very powerful for genealogical and
evolutionary studies of animal populations (Avise et al., 1987; Bernatchez &
Guyomard, 1994; Crandall & Fitzpatrick, 1996) and microsatellites have become the
most widely used genetic marker in recent times used to infer population genetic
structure and for population dynamic studies (Bruford & Wayne, 1993; Paetkau et
al., 1995; King et al., 2001).
2.2.1 Mitochondrial DNA
Crustacean mtDNA was first isolated by Batuecas et al. (1988) in a study of the
genome organisation of the mitochondrial organelle in Artemia. Since this time, a
number of mtDNA genes have been targeted in crustaceans for phylogenetic
purposes. These include the ribosomal RNA genes 16S and 12S, cytochrome
oxidase I (COI) and Cytochrome b (Cyt-b). While COI and Cyt-b are mitochondrial
protein coding genes, the 12S and 16S genes are structural rRNA, non-protein
coding genes.
The combination of both variable and conserved regions within the same gene is
most likely the major reason why 16s rRNA has become one of the most popular
genes used for reconstructing phylogenies in many decapod crustaceans (Crandall
Chapter Two: General Methods
23
et al., 1999; Crandall et al., 2000). In parallel, COI has revealed high levels of
variation in many arthropods, and has also proven successful for delineating
divergent clades in many crustacean taxa (Cook, 2002). Estimates of mutation rates
and molecular clocks used to infer time since divergence of independent clades in
crustaceans can be calculated using both 16S and COI sequences (Schneider-
Broussard et al., 1998). Such time frames for cladogenesis can allow insights into
earth history events which may have influenced divergence among monophyletic
lineages identified in genetic studies.
PCR enables the amplification of specific DNA sequences for analysis. Specific
primers have been published for an array of taxa, targeting many different
mitochondrial genes, which makes the study of the mitochondrial genome attractive.
A number of universal primers allow the amplification of genes across divergent taxa
possible, enabling the design of species-specific primers if required. Universal
primers targeting 16s, 12s, Cyt-b, COI, COII/III, ATPase and control region were
trialled on C. quadricarinatus DNA for PCR repeatability. 16S and COI were
selected for further investigation in this study
2.2.2 Microsatellite DNA
Microsatellites are iterations of 1-6bp nucleotide motifs, also known as simple
sequence repeats (SSRs) or short tandem repeats. They have been detected in the
genomes of every organism examined so far and they are distributed randomly or
almost randomly over the euchromatic genome in both coding and non-coding
regions (Jarne & Lagoda, 1996; Estoup et al., 1998). They are inherited in a co-
dominant pattern and are usually characterised by a high degree of length
polymorphism (Li et al., 2002). The origin of polymorphism is still debated, though
most appear likely to be due to slippage events during DNA replication (Schlötterer
& Tautz, 1992). Despite the fact that the mechanism(s) of microsatellite evolution
are still unresolved, they are considered to be the most powerful genetic markers
currently available due to their high variability and amenability to population genetic
analysis (Ruzzante et al., 1998). Microsatellites are also among the fastest evolving
DNA sequences with mutational rates varying from 10-2 to 10-6 events per locus per
generation. The mutation rate of a particular microsatellite is usually unknown and
the mutation process can display distinct differences among species, repeat types,
loci and alleles (Ellegren, 2000; Schlötterer, 2000; Li et al., 2002). Microsatellite
variation is manifested predominantly as changes in the number of repeats and so
alleles can be screened by electrophoresis to separate different fragment sizes.
Chapter Two: General Methods
24
Microsatellites are mostly species specific, however, conservation of primer
sequences across closely related taxa has been observed (Moore et al., 1991;
FitzSimmons et al., 1995; Chapuisat, 1996; Coltman et al., 1996). However, cross
amplification in related taxa can often result in null alleles where mutations in primer
sites lead to a failure in amplification of some alleles in a closely related species
(Pienkowska & Schelling, 2001). To overcome this potential problem, most studies
develop species-specific primer sets. Microsatellite primers were not available for
any Cherax species at the time of commencement of this study so C.
quadricarinatus specific microsatellite primers were developed from first principles
(Baker et al., 2000).
2.3 Geographic distance among sampled wild populations Two distance measures were employed. Coastal distance, measuring the real
distance between river mouths; and overland distance, measuring the minimum
distance between tributaries of neighbouring rivers.
Chapter Three: Phylogenetics of wild C. quadricarinatus
23
3.0 Phylogenetic relationships among wild C. quadricarinatus populations 3.1 Introduction Organisms that inhabit riverine systems can show a variety of population structures
that are usually related to relative dispersal capability and/or past earth history events
(Heads, 1999; Nagel, 2000; Waters et al., 2001a; Glaubrecht & von Rintelen, 2003; de
Bruyn et al., 2004). Zink et al. (1996) studied the evolutionary genetics of Hawaiian
freshwater fish and reported a lack of phylogenetic structure, even though fish were
confined to islands surrounded by ocean. They suggested that the amphidromous
(marine) larval phase of these fish facilitated extensive gene flow among islands. In
contrast, Bernatchez and Wilson (1998) observed that populations in different
freshwater drainages are effectively ‘islands’, as unfavourable habitat conditions
(terrestrial or unsuitable aquatic) among separate drainages restrict obligate freshwater
species to single drainage systems. Geomorphological events, such as uplift that result
in waterfalls or changes in flow direction, can also play an important role in shaping
genetic relationships among populations of freshwater species (Hughes, 1996;
Hurwood & Hughes, 1998; Waters et al., 2001a; de Bruyn et al., 2004). Earth history
events can interrupt gene flow for long periods and play a role in the eventual formation
of new species, assuming allopatric models of speciation (Mayr, 1942; Otte & Endler,
1989; Avise & Wollenberg, 1997).
Evidence suggests that past fluctuations in sea level have influenced the genetic
structure of a number of terrestrial and aquatic species across northern Australia and
PNG (Chenoweth et al., 1998; Keogh, 1998; McGuigan et al., 2000; Unmack, 2001;
Ladiges et al., 2003; de Bruyn et al., 2004). In contrast to present day sea levels that
have broken freshwater connections between Australia and New Guinea, sea levels
have been lower in the past and would have facilitated connectivity for terrestrial and
freshwater taxa in Australia. For example, rainbow fish (McGuigan et al., 2000) and the
green python, Morelia viridis (Rawlings & Donnellan, 2003) are believed to have
dispersed between northern Queensland and PNG when sea levels were lower.
The southern half of New Guinea forms part of the Australian tectonic plate and has
been an integral part of continental Australia since the Australian plate split from the
Antarctic core of Gondwana about 95 MYA (Veevers, 1984). As sea levels fluctuated
periodically, Australia and New Guinea have been alternately linked by terrestrial
corridors or separated by marine incursions on a number of occasions over millions of
years (Chappell, 1983). Voris (2000) hypothesized that a large ancient river system
Chapter Three: Phylogenetics of wild C. quadricarinatus
24
existed at times of lower sea levels that linked major rivers in southern New Guinea to
northern Australia (Figure 3.1a). There is also evidence to suggest that throughout
much of the Pleistocene, a large freshwater to brackish water lake, Lake Carpentaria,
formed in what is today the Gulf of Carpentaria (Torgersen et al., 1985; Jones &
Torgersen, 1988) (Figure 3.1b). This lake existed periodically at times of low sea level
until about 8500 years ago (Chappell, 1983).
Figure 3-1: 1) Ancient river system at -120m sea level contour, 2) Lake Carpentaria shown at the-75m sea level contour. Present day sea level also indicated in dark grey. The ancient shorelines are based on present day depth contours; the major Pleistocene river systems are depicted (Voris, 2000).
Interestingly, across the same distribution of C. quadricarinatus in northern
Australia/PNG, four discrete genealogical lineages of the giant freshwater prawn
(Macrobrachium rosenbergii) have been identified recently: (i) a Western Australian
lineage; (ii) a Gulf of Carpentaria/Northern Territory lineage; (iii) an Irian Jayan lineage;
and (iv) a Papua New Guinean/NE Australian (Cape York) lineage (de Bruyn et al.,
2004). de Bruyn et al(2004) also hypothesised that the intermittent existence of Lake
Carpentaria facilitated dispersal of M. rosenbergii among Gulf of Carpentaria rivers. M.
rosenbergii can survive approximately 3 weeks as post larvae in sea water. Adults can
survive in brackish water for extended periods of time, but individuals will not tolerate
full marine conditions for more than a week (de Bruyn et al. 2004). C. quadricarinatus
spends its whole life in freshwater, unlike M. rosenbergii that has a short brackish
water larval phase, therefore more genetic divergence among populations isolated in
the same drainage system could be expected in C. quadricarinatus.
Chapter Three: Phylogenetics of wild C. quadricarinatus
25
Mitochondrial DNA (mtDNA), by virtue of maternal inheritance and a non-recombining
haploid nature, has a four-fold smaller effective population size than equivalent nuclear
genes which make it a powerful tool for detecting population structure in natural
systems (Wollenburg & Avise, 1998). The control region has the highest mutation rate
of any mitochondrial gene, whereas the ribosomal genes (12s and 16s) are generally
considered to be the most highly conserved regions (Parker et al., 1998).
Monophyletic lineages in intraspecific gene trees can be detected using mtDNA, and
the degree of molecular divergence among lineages estimated from mtDNA haplotypes
can be dated using a molecular clock approach (Brown et al., 1979). Estimates of time
frames for cladogenesis will allow insight into potential earth history events that may
have influenced any divergence observed among C. quadricarinatus populations.
Combining the results of two mtDNA loci that evolve at different evolutionary rates, will
allow for a comprehensive interpretation of the levels and patterns of genetic
divergence that may exist among wild C. quadricarinatus populations. The aim of this
study was, therefore, to determine phylogenetic relationships among wild stocks of the
putative single species of C. quadricarinatus in northern Australia and southern PNG.
Sequences of two mtDNA genes (16s and COI) from crayfish sampled from river
systems collected across the natural distribution of C. quadricarinatus in Australia and
PNG were examined to determine genetic differentiation and phylogenetic relationships
among wild stocks.
Chapter Three: Phylogenetics of wild C. quadricarinatus
26
3.2 Mitochondrial DNA Methodology
3.2.1 Samples
Wild C. quadricarinatus were sampled from 17 drainages across northern Australia and
southern PNG. Two individuals from each location were sampled for use in 16s and
COI analyses.
Table 3-1: Site Location, river drainage, abbreviation used in following tables and sample size for 16s and COI mtDNA gene analysis of C. quadricarinatus used in this phylogenetic study.
Site Location Drainage Abbrev. n (16s) n (COI) Kununurra Dam, WA Ord Ord 2 2 Howard River, NT Howard How 2 2 Adelaide River, NT Adelaide Ade 2 2 Roper River, NT Roper Rop 2 2 McArthur River, NT McArthur McA 2 2 Calvert River, NT Calvert Cal 2 2 Nicholson River, NT&QLD Gregory Nic 2 - Gregory River, QLD Gregory Gre 2 2 Louie Creek, QLD Gregory Lou - 2 Leichhardt River, QLD Leichhardt Lei 2 - Flinders River, QLD Flinders Fli 2 2 Norman River, QLD Norman Nor 2 2 Gilbert River, QLD Gilbert Gil 2 2 Little River, QLD Gilbert LR - 2 Einsleigh River, QLD Gilbert Ein - 2 Elizabeth River, QLD Gilbert Eli - 2 Mitchell River, QLD Mitchell Mit 2 2 Lower Mitchell, QLD Mitchell LMit - 2 Rosser Creek Mitchell RC - 2 Chillagoe River, QLD Mitchell Chi - 2 Weipa, QLD Mission Wei 2 2 Lockerbie, QLD Jardine Loc 2 2 Bensbach River, PNG Bensbach Ben 2 2 Oriomo River, PNG Oriomo Ori 2 2 MtBosavi, PNG Kikori MtB 2 2
3.2.2 DNA Extraction
Initial sequence data from Cytochrome Oxidase I (COI) obtained using whole genomic
C. quadricarinatus DNA, suggested that variation may result from a pseudogene. This
phenomenon has been reported in a wide range of organisms, including a closely
related species, C. destructor (duplication of 16s gene region) (Nguyen et al., 2002).
To overcome the potential for amplifying translocated genes a specific mtDNA
extraction protocol was employed to isolate mtDNA and remove nDNA before
amplification.
Chapter Three: Phylogenetics of wild C. quadricarinatus
27
3.2.3 Mitochondrial DNA Extraction
Mitochondrial DNA (mtDNA) was extracted using a modified procedure developed by
Tamura and Aotsuka (1988). This extraction method was carried out as follows:
approximately 100mg of C. quadricarinatus muscle tissue or tail clip was digested in
1mL homogenising buffer (0.25M sucrose, 10mM EDTA, and 30mM Tris-HCl, pH 7.5)
and 10μl of 20mg/mL Proteinase K for 1–2 hours. This solution was centrifuged at
1000g for 1 min to pellet nuclei and cellular debris. The supernatant was recovered and
centrifuged at 12 000g for 10mins to pellet the mitochondria. The pellet was
resuspended in 100μl 10mM tris- EDTA pH 8.0, and 10mM EDTA. To this, 200μl of
freshly prepared 0.18M NaOH containing 1% sodium dodecyl acetate (SDS) was
added and incubated on ice for 5min. 150μl of ice-cold solution of 3M potassium and
5M acetate was added and the sample incubated on ice for a further 5 min. This
mixture was centrifuged at 12 000g for 5 min and the supernatant recovered. Equal
volumes of phenol:chloroform/isoamyl was added, the sample mixed thoroughly and
centrifuged for 2 min at 12 000g. The aqueous layer was transferred to a fresh tube
and twice the volume of ethanol added and the sample then stored at –20oC for 15min
to precipitate the mtDNA. After centrifugation at 12 000g for 15 – 20 minutes the
resulting mtDNA pellet was washed with 1ml 70% ethanol and then dried at room
temperature. The pellet was suspended in 50μl of water and stored at -20oC until
required for genetic analysis.
3.2.4 PCR Analysis
Universal crustacean ribosomal 16s (Crandall & Fitzpatrick, 1996) primers were
utilised, in combination with published cytochrome oxidase I primers (Palumbi et al.,
1991) to successfully amplify C. quadricarinatus mtDNA. The degenerate primer (COf-
L) was replaced with a specific primer designed here for C. quadricarinatus to ensure
specificity during PCR and unambiguous sequence results.
16s ribosomal DNA Primers (Crandall and Fitzpatrick, 1996)
16S71 (forward): ATA ARG TCT RAC CTG CCC 1472 (reverse): AGA TAG AAA CCA ACC TGG
Cytochrome Oxidase I Primers (Palumbi et al, 1991)
COa-H: AGT ATA AGC GTC TGG GTA GTC COf-L (replaced): CCT GCA GGA GGA GGA GAY2 COcq-L (this study): CGG CAT AGT CTC ACA CAT CG
2 Y=C/T
Chapter Three: Phylogenetics of wild C. quadricarinatus
28
3.2.5 Sequencing of mtDNA Haplotypes
PCR products for sequencing were purified according to the protocols of QIAquick
PCR Purification Preps (QIAGEN Inc.). Approximately 50ng of purified DNA template
was combined with 3.2 pmoles of each forward or reverse primer, 1μl of ABI (Applied
Biosystems Incorporated) Big Dye version 3.1, 3μl dilution buffer (400mM Tris, pH 9.0,
10mM MgCl2) and made up to 12μl volume with ddH20. Sequencing reactions were
then amplified under the following conditions: initial denaturation at 94oC for 5 mins
followed by 30 cycles of 96oC for 10 secs, 50oC for 5 secs, 60oC for 4 mins and 10mins
at 4oC. Each sequencing reaction was mixed with 2μl 3M sodium acetate (pH4.6) and
50μl of 95% ethanol. Tubes were vortexed briefly and left at room temperature for
15mins. Tubes were then centrifuged for 20mins at 13000rpm. The supernatant was
removed and the pellet washed with 250μl of 70% ethanol and centrifuged for a further
5 mins at 13,000rpm. The supernatant was then removed and the pellet air dried.
Sequencing was conducted at AGRF (Australian Genetic Research Facility, Brisbane).
C. quadricarinatus sequences were edited in Chromas 2.13 (Technelysium Pty Ltd)
and aligned with the ClustalW analysis (Thompson et al. 1994) using the Australian
National Genomic Information Service (ANGIS) online computer package.
3.3 Statistical Analysis
3.3.1 Neutrality Tests
Fu and Li’s (1993) D and F tests were performed on the C. quadricarinatus sequences
using DNASP version 3.99 (Rozas & Rozas, 2003).
3.3.2 Testing for saturation
The probability that nucleotides are the same due to chance convergence increases
with time since divergence. Testing for saturation involves plotting uncorrected against
corrected genetic distance. When a scatter plot of uncorrected versus corrected
distances is made, the degree to which points deviate from the line of best fit indicates
saturation and the degree of homoplasy (Reed & Sperling, 1999). In faster evolving
DNA regions (eg. COI), the level of saturation is usually greater than that evident in
slower evolving (eg. 16s) regions.
3.3.3 Phylogenetic reconstruction of wild C. quadricarinatus populations
Pairwise nucleotide differences among mtDNA haplotypes were calculated in MEGA
version 2.1 (Kumar et al., 2001) using an appropriate substitution model as determined
Chapter Three: Phylogenetics of wild C. quadricarinatus
29
in Modeltest (Posada & Crandall, 1998). A gamma value (for each gene sequence
determined using PAUP* version 4 (Swofford, 2003)) was used to account for variable
rates of substitutions at different nucleotide sites. The resulting distance matrix was
used to construct trees with Neighbour Joining and Maximum Likelihood algorithms.
Statistical support for trees were tested using 1000 bootstrap replicates (Felsenstein,
1985). A closely related Cherax species, C. destructor, was used as an outgroup for
resolving C. quadricarinatus relationships.
Minimum spanning networks were constructed using TCS 1.11 (Clement et al., 2000).
TCS implements the estimation of gene genealogies from DNA sequence data
described by Templeton et al. (1992). The advantage of this approach is that it allows
haplotypes to form nodes in the network, which is important for intraspecific data
because ancestral haplotypes can be identified in samples, which may themselves
have given rise to more derived (recent) haplotypes.
3.3.4 Isolation by distance
To determine whether population structure was influenced by geographic distance,
isolation by distance analysis was carried out using IBD ver 1.5 (Bohonak, 2002).
Pairwise distance estimates were calculated in MEGA and correlated with geographic
distance using the matrix correlation methods of the Mantel test. The genetic and
geographic distance estimates were both log transformed.
3.3.5 Molecular clock estimates
A molecular clock approach proposes that genes evolve at rates that are roughly
constant over time and across evolutionary lineages (Brown et al., 1979). If divergence
accumulates in a relatively clockwise fashion, then time scales can be estimated for
important evolutionary events in the absence of fossil evidence. Based on molecular
clock theory, each specific gene or protein of an organism can serve as an
independent molecular clock. This is based on the fact that each protein has a distinct
rate of evolution depending on individual level of functional constraint. The less
functional constraint on a molecule, the faster it will evolve in terms of substitution rate
compared with molecules subject to stronger constraints (Nei & Koehn, 1983).
A chi-square test for homogeneity of base composition was implemented in TREE-
PUZZLE 5.2 (Schmidt et al., 2002) to test the clock like evolution of C. quadricarinatus
mtDNA sequences. TREE-PUZZLE compared trees generated under the assumption
of a molecular clock with trees unconstrained by a molecular clock (Felsenstein, 1988).
Chapter Three: Phylogenetics of wild C. quadricarinatus
30
Molecular clocks have been calibrated for many taxa, primarily within the bounds of
particular genes (Swofford et al., 1996). 16s mtDNA in crustacean has been estimated
to accumulate mutations a 0.53 – 0.96% per million years (Myr) (Sturmbauer et al.,
1996; Stillman & Reeb, 2001)) and COI at 1.4 – 2.6% MYR (Knowlton & Weigt, 1998;
Schneider-Broussard et al., 1998).
3.4 Mitochondrial Results
3.4.1 Analysis of 16s Sequence diversity
Sequence data for 36 C. quadricarinatus individuals from 482bp of 16s rRNA sequence
revealed 38 variable nucleotide positions resulting in 11 unique haplotypes. Haplotypes
were distributed among 18 populations from discrete drainages across northern
Australia and PNG. Table 3-2 details the informative nucleotide sites among the 16s C.
quadricarinatus sequences; populations are listed in a geographical, sequential fashion
with Australian rivers from west to east, followed by PNG rivers from west to east. No
variation was detected between any two individuals sequenced from the same site and
some haplotypes were shared among neighbouring rivers. For example Adelaide and
Howard exhibited the same 16s haplotype; the five ‘western gulf’ rivers, McArthur,
Calvert, Gregory, Nicholson and Leichhardt also shared a single common haplotype.
Chapter Three: Phylogenetics of wild C. quadricarinatus
31
Table 3-2: Informative sites among sampled C. quadricarinatus river populations from 482bp of 16s mtDNA identified by sequencing. Dots indicate homology to the Ord River haplotype. (WGC – western Gulf of Carpentaria; SGC – southern Gulf of Carpentaria)
Position of variable site (482bp) Haplotype River population 50 91 93 95 96 97 98 134 145 158 167 174 177 180 189 213 265 279 283 284 288 290 293 295 299 316 323 325 342 370 410 418 419 427 477 478 478 482
West 1 Ord A A C C G A A G A A A T T G G C C G T T T G T A T G A T A A T T A A G C G A West 2 Howard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . G . . . C G A G West 2 Adelaide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . G . . . C G A G West 3 Roper . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C . East 1 McArthur G . . . . G . A . . . A . . . T T . . . . A . . C A . . . G . C G G . . . . East 1 Calvert G . . . . G . A . . . A . . . T T . . . . A . . C A . . . G . C G G . . . . East 1 Gregory G . . . . G . A . . . A . . . T T . . . . A . . C A . . . G . C G G . . . . East 1 Nicholson G . . . . G . A . . . A . . . T T . . . . A . . C A . . . G . C G G . . . . East 1 Leichhardt G . . . . G . A . . . A . . . T T . . . . A . . C A . . . G . C G G . . . . East 2 Flinders G . . . . G . A . . . A . . . T T . . . . A . G C A . . . G . C G G . . . . East 2 Norman G . . . . G . A . . . A . . . T T . . . . A . G C A . . . G . C G G . . . . East 2 Gilbert G . . . . G . A . . . A . . . T T . . . . A . G C A . . . G . C G G . . . . East 3 Mitchell G . . . . G G A . . . A . . . T T . . . . A . G C A . . . G . C G G C G A G
East 4 Weipa G . . . . G . A . . . A . . . T T . . . . A . . C A . . . G . C G G C G A G East 5 Jardine G . . . . G . A . . . A . . . T T . . . . A . G C A . . . G . C G G C G A G PNG 1 Bensbach G . . . . G . A . . T A . . . T T . . . . A . G C A . . . G . C G G C G A G PNG 2 Oriomo G G . . . G . . . . G A . A . T T . . . . A . . C A . . . . . C . . . . T . PNG 3 MtBosavi G . T T C G . . G T . A C . A T T A C C C A G . C A T C G . . C . . . . . .
Chapter Three: Phylogenetics of wild C. quadricarinatus
32
Pairwise haplotype distances are presented in Table 3-3. Modeltest results suggest
that the Tamura and Nei (1993) model of nucleotide substitution was appropriate for
the C. quadricarinatus 16s data. This model accounts for variable substitution rates
between purines and pyrimidines and GC content. The greatest pairwise haplotype
divergence found among Australian C. quadricarinatus populations was evident
between the southern gulf haplotype, shared by Flinders, Norman, Gilbert rivers and
the western haplotype of the Adelaide and Howard rivers (3.9% difference). A large
divergence of 3.5% was also evident between populations from Weipa and the
Roper River located on opposite sides of the Gulf. Mt Bosavi in PNG showed a large
divergence (ranging from 3.9 – 6%) from all Australian and other PNG C.
quadricarinatus populations. Oriomo also showed a relatively large divergence from
other C. quadricarinatus populations (ranging from 1.7 – 3.5%); whereas, Bensbach
(PNG) samples shared a very close relationship with northern Queensland, being
only 0.2% and 0.4% different from Jardine and Weipa haplotypes, respectively. Like
northern Queensland populations, Bensbach samples were also divergent from
western Australian haplotypes, up to 3.9% (Ord).
3.4.1.1 Neutrality tests
Both Fu and Li tests were non-significant, therefore, C. quadricarinatus 16s
sequences were assumed to be evolving according to a neutral model (Fu and Li's
D: -1.18030: (P > 0.10); Fu and Li's F: -1.15721: (P > 0.10)).
3.4.1.2 16s saturation plots
After plotting uncorrected (p distance) versus corrected (Tamura Nei (1993) gamma
= 0.11) distance measures for C. quadricarinatus 16s haplotypes revealed no
evidence of saturation (R2 = 0.9839: data not shown).
Chapter Three: Phylogenetics of wild C. quadricarinatus
33
Table 3-3: Relationship among sampled populations based on 16sRNA sequences. Number of base pair differences between C. quadricarinatus river 16s haplotypes in the upper matrix; p distance of C. quadricarinatus 16s haplotypes in the lower matrix. Rivers are listed west to east. Highest and lowest values are in the bold.
Ord Howard Adelaide Roper McArthur Calvert Gregory Nicholson Leichhardt Flinders Norman Gilbert Mitchell Weipa Jardine Bensbach Oriomo MtBosavi Ord 5 5 1 13 13 13 13 13 14 14 14 19 17 18 19 13 24 Howard 0.010 0 5 18 18 18 18 18 19 19 19 16 14 15 16 17 29 Adelaide 0.010 0.000 5 18 18 18 18 18 19 19 19 16 14 15 16 17 29 Roper 0.002 0.010 0.010 14 14 14 14 14 15 15 15 19 17 18 19 13 25 McArthur 0.027 0.037 0.037 0.029 0 0 0 0 1 1 1 6 4 5 6 8 19 Calvert 0.027 0.037 0.037 0.029 0.000 0 0 0 1 1 1 6 4 5 6 8 19 Gregory 0.027 0.037 0.037 0.029 0.000 0.000 0 0 1 1 1 6 4 5 6 8 19 Nicholson 0.027 0.037 0.037 0.029 0.000 0.000 0.000 0 1 1 1 6 4 5 6 8 19 Leichhardt 0.027 0.037 0.037 0.029 0.000 0.000 0.000 0.000 1 1 1 6 4 5 6 8 19 Flinders 0.029 0.039 0.039 0.031 0.002 0.002 0.002 0.002 0.002 0 0 5 5 4 5 9 20 Norman 0.029 0.039 0.039 0.031 0.002 0.002 0.002 0.002 0.002 0.000 0 5 5 4 5 9 20 Gilbert 0.029 0.039 0.039 0.031 0.002 0.002 0.002 0.002 0.002 0.000 0.000 5 5 4 5 9 20 Mitchell 0.039 0.033 0.033 0.039 0.012 0.012 0.012 0.012 0.012 0.010 0.010 0.010 2 1 2 13 25 Weipa 0.035 0.029 0.029 0.035 0.008 0.008 0.008 0.008 0.008 0.010 0.010 0.010 0.004 1 2 11 23 Jardine 0.037 0.031 0.031 0.037 0.010 0.010 0.010 0.010 0.010 0.008 0.008 0.008 0.002 0.002 1 12 24 Bensbach 0.039 0.033 0.033 0.039 0.012 0.012 0.012 0.012 0.012 0.010 0.01 0.010 0.004 0.004 0.002 12 25 Oriomo 0.027 0.035 0.035 0.027 0.017 0.017 0.017 0.017 0.017 0.019 0.019 0.019 0.027 0.023 0.025 0.025 19 MtBosavi 0.050 0.060 0.060 0.052 0.039 0.039 0.039 0.039 0.039 0.041 0.041 0.041 0.052 0.048 0.050 0.052 0.039
Chapter Three: Phylogenetics of wild C. quadricarinatus
34
3.4.1.3 Phylogenetic analysis of 16s sequences
All methods of phylogenetic reconstruction (NJ and ML) used here consistently
resolved four discrete C. quadricarinatus lineages. Figure 3-2 presents a
Neighbour-Joining tree of unique 16s haplotypes from Australia and PNG with
C. destructor as an outgroup. Mt Bosavi (PNG) and Oriomo (PNG) haplotypes
formed separate independent lineages and fell outside all other C.
quadricarinatus haplotypes. There was a strong relationship between
phylogenetic structuring of Australian haplotypes and their relative geographic
position. Haplotypes from rivers found in the west of northern Australia formed a
third lineage, and haplotypes from the eastern river systems in Australia formed
a fourth lineage. A striking genetic transition (over ~200km) was evident in
northern Australia between the Roper and McArthur Rivers (in the south west
Gulf of Carpentaria). Interestingly Bensbach (PNG) clustered within the eastern
Australia river lineage and most closely with haplotypes found in northern
Queensland (Weipa, Jardine and Mitchell). The tree clearly supports two
monophyletic C. quadricarinatus lineages in Australia with unique lineages
corresponding geographically to all western rivers (Ord, Roper, Howard,
Adelaide) versus all eastern rivers (McArthur, Leichhardt, Calvert, Gregory,
Nicholson, Flinders, Gilbert, Norman, Mitchell, Weipa, Jardine). The boundary
between the two clades occurs between the McArthur and Roper Rivers in south
east Northern Territory.
Four discrete haplotype networks were generated in TCS, Mt Bosavi (PNG),
Oriomo (PNG), western Australia and eastern Australia/ Bensbach (PNG).
Networks are presented in Table 3-3. Individual networks could not be joined
because divergence among haplotype networks exceeded the 95% confidence
limits derived from the parsimony estimation procedure in TCS (Templeton et
al., 1992). This relationship accords well with the topology of the phylogenetic
trees.
3.4.1.4 Isolation by distance
A significant isolation by distance relationship among 16s C. quadricarinatus
haplotypes was observed (Z = -872.8494, r = 0.6602, one-sided p <= 0.0010
from 1000 randomizations).
Chapter Three: Phylogenetics of wild C. quadricarinatus
35
3.4.1.5 16s molecular clock estimates
For the total dataset, the log likelihood ratio test rejected the hypothesis that 16s
haplotypes were evolving according to a clock like model of evolution. However,
clock like evolution could not be rejected for the eastern Australian lineage (-ln
L= -703.52 with molecular clock enforced vs. –ln L = -701.45 without the
molecular clock enforced, χ2= 4.13, d.f= 4, P> 0.10). Clock like evolution within
the western clade could not be tested, as insufficient haplotypes were available.
Using molecular clock estimates of 16s evolution for crustaceans from the
literature (0.53 – 0.96% Stillman and Reeb, 2001, Sturmbauer et al, 1996), a
2.7–3.9% sequence divergence between eastern and western Australian C.
quadricarinatus clades translates into an estimated time of divergence of 7.3
(Pliocene) - 2.8 (Pleistocene) million years before present. Divergence time
among individual populations within clades extends back to 1.88 MYA.
East 3
PNG 1
East 5
East 4
East 2
East 1
West 1
West 2
West 3
PNG 2
PNG 3
C. destructor
2286
54
44
41
30
85
5971
0.05
Figure 3-2: Neighbour joining tree for 16s sequences of C. quadricarinatus, with C. destructor as an outgroup. Tree constructed in MEGA version 2.1 employing the Tamura-Nei (1993) (0.11 gamma) model of evolution. Values at nodes represent bootstrap confidence levels (1000 replicates) if greater than 50.
Chapter Three: Phylogenetics of wild C. quadricarinatus
36
Figure 3-3: Parsimony network for C. quadricarinatus 16s haplotypes constructed in TCS. Individual networks are not joined because divergence between haplotypes exceeds the 95% confidence limits derived from the parsimony estimation procedure (Templeton et al1992). (WGC – western Gulf of Carpentaria; SGC – southern Gulf of Carpentaria; Mt B – Mt Bosavi)
3.4.2 Analysis of COI haplotype diversity
Sequence analysis of 48 C. quadricarinatus individuals for a 524bp region of the
COI gene revealed 46 variable nucleotide positions resulting in 17 unique
haplotypes from C. quadricarinatus populations sampled from 23 major
freshwater drainages across northern Australia and PNG. Several observations
confirm that the DNA sequences generated were unlikely to be nuclear
psuedogenes of the mitochondrial 16s gene. COI sequences showed a strand
bias against guanine on the light strand (T= 33.2% C= 23.4% A= 28.0% G=
15.4%), which is characteristic of the mitochondrial genome but not the nuclear
genome (Macey et al., 1999). Furthermore, no insertions or deletions were
present, most mutations were silent and no stop codons were evident in the
amino acid sequence alignment.
East 5 East 4
East 2
East 3
PNG 1
East 1
PNG 2 PNG 3
West 2
West 1 West 3
Chapter Three: Phylogenetics of wild C. quadricarinatus
37
Table 3-4: Informative sites among C. quadricarinatus COI haplotypes. 49 variable nucleotide positions among river haplotypes of a 524bp of C. quadricarinatus COI mtDNA as determined by sequencing. Dots indicate homology to the Ord River haplotype. River haplotypes have been segregated and named according to geographic origin - West, East and PNG.
Base pair position of variable site (total 524bp) Haplotype Drainage
13 3 2
3 3
4 3
4 9
58
64
94
124
148
181
190
205
206
214
217
229
239
243
244
274
289
292
293
2 9 8
3 0 2
3 1 2
319
337
361
385
409
412
415
427
430
431
449
460
471
491
496
499
501
502
504
506
517
520
West1 Ord G G A T G C C C C C C C A T C T G A C T C T T C A G C C C T A G G T C C C C A C C G A C T A C T A
West2 Howard . . . . . . . . . . . . . . . . . . . . . C . . . . . . . . . . . . T . . . . . . . G A C T A . G
West3 Adelaide . . . . . . . T . . . . . . . . . . . . . C . . . . . . . . . . . . T . . . . . . . G A C T A . G
West4 Roper . A G . . . . . . . . . . . . . . . . . . C . . . . . . . . . . . . T . . . . . . . G A C T A . G
East1 McArthur Weipa Gregory
A . . C A . . . T . . T . C T C A T . . . . C T . . . T T C G A T . . T T . . . T . G A C T A . .
East2 Calvert A . . C A . . . T . . T G C T C A T . . . . C T . . . T T C G A T . . T T . G . T . G A C T A . .
East3 Gregory A . . C A T . . T . . T . C T C A T . . T . C T . . . T T C G A T . . T . T . . T . G A C T A . .
East4 Flinders A . . C A . . . T . . T . C T C A T . C . . C T . . . T T . G A T . . . T . . . T . . A C T A . .
East5 Norman A . . C A . . . T . . T . C T C A T . . . . C T . . . T T . G A T C . . T . . . T . . A C T A . .
East6 Norman A . . C A . . . T . . T . C T C A T . . . . C T G . . T T . G A T . . . T . . . T . . A C T A . .
East7 Gilbert Norman Mitchell
A . . C A . . . T . . T . C T C A T . . . . C T . . . T T C G A T . . . T . . . T . . A C T A . .
East8 Gilbert A . . C A . . . T . . T . C T C A T . . . . C T . . . T T . G A T . . . T . . . T . G A C T A . .
East9 Mitchell A . . C A . T . T . . T . C T C A T . . . . C T . . . T T . G A T . . . T . . . T . . A C T A . .
East10 Jardine A . . C A . . . T . . T . C T . A T . . . . C T . A . T T . G A T . T . T . . . T . . A C T A . .
PNG1 Bensbach A . . C A . . . T . T T . C T C A T . . . . C T . . . T T . G A T . . . T . . . T . . A C T A . .
PNG2 Oriomo A . . C A . . . T . . T . . T C A T . . . . C T . . . T T . G A T . . . . . . . T . . A C T A . .
PNG3 MtBosavi A . . C A T . T . T . T . . T . A T . . . . C T . . . . T . . A T . . . . . . . T A . A C T A C .
Chapter Three: Phylogenetics of wild C. quadricarinatus
38
Table 3-5 details divergence estimates using the Tamura-Nei (1993) substitution
rate and a gamma value of 0.22. The greatest pairwise haplotype difference was
evident between East 2/East 3 and West1/West4 haplotypes - a net divergence
of 5.2%.
Translation of the nucleotide sequence into amino acid sequence for this coding
gene indicated that most polymorphisms were silent with a single fixed amino
acid difference observed between western and eastern Australian lineages and
two single amino acid changes in West 4 and East 10. C. quadricarinatus and C.
destructor amino acid sequences were aligned to determine a comparative level
of variability of amino acid sequences between two Cherax species. The
alignment produced 5 and 4 amino acid changes (across a total of 174 amino
acids) in eastern and western lineage sequences, respectively.
3.4.2.1 COI Neutrality Test
Both Fu and Li tests proved non-significant and therefore C. quadricarinatus COI
appears to be evolving according to a neutral model (Fu and Li's D: -0.66579: (P
> 0.10); Fu and Li's F: -0.71281: (P > 0.10)).
3.4.2.2 COI Saturation Plot
Plotting uncorrected versus corrected (Tamura Nei (1993); gamma = 0.22)
distance measures for C. quadricarinatus COI haplotypes revealed no evidence
for saturation (R2 = 0.9937; data not shown).
Chapter Three: Phylogenetics of wild C. quadricarinatus
39
Table 3-5: Relationship among sampled populations based on COI sequences; the upper matrix shows the number of base pairs different between COI haplotypes from the river indicated; the lower matrix shows the p distance between COI haplotypes from the river indicated.
West1 West2 West3 West4 East1 East2 East3 East4 East5 East6 East7 East8 East9 East10 PNG1 PNG2 PNG3 West1 8 9 10 25 27 27 23 23 23 23 23 23 23 23 20 21 West2 0.015 1 2 23 25 25 23 23 23 23 21 23 21 23 20 21 West3 0.017 0.002 3 24 26 26 24 24 24 24 22 24 22 24 21 20 West4 0.019 0.004 0.006 25 27 27 25 25 25 25 23 25 23 25 22 23 East1 0.048 0.044 0.046 0.048 2 4 4 4 4 2 2 4 6 4 5 14 East2 0.052 0.048 0.050 0.052 0.004 6 6 6 6 4 4 6 8 6 7 16 East3 0.052 0.048 0.050 0.052 0.008 0.012 8 8 8 6 6 8 10 8 7 14 East4 0.044 0.044 0.046 0.048 0.008 0.012 0.015 2 2 2 2 2 4 2 3 12 East5 0.044 0.044 0.046 0.048 0.008 0.012 0.015 0.004 2 2 2 2 4 2 3 12 East6 0.044 0.044 0.046 0.048 0.008 0.012 0.015 0.004 0.004 2 2 2 4 2 3 12 East7 0.044 0.044 0.046 0.048 0.004 0.008 0.012 0.004 0.004 0.004 2 2 4 2 3 12 East8 0.044 0.040 0.042 0.044 0.004 0.008 0.012 0.004 0.004 0.004 0.004 2 4 2 3 12 East9 0.044 0.044 0.046 0.048 0.008 0.012 0.015 0.004 0.004 0.004 0.004 0.004 4 2 3 12 East10 0.044 0.040 0.042 0.044 0.012 0.015 0.019 0.008 0.008 0.008 0.008 0.008 0.008 4 5 12 PNG1 0.044 0.044 0.046 0.048 0.008 0.012 0.015 0.004 0.004 0.004 0.004 0.004 0.004 0.008 3 12 PNG2 0.038 0.038 0.040 0.042 0.010 0.013 0.013 0.006 0.006 0.006 0.006 0.006 0.006 0.010 0.006 9 PNG3 0.040 0.040 0.038 0.044 0.027 0.031 0.027 0.023 0.023 0.023 0.023 0.023 0.023 0.023 0.023 0.017
Chapter Three: Phylogenetics of wild C. quadricarinatus
40
3.4.2.3 Phylogenetic analysis of COI
A neighbour-joining tree of all COI river haplotypes revealed four distinct lineages
(Figure 3-4) and is similar to the topology of 16s haplotypes. Populations from
western Australian rivers formed a well supported lineage, populations from eastern
Australian, Bensbach (PNG) and Oriomo (PNG) rivers formed a second lineage and
MtBosavi (PNG) formed a third lineage. Within the eastern lineage haplotypes East
1, East 2 and East 3 formed a clade encompassing the western Gulf rivers of
McArthur, Gregory, Calvert, Louie Creek, and Weipa in the north east.
East1
East2 East3
East7
East8
East4
East5
East6
East9
PNG1
East10
PNG2
PNG3
West1
West2 West3
West4 75
97
100
61
74
93
47
54
28
58
44
0.005
Figure 3-4: Neighbour joining tree of Australian COI C. quadricarinatus haplotypes. Tree constructed in MEGA using Tamura-Nei (1993) (0.22 gamma) model of evolution. Values at nodes represent bootstrap confidence levels (1000 replicates).
Chapter Three: Phylogenetics of wild C. quadricarinatus
41
Haplotype networks constructed in TCS, allow evolutionary relationships among
haplotypes to be visualised (Figure 3-5). Four networks were generated. Individual
networks could not be joined because divergence among haplotypes exceeded the
95% confidence limits derived from the parsimonious estimation procedure
(Templeton et al1992). The first network includes haplotypes from western Australia
(rivers); the second network is made up of eastern Australian rivers and includes the
Bensbach population from PNG. The third and fourth networks consist of single
haplotypes PNG 2 (Oriomo) and PNG 3 (Mt Bosavi) respectively.
Figure 3-5: Parsimony network for C. quadricarinatus COI haplotypes constructed in TCS reveals evolutionary relationships among haplotypes. Individual networks are not joined because divergence between haplotypes exceeds the 95% confidence limits derived from the parsimonious estimation procedure (Templeton et al. 1992).
East 9
East 3
East 2
East 1
East 4
East 5
East 6
East 7 East 8
PNG 1
East 10
West 1 West 2
West 3
West 4
PNG 2
PNG 3
Chapter Three: Phylogenetics of wild C. quadricarinatus
42
3.4.2.4 Isolation by distance
A significant isolation by distance relationship among COI C. quadricarinatus
haplotypes was observed (Z = -706.3913, r = 0.6300, one-sided p <= 0.0010 from
1000 randomizations).
3.4.2.5 COI molecular clock estimates
A log likelihood ratio test rejected the hypothesis that lineages were evolving
according to a clock like model of evolution. However, clock like evolution was not
rejected within each lineage (eastern: -ln L= -920.43 with molecular clock enforced
vs. –ln L –911.11 without the molecular clock enforced, χ2=18.65, d.f=11, P> 0.10;
western: -ln L= -920.41 with molecular clock enforced vs. –ln L –919.58 without the
molecular clock enforced, χ2=1.67, d.f=2, P> 0.10)
Using the molecular clock estimates for crustacean COI (1.4% per million years;
Knowlton and Weight 1998), 3.8 - 5.4% divergence between eastern and western C.
quadricarinatus lineages translates into an estimated time of divergence of 7.56-
5.32 million years before present.
Chapter Three: Phylogenetics of wild C. quadricarinatus
43
3.5 Discussion Phylogenetic analysis of 16s and COI mtDNA gene sequences from C.
quadricarinatus populations in northern Australia and southern PNG resolved two
distinct genealogical lineages in Australia and three in PNG. Both mitochondrial
genes were evolving according to neutral expectations and did not show evidence of
saturation, making them suitable for investigating evolutionary relationships among
wild C. quadricarinatus populations.
The two discrete Australian lineages accord with Reik’s (1969) description of two
morphologically distinct species that he designated C. quadricarinatus and C.
bicarinatus, described geographically from eastern and western populations,
respectively. The divergence at a single allozyme locus (Carbonic anhydrase)
detected among Australian C. quadricarinatus populations by Macaranas et al.
(1995) adds further support to their recognition as monophyletic clades. Further, an
unpublished QUT honours study reported that no successful matings were achieved
between Weipa (eastern) and Howard (western) C. quadricarinatus individuals in a
laboratory breeding trial (Ogden, 2000), suggesting that C. quadricarinatus from the
geographic extremes of the species natural distribution may not recognise each
other as potential mates. While this experiment was undertaken under artificial
conditions, it provides additional support that eastern and western C.
quadricarinatus lineages are highly divergent. These data do, however contradict
Austin’s (1996) allozyme study that found no significant difference among Australian
and PNG C. quadricarinatus populations. Austin used allozyme data to reject Reik’s
(1969) conclusions, and consequently, C. quadricarinatus, C. bicarinatus and C.
albertsii are treated as a single taxon.
The existence of two distinct lineages of C. quadricarinatus in Australia raises the
question as to whether the lineages represent two distinct biological species.
Specific status of allopatric lineages can be difficult to assess, so the evolutionary
species concept (Simpson, 1951; Wiley, 1978) has become a popular choice for
assessing whether a group of organisms is a phyletic lineage (an ancestral-
descendent sequence of interbreeding populations, evolving independently of
others, with its own separate and unitary evolutionary role and tendencies (Simpson,
1951)).
Unless the two C. quadricarinatus lineages can be found in sympatry it is difficult to
assess whether the two lineages are reproductively isolated and do not recognise
each other as potential mates under natural conditions. The amount of genetic
Chapter Three: Phylogenetics of wild C. quadricarinatus
44
divergence detected among C. quadricarinatus lineages is large and similar levels of
divergence have been documented between other Cherax populations that are
recognised as subspecies. C. destructor destructor and C. destructor albidus exhibit
4.7% sequence divergence at 16s RNA (Campbell et al., 1994), therefore a 3.9%
16s sequence difference between the Australian eastern and western lineages
suggests the current taxonomic designation should be revised. Possibly the eastern
and western lineages of C. quadricarinatus may require re-classification into
subspecies. If sequence data were the only criterion for species/subspecies
boundaries, the Mt Bosavi population should also be designated as a subspecies,
as it is up to 6% divergent from all Australian C. quadricarinatus sequences.
The three C. quadricarinatus populations sampled in PNG were all genetically
distinct lineages. PNG unlike northern Australia is very mountainous. Such immense
physical barriers (rugged mountain ranges) will almost certainly reduce dispersal
capabilities for any freshwater species. Interestingly, a close genetic relationship
was evident between one PNG C. quadricarinatus lineage (Bensbach) and the
eastern Australian lineage. While more comprehensive sampling will be required to
fully resolve C. quadricarinatus phylogeography in PNG, the close genetic
relationship of a PNG C. quadricarinatus population and northern Australia C.
quadricarinatus provides evidence for a recent freshwater connection between
northern Australia and PNG. The most recent land bridge between northern
Australia and PNG was present until 8500 years ago (Torgersen et al., 1985; Chivas
et al., 2001). During times of lowered sea level, Australia and southern PNG were a
single landmass with terrestrial and freshwater organisms theoretically then able to
disperse among the two areas over land and via freshwater connections (Figure 3-
1). Relationships among sequences as shown by the haplotype networks (Figure
3-3 and Figure 3-5) suggest that the most recent ancestor, if still extant, was not
sampled (by chance) in the current study.
When all Australian C. quadricarinatus sampled populations were considered
together there was a positive correlation between geographical distance and genetic
distance, suggesting an ‘isolation by distance’ effect. This was largely due to the
significant divergence between eastern and western lineages across the natural
distribution of C. quadricarinatus in Australia. However, if populations within eastern
and western regions are considered separately, no correlation with geographic
distance was evident. If contemporary gene flow occurs between populations of the
two lineages, eastern and western haplotypes should be found in the same
geographic area. However, the probability of detecting haplotypes of both lineages
Chapter Three: Phylogenetics of wild C. quadricarinatus
45
within a site was low given the small sample sizes examined here (n=2). A contact
or hybrid zone could potentially exist somewhere within the 200km transition zone
between the Roper and McArthur Rivers. Unfortunately, while sites were sought in
this area (Limmen Bight catchment) no C. quadricarinatus populations were found
there.
Clock like evolution for C. quadricarinatus sequences was evident in the current
study, although log likelihood tests rejected the hypothesis of clock like evolution for
16s and COI data sets when all populations were considered together. Clock like
evolution was confirmed however within eastern and western lineages respectively.
This indicates that while populations within each lineage are evolving in a clock like
fashion, independent lineages have not been evolving in unison. Dates for time to
common ancestor hypothesised for C. quadricarinatus are estimates calibrated for
marine decapods (16s - porcelain crabs; 0.53%/MY, Stillman and Reeb, 2001 and
fiddler crabs; 0.96%/MY, Sturmbauer et al., 1996 and COI - 1.4%MY; Knowlton and
Weight, 1998) and should be interpreted as indicating only a range of time during
which the evolutionary events may have occurred. Divergence of Australian C.
quadricarinatus lineages using 16s sequence data suggest this occurred 2.8 – 7.3
million years ago, while COI sequence estimates suggest coalescence of eastern
and western lineages between 5.32 – 7.56 million years ago. This dates back to the
Tertiary (late Miocene, 23.8 – 5.3 MYA; Pliocene, 5.3 – 1.8MYA). 16s data
estimates divergence within eastern and western lineages up to 1.88MYA,
corresponding to the beginning of the Pleistocene, an epoch characterised by four
major glacial advances and significant eustatic events in northern Australia.
Substantial geomorphological events such as the rapid uplift of PNG’s central
mountain range (Dow, 1977; Pigram & Davies, 1987), and dramatic climate
oscillations (Axelrod and Raven, 1982) occurred during the Tertiary and Quaternary
periods (Dow, 1977; Hill & Gleadow, 1989). The uplift of PNG’s cordillera has been
episodic rather than a gradual continuous event, with an initial major burst of uplift at
5.8–5.3 MYA and less intense episodes of folding and thrusting spanning the period
5.3–4.7 MYA. The degree of sequence divergence detected between Australian and
PNG C. quadricarinatus conspecifics is compatible with the timing of these tectonic
events and so they provide a potential causative agent for distinct C. quadricarinatus
lineages evolving in PNG.
Chapter Three: Phylogenetics of wild C. quadricarinatus
46
3.5.1 Reconstruction of the evolution of modern C. quadricarinatus lineages
Two alternative scenarios can be hypothesised to explain the presence of two C.
quadricarinatus lineages in Australia. Firstly, following evolution of C.
quadricarinatus in northern Australia, alteration of ancient river drainage watersheds
and eustatic changes resulted in geographical barriers that restricted gene flow
between eastern and western populations. Subsequently, C. quadricarinatus
populations evolved independently and diverged under the influences of genetic
drift, selection, probable colonisation/founder events and population expansion
events post separation. In support of this theory, Macaranas et al. (1995) proposed
that strong selection pressure related to water pH may have influenced the genetic
structure C. quadricarinatus across northern Australia. Basalt soils in eastern
northern Australia produce acidic waters, and ancient coral reef, that are now
exposed limestone escarpments have produced alkaline waters in western northern
Australia. Following isolation, this major environmental difference could have
influenced the evolution of two geographically adapted gene pools corresponding to
the modern eastern and western C. quadricarinatus lineages.
A second scenario is that C. quadricarinatus evolved in PNG and two independent
colonisation events of divergent C. quadricarinatus lineages from PNG occurred at
times of lowered sea levels when northern Australia was connected to PNG via a
land bridge. Divergent lineages of C. quadricarinatus in PNG resulted from
substantial geomorphological events such as the rapid uplift of PNG’s central
mountain range (Dow, 1977; Pigram and Davies, 1987). In addition, dramatic
climatic oscillations (Axelrod & Raven, 1982) during the Tertiary and Quaternary
makes it highly likely that populations of C. quadricarinatus may have become
isolated and restricted to discrete habitat refugia by these events, allowing divergent
lineages to evolve in New Guinea. Later, during times of lowered sea levels with
freshwater rivers coalescing, C. quadricarinatus may have colonised Australia via
two routes: one route west into Arnhem Land across the Arafura Sill and the other
route from PNG south along the Cape York peninsular, into gulf rivers. Colonisations
would have been followed by range expansions into their current distributions.
Subsequent rises in sea level later severed connections between PNG and
Australian rivers.
The division between eastern and western lineages in Australia occurs over a
relatively small geographic distance (a distance of less than 200km of coastline
between the river mouths of the Roper and McArthur Rivers) in the south west
corner of the Gulf of Carpentaria. The two evolutionary lineages found in Australia
Chapter Three: Phylogenetics of wild C. quadricarinatus
47
continue to evolve independently perhaps due to extrinsic factors such as
environmental adaptation (eg. influence of different water chemistry), or perhaps
intrinsic factors such as behavioural differences (eg. different mate recognition cues,
Paterson, 1985).
A close genetic relationship between C. quadricarinatus from northern Australian
and populations in PNG has been observed in other terrestrial (green python,
Morelia viridis, Rawlings & Donnellan, 2003) and aquatic species (rainbow fish,
McGuigan et al., 2000; prawns,de Bruyn et al., 2004). A hypothesis for two
independent colonisations of Melanotaeniid rainbow fish into Australia from PNG
was based on monophyletic relationships among Australian and southern New
Guinea rainbow fish (McGuigan et al. 2000). McGuigan et al. (2000) suggested
contemporary distributions of Melanotaeniid rainbow fish clades reflect episodic
connections via the ancient freshwater Lake Carpentaria during periods of low sea
level when routes for dispersal from PNG to northern Australia were present.
Patterns of genetic structuring of C. quadricarinatus populations concur with that of
another decapod crustacean Macrobrachium rosenbergii that share a similar
distribution in Australia and PNG (de Bruyn et al, 2004). Studies by de Bruyn et al.
(2004) have revealed distinct lineages in PNG, eastern and western Australia, as
well a PNG clade that has a close genetic relationship with an eastern Australian
clade. de Bruyn et al. (2004) also concluded that the intermittent existence of Lake
Carpentaria in the past may have facilitated dispersal of M. rosenbergii among Gulf
of Carpentaria rivers. Lake Carpentaria could have also facilitated dispersal by C.
quadricarinatus, however, since the salinity levels of Lake Carpentaria remain
unknown, and because ancient river systems have been hypothesised to historically
connect some gulf rivers (Voris, 2000), such an inference cannot be made here.
Across C. quadricarinatus’ natural distribution, ancient watercourses are once likely
to have linked populations that are now disjunct. However, geomorphological events
during the Tertiary, coupled with sea level changes during the Pleistocene, have
resulted in modern C. quadricarinatus populations that show significant populations
today.
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
49
4.0 The Extent of Contemporary Gene Flow among Wild Australian C. quadricarinatus Populations
4.1 Introduction
Spatial, physical, temporal and/or biological limitations on gene flow can promote
genetic subdivision among populations of a species (Paetaku et al., 1998; Prodohl et
al., 1998; Luikart et al., 1999; Balloux & Lugon-Moulin, 2002; Costello, 2003). Natural
distributions that exceed the normal dispersal or migrational capacity of individuals can
contribute to spatial patterns of genetic heterogeneity (and even lead to speciation)
(Waters et al., 2001b). The island model (Wright, 1931) is a geographical null
hypothesis of population structure, in which dispersal is unbiased with respect to
distance between habitat islands, but is unlikely to be relevant for freshwater species
with extensive distributions that extend across discrete drainages. A stepping-stone
model (Kimura, 1953) therefore, may better approximate dispersal of most freshwater
species. Stepping-stone dispersal occurs between neighbouring populations where long
distance dispersal is assumed to be rare. Unlike the island model, stepping-stone
dispersal is a correlation of gene frequencies that decreases as the number of steps
between populations increases (Kimura & Weiss, 1964). A similar decline is expected
under an isolation by distance model among continuously distributed populations.
Consequently, gene flow among populations is expected to decline with geographic
distance under stepping-stone dispersal or isolation by distance models of dispersal,
but not under the island model.
Problems with the utility of the above genetic models to explain likely patterns of genetic
variation in freshwater systems led Meffe and Vrijenhoek (1988) to propose the Stream
Hierarchy Model (SHM) as a means for summarising the relationships among
freshwater populations within and among drainages. Due to the complex hierarchical
branching patterns of most riverine drainages, the SHM proposes that the probability of
connectivity among populations was related to the position of a population in a
particular drainage, such that populations within the same stream are likely to be
genetically more similar than populations in different subcatchments and so on
hierarchically, with most differentiation occurring among discrete drainages.
C. quadricarinatus have a simple lifecycle that is completed in freshwater, although
juveniles can tolerate salinities up to 20ppt (brackish) (Jones, 1995) for short periods of
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
50
time. Being devoid of a free-swimming larval stage, C. quadricarinatus are not expected
to disperse widely as juveniles, compared with some marine crayfish, where larvae are
known to travel great distances via ocean currents (Ward et al., 1994). Local C.
quadricarinatus populations may sometimes even go extinct in drought years with some
ephemeral habitats recolonised from more permanent populations. Depending on the
pattern of recolonisation, genetic diversity could as a consequence decline rapidly
within and among wild populations. If local extinction and recolonisation (bottleneck)
events are frequent, the populations will tend to coalesce rapidly. Genetic drift
combined with local selection effects, in contrast, are likely to increase the extent of
genetic differentiation among isolated populations.
Most natural drainage systems inhabited by C. quadricarinatus in northern Australia are
subject to seasonal flooding, thus dispersal of C. quadricarinatus between neighbouring
rivers may be possible where topography is low. Grimes and Kingford (1996) have also
documented freshwater fish larvae dispersing between discrete drainages when flood
plumes from rivers provide freshwater or low salinity water connections between river
mouths. Salinity is known to reduce significantly in coastal areas in the Gulf of
Carpentaria following extensive rainfall during the wet season (Wolanski, 1993). C.
quadricarinatus may also be capable of limited terrestrial dispersal across drainage
boundaries during humid conditions. Terrestrial dispersal has been documented in
Cherax destructor (Hughes & Hillyer, 2003), where topography between catchments
was minimal and the occurrence of flooding across drainage boundaries was low.
Although individual dispersal capabilities of C. quadricarinatus are essentially unknown,
evidence from other closely related Cherax species suggests that dispersal among
drainages might be possible, at least at small geographic scales.
Mitochondrial DNA analysis of C. quadricarinatus populations identified two divergent
phylogenetic lineages in northern Australia indicating that gene flow between western
and eastern regions has been disrupted in the past for a significant period of
evolutionary time. However, within the two lineages, some haplotypes were shared
among geographically close drainage systems. Across C. quadricarinatus’ natural
distribution, ancient watercourses are once likely to have connected some populations,
however a rise in sea level to its modern day level has severed these historical
freshwater connections.
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
51
This chapter investigates whether gene flow is occurring among contemporary C.
quadricarinatus populations in northern Australia. To assess if present day genetic
structuring of C. quadricarinatus is due to historical events, or if contemporary gene flow
has played a role in shaping genetic patterns, microsatellite markers were developed.
Microsatellites have proven useful for detecting variation in species that exhibit little
allozyme variation (Hughes & Queller, 1993), are co-dominant and are assumed to be
selectively neutral (Bowcock et al., 1994). The specific objectives of this study were to
(1) examine the levels and patterns of microsatellite variation in wild populations of C.
quadricarinatus in Australia; and (2) given the existence of discrete western and eastern
mtDNA lineages, to determine the extent of contemporary gene flow within and among
wild Australian C. quadricarinatus lineages using nuclear markers.
4.2 Microsatellite Methods
4.2.1 Sample sites
Fourteen populations were used in the microsatellite analysis (Table 4-1). Some
populations used in the mtDNA study were excluded due to small sample sizes (Louie
Creek (n=2), Lockerbie (n=6), Bensbach (n=4), Oriomo (n=6) and MtBosavi (n=4)).
Table 4-1: Site Location, river drainage, abbreviation, sample size of C. quadricarinatus populations used for microsatellite analysis
Site Location Drainage Abbrev. n Kununurra Dam, WA Ord Ord 22 Howard River, NT Howard How 30 Adelaide River, NT Adelaide Ade 24 Roper River, NT Roper Rop 11 McArthur River, NT McArthur McA 22 Calvert River, NT Calvert Cal 22 Gregory River, QLD Gregory Gre 33 Flinders River, QLD Flinders Fli 32 Norman River, QLD Norman Nor 32 Gilbert River, QLD Gilbert Gil 34 Elizabeth River, QLD Gilbert Eli 18 Mitchell River, QLD Mitchell Mit 34 Chillagoe River, QLD Mitchell Chi 32 Weipa, QLD Mission Wei 30
4.2.2 DNA Extraction
Approximately 100mg of abdominal muscle or pleopod tissue was soaked in GTE buffer
for at least 30mins to remove excess ethanol, tissue samples were then placed in 500μl
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
52
of 2x CTAB3 buffer (1M Tris HCl, 4M NaCl, 0.5M EDTA, 0.5M CTAB, 0.5M 2-
mercaptoethanal) with 15μl of Proteinase K (20mg/ml), and samples incubated in a
water bath at 55oC overnight. Following digestion, 500μl of chloroform:iso-amyl alcohol
(24:1) was added to each tube and mixed thoroughly by gentle inversion of the tube
and this mixture centrifuged at 13 000rpm for 15mins. The aqueous layer was then
removed and samples transferred to a clean tube and the extraction repeated with
phenol:chloroform:iso-amyl alcohol (25:24:1), followed by chloroform:iso-amyl alcohol
(24:1). Precipitation of genomic DNA was carried out using 1ml of cold (-20) 100% iso-
propanol and samples incubated at -20 for one hour. DNA was then centrifuged at 13
000rpm for 15 min, the alcohol decanted and the pellet resuspended in cold (-20) 70%
ethanol. The DNA was again centrifuged at 13 000rpm for a further 5 min. The ethanol
was then decanted and the pellet left to dry at room temperature for 5-10 min. The
pellet was then dissolved in 100-200μl of 1x TE (0.001M Tris-HCL pH7.5, 0.0001M
EDTA4). DNA was electrophoresed through a 1% TBE (1M Tris/.83M Boric Acid/ 10mM
EDTA) agarose gel and visualised under ethidium bromide. Genomic DNA
concentration in each sample was determined using a GeneQuant (RNA/DNA
Calculator, The Australian Chromatography Company). DNA was diluted with distilled
water to approximately 100ng/μl for PCR and stored at –20oC when not in use.
4.2.3 Microsatellite Isolation and Characterisation
The genomic library used to develop C. quadricarinatus microsatellite loci was
developed from a C. quadricarinatus individual collected from the Flinders River
(eastern lineage). Procedures for the construction and screening of the genomic library
are outlined in Baker et al. (2000) (see Appendix 1). Table 4.2 characterises the C.
quadricarinatus microsatellite loci developed for this study.
3 Hexadecyltrimethylammonium Bromide 4 Ethylenediaminetetraacetic acid
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
53
Table 4-2: Locus name, primer sequences (5’ to 3’ direction), repeat type and size, and PCR conditions for microsatellite loci used in this study.
In the early stages of screening it became evident that western C. quadricarinatus
populations would not amplify with all C. quadricarinatus primer sets developed from an
‘eastern’ lineage individual. After extensive experimental manipulation that involved
changing PCR conditions and redesigning primers, western C. quadricarinatus
populations would amplify with only three of the 12 primer sets developed. While
Koskinen (2004) suggested that 30 microsatellite loci are needed for a comprehensive
population genetic analysis, a much lower number of loci can still be informative and
are used commonly for similar studies in the literature. Five loci were chosen based on
their repeatability and gel separation (clarity of alleles/ stutter bands) and were used to
screen variation in eastern C. quadricarinatus populations, see Table 4.3.
Table 4-3: Locus name, repeat type/size, annealing temperature, magnesium chloride concentration and amplification success of C. quadricarinatus microsatellite loci used in this study.
4.2.4 Radioisotope Analysis of C. quadricarinatus Microsatellites
Microsatellite loci were amplified in 0.5μl Eppendorf tubes using: 50ng of genomic DNA,
1.5x Tth reaction buffer (Pharmacia), 2mM dNTPs (dCTP labelled with 32P), 2/3mM
MgCl2, 16pmol of each primer 0.02U Tth polymerase (Pharmacia); and ddH20 to a
Primer Name Primer Sequence Repeat Size (bp) TA (oC) MgCl2 (mM)
CQU.001-FOR GCA TCA TCT GCA AAC AAG GAT AC (CA)11~(CA)18 178 55 3 CQU.001-REV GTG ACG GGA CCA AGA ATA TGA AG CQU.002-FOR TGT CAG TGT ATG CGG TAG CCA CG (CA)27 179 50 2 CQU.002-REV TGC CGT TCT TCC ATA ACC TCA GG CQU.003-FOR GGG AGA GGG TGG ATT TAC TAC CG (CA)29 219 50 2 CQU.003-REV CCA TGA GAA ATG CTC TGA GAC TCG CQU.004-FOR AAG CCG ACC ATA AA GAA ATC AG (CA)32 218 50 3 CQU.004-REV TTT GCA CTT GGT GGG ATT GAA C CQU.006-FOR AAC TGC CAC CAA ATA CTG CAA GC (CT)11 164 55 3 CQU.006-REV TTG CTC GGG ACA CCT TAC TAG ACG
Amplified Locus Eastern Western
CQU.001 Yes No CQU.002 Yes No CQU.003 Yes Yes CQU.004 Yes Yes CQU.006 Yes Yes
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
54
volume of 20μl, using the following cycles: 1 min at 94oC, 1min at TA (see Table 2.3)
and 2min at 72oC, for 33 cycles with a 10 min extension at 72oC
Following amplification, 40μl of 95% formamide, 50mM EDTA dye was added to each
sample and the products denatured at 94oC for 3 min and then placed immediately on
ice. 1μl of PCR product was then electrophoresed at 70 watts through a 5% denaturing
polyacrylamide sequencing gel. Gels were dried for 45min at 80oC and visualised using
autoradiography. Reference individuals possessing unique alleles, were included on
each gel run. Individuals were genotyped in comparison to these reference alleles.
Allele frequencies were tabulated for each population.
During the screening process for allelic diversity at C. quadricarinatus microsatellite loci,
a GelScan 2000 (Corbett Research) which is an integrated electrophoretic and
computerised system using a laser to detect fluorescently labelled PCR products was
purchased by the SNRS Genetics Laboratory. Reverse primers were fluorescently hex-
labelled and electrophoretic running conditions re-optimised for GelScan microsatellite
analysis.
4.2.5 Fluorescent Analysis of C. quadricarinatus Microsatellites
Microsatellite loci were amplified in 96-well plates using the following conditions: 50ng
of genomic DNA, 1.5x Tth reaction buffer (Pharmacia), 2/3mM dNTPs 3mM MgCl2,
10pmol of each primer (reverse primer hex-labelled), 0.02U Tth polymerase
(Pharmacia); and ddH20 to a volume of 12μl. PCR reactions were cycled using the
optimised annealing temperature in an Eppendorf Mastercycler PCR machine using the
following conditions: one extended denaturation at 94oC for 2 min, then 40 sec at 94oC,
40 sec at TA (see Table 2-3) and 1 min at 72oC, for 29 cycles with a 10 min extension at
72oC.
Following amplification, 12μl of 95% formamide, 50mM EDTA dye were added to each
sample and the products denatured at 94oC for 3 min and samples placed immediately
on ice. Samples were electrophoresed through a 5% acrylamide gel at 1200volts using
a GelScan 2000 (Corbett Research). A 350bp size ladder (Genetix) combined with C.
quadricarinatus alleles of known size were run at either end and in the middle of the
unknown samples on each gel. Representative alleles scored using P32 methods were
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
55
re-amplified and run on the GelScan to confirm reproducibility and to assign a repeat
size.
Within each plate two tubes were left empty to allow control (reference) samples to be
loaded. Because alleles at dinucleotide loci differ by as little 2bp, a misalignment with
size markers, or ‘frowns’ in gel running conditions can easily lead to scoring errors, so
controls (known genotypes) were used routinely on all gels.
Gel images were analysed using OneDScan (Scanalytics). To reduce error during
genotyping using OneDScan software (Scanalytics), gel images were double-checked.
The digital gel images were scored twice, on different occasions, to ensure accurate
genotype data.
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
56
4.2.6 Statistical Analysis
4.2.6.1 Linkage disequilibrium Exact P-tests for detecting linkage disequilibrium were used to test the independence of
microsatellite loci using a Markov chain approach, as performed in GENEPOP ver. 3.1
(Raymond & Rousset, 1995). A Bonferonni approach (Rice, 1989) was used to correct
for multiple simultaneous tests.
4.2.6.2 Tests for Hardy-Weinberg Equilibrium (HWE)
Observed genotypic frequencies were compared with those expected under Hardy-
Weinberg equilibrium using exact tests (Louis and Dempster 1987) using a Markov
chain method (Guo and Thompson 1992) for loci with five or more alleles. Tests were
performed in GENEPOP ver. 3.1 (Raymond and Rousset, 1995). The Bonferonni
correction (Rice 1989) was used to correct for multiple simultaneous tests.
4.2.6.3 Molecular diversity
Common indices of genetic variation including: number of alleles per locus, number of
effective alleles and mean heterozygosity (HO and HE) and fixation indices were
estimated for each locus using GenAlEx Ver 1.5 (Peakall & Smouse, 2001). A fixation
index value (F) close to zero is expected under random mating. Positive values indicate
inbreeding (or null alleles), while negative values indicate an excess of heterozygotes,
due to assortative mating or selection acting at the locus.
4.2.6.4 Null allele analysis The relatively large number of alleles that microsatellite loci commonly reveal will
inherently cause departures from HW if sample sizes are low. Null alleles that are not
amplified create an apparent heterozygote deficit because they produce pseudo-
homozygotes (Brookfield, 1996). If a null allele has a frequency of p, the mean number
of individuals that have to be sampled in order to observe one homozygote is E(n)=1/p2.
Brookfield (1996) described a method for estimating the frequency of null alleles, r, from
the deficiency of heterozygotes that they induce. The expected frequency of
heterozygotes, from HWE formula is:
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
57
Σpi.pj= Σpi
.pj/(1-r)2=He
Thus, D=(He-Ho)/He=2r/(1+r)
Thus, r=D/(2-D)
4.2.6.5 Population differentiation
Most microsatellite alleles are believed to evolve by the addition or deletion of single
repeats, and less frequently by mutations involving two or more repeats (Weber &
Wong, 1993; DiRienzo et al., 1994; Primmer & Ellegren, 1998). Understanding the
mutation model underlying microsatellite evolution is crucial for the development of
statistics to accurately define population genetic structures. Two general models have
been proposed to account for variation at a genetic locus, the infinite allele’s model
(IAM, (Kimura & Crow, 1964)) and the stepwise mutation model (SMM, (Kimura & Otha,
1978)).
FST is a decreasing function of N(m + u), the product of local population size and the
sum of migration and mutation. FST becomes a simple function of the number of
migrants when mutation is negligible, although this is often not the case for
microsatellites. An additional difficulty arises when the mutation model cannot be
assumed to an IAM. Under mutation models generating homoplasy, such as SMM, the
relationship between FST and the number of migrants may no longer hold (Rousset,
1996). Slatkin (1995) proposed RST as an analogue to FST for microsatellite loci
assuming a stepwise mutation model. Recently however, questions have been raised
about the reliability of RST (Balloux & Goudet, 2002). The drawback with RST is its high
variance, even under the strictest SMM, FST estimates therefore may outperform their
RST counterparts (Gaggiotti et al., 1999). Given that the mutation model for C.
quadricarinatus microsatellite loci is unknown, the conservative method for estimating
extent of population differentiation (FST) was implemented. FST was calculated (Weir &
Cockerham, 1984) and tested for significance using 1000 random permutations in
GenAlEx ver 5.1 (Peakall and Smouse, 2001).
4.2.6.6 Genetic distance FST, a pairwise comparison between populations, only takes into account data from two
populations, not all populations simultaneously. This can be done with genetic distance
measures of which there are two types; (i) without biological assumptions or models
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
58
known as geometric distances, and (ii) with biological models taking into account
mutation and drift, but assuming no selection.
Genetic divergence among populations was first quantified using Cavalli-Sforza and
Edwards’ (1967) chord distance (DCE), which makes no assumptions about constant
population size or relative mutation rates among loci. Takezaki and Nei (1996)
evaluated DCE in simulations of tree-building algorithms for microsatellite loci and
concluded that this distance measure usually performed well. DCE is thus re-emerging
as the preferred algorithm for microsatellite analyses as it makes no assumptions about
mode of microsatellite mutation. Cavalli-Sforza’s DCE (Cavalli-Sforza and Edwards1967)
was calculated uisng GENDIST from gene frequencies in PHYLIP ver 3.57
(Felsenstein, 1995).
4.2.6.7 Isolation by distance measures
Isolation by distance refers to the increase in genetic differentiation among sites with
increasing geographic distance, under restricted levels of gene flow (Wright, 1943). At
equilibrium, gene flow and genetic drift, and hence the level of genetic differentiation
should be inversely correlated with distance among populations.
Isolation by distance was estimated using IBD Ver 1.5 (Bohonak, 2002). Chord distance
estimates were correlated with coastline geographic distance between river mouths
using matrix correlation methods of the Mantel test in the IBD Ver 1.5 program.
Because C. quadricarinatus populations are distributed in two dimensions rather than
along linear habitat features, I used log-transformed genetic and geographic distances
were used here as advocated by Rousset (1997).
Hutchison and Templeton (1999) suggested a graphical technique for determining the
influence of gene flow and drift on genetic variability. Traditional attempts to relate
estimates of regional FST to gene flow and drift via Wright’s (1931) equation FST
(1/(4Nm+1)) are often inappropriate because most natural populations may not have
reached equilibrium. Hutchison and Templeton’s (1999) graphical representation of
theoretical relationships between genetic (FST) and geographical distance describes
four possible outcomes resulting from the evolutionary dynamics that may have affected
populations historically. These include 1) equilibrium between gene flow and drift; 2)
gene flow more influential than drift; 3) drift more influential than gene flow; and 4) gene
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
59
flow and drift influence population structure differently depending on scale. A
scatterplot of the pairwise genetic and geographic distances among populations
sampled here was produced in Excel and the resulting graph compared to hypothetical
graphs in Hutchison and Templeton (1999) to infer the relative influences that gene flow
and drift could have had on the distribution of genetic variability in wild C.
quadricarinatus populations.
4.2.6.8 AMOVA analysis of molecular variance
The hierarchical population genetic structure of wild C. quadricarinatus stocks were
examined using analysis of molecular variance and the results tested for significance
using 1000 random permutations in GenAlEx (Peakall & Smouse, 2001). The AMOVA
analysis procedure follows the methods of Excoffier et al(1992).
4.2.6.9 Detection of recent population bottlenecks
Populations that have experienced a recent reduction in effective population size
(bottleneck) exhibit a correlated reduction in allele number (k) and gene diversity (HE) at
polymorphic loci. But allele number will reduce faster than gene diversity. Thus in
recently bottlenecked populations, observed gene diversity will be higher than the
expected equilibrium gene diversity (Heq) which is computed from the observed
number of alleles (k), under the assumption of constant-size (equilibrium) populations
(Luikart et al., 1998).
Gene diversity excesses (HE >Heq) have only been demonstrated for loci evolving
under an infinite allele model (IAM) (Maruyama & Fuerst, 1985). If the locus evolves
under a strict stepwise mutation model (SMM), there can be situations where gene
diversity excess is not observed (Cornuet & Luikart, 1996). Few loci however, follow a
strict SMM, and as soon as they depart slightly from this mutation model towards IAM,
they will exhibit a gene diversity excess as a consequence of any past genetic
bottleneck. Because few microsatellite loci follow a strict (one-step) SMM, a two-phase
model of mutation (TPM) is considered more appropriate. The TPM is intermediate to
the SMM and IAM (Luikart, 1998).
A second method to test for recent population bottlenecks implements a qualitative
descriptor of allele frequency distributions (‘mode-shift’ Indicator) that can discriminate
bottlenecked populations from stable populations. In a population at mutation-drift
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
60
equilibrium (the effective size of which has remained constant in the recent past), there
is approximately an equal probability that a locus will show a gene diversity excess or a
gene diversity deficit.
A Wilcoxon’s signed rank test was implemented to test for excess heterozygosity
developed by Cornuet & Luikart (1996): Simulation of Heq distributions assumed the
two-phase mutation model (TPM). The second method is a graphical representation of
the mode-shift indicator originally proposed by Luikart et al. (1998). Loss of rare alleles
in bottlenecked populations is detected when one or more of the common allele classes
have a higher number of alleles than the rare allele class (Luikart et al. 1998).
Bottleneck events were tested using both methods discussed above and were
conducted using ‘BOTTLENECK’ version 1.2.02 (Piry & Luikart, 1999).
4.2.6.10 Shannon-Weaver Index of genetic diversity Genetic diversity within a population may be lost via four related processes: founder
effect, demographic population bottlenecks, genetic drift, or inbreeding. Loss of genetic
diversity is believed to have implications for population persistence over various
temporal scales (Crozier, 1992). In the short term (e.g. generations), inbreeding
resulting from small population size may cause inbreeding depression with
corresponding reductions in mean population fitness. In the long term (hundreds or
thousands of years), reduced genetic diversity within a population may lower
evolutionary potential (ability to adapt to future environmental circumstances) or
decrease the probability of future speciation events. Shannon's Information index
provides a numerical value for relative estimate of genetic diversity with high values
representing greater amounts of genetic diversity (Peakall and Smouse, 2001). Unlike
HE, this information index value is not bounded by 1 and may therefore be a better
measure of allelic and genetic diversity. Estimates of genetic diversity are based on
frequencies of genotypic variants and can be used to assess diversity occurring not
only within populations, but also within different geographical regions or different
germplasm collections.
The Shannon-Weaver Index (Shannon & Weaver, 1949) formula is: I = - Σpi lnpi
Where ln=the natural logarithm and pi is the frequency of the ith allele.
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
61
4.3 Results In contrast to eastern populations that were screened at five loci, the four western
populations of C. quadricarinatus, (Ord, Adelaide, Howard and Roper) could only be
screened for diversity at three microsatellite loci designed specifically for C.
quadricarinatus. Failure to amplify entire populations with species-specific
microsatellite primers has not been reported previously in the literature. Due to the
different number of loci examined for western populations (3 loci) versus eastern
populations (5 loci), microsatellite analyses were segregated and the two data sets
treated separately. Also, although the sample size collected from the Gregory River
was relatively large (n=33), low numbers of individuals amplified at most loci,
especially CQU006 where only two individuals amplified. The Gregory population
was therefore excluded from analyses as small sample sizes can bias results (eg
genetic distance).
4.3.1 Microsatellite analyses of Eastern Populations
4.3.1.1 Linkage Disequilibrium
Permutation tests indicated that no significant linkage disequilibrium was evident in
eastern populations. This confirms that results from different loci are independent
markers of underlying genetic variation in the sampled populations.
4.3.1.2 Hardy Weinberg Departures
After Bonferroni correction 18 of the 45 tests were found to have significant p-values
at the 0.001 level (Appendix 3). Populations that deviated from HWE included:
CQU001: Chillagoe, Mitchell; CQU002: Norman, Mitchell, Weipa and McArthur;
CQU003: Gilbert, Mitchell and Calvert; CQU004: Norman, Elizabeth, Gilbert,
Chillagoe, Mitchell and Calvert; CQU006: Norman, Chillagoe, and Mitchell. Mitchell
was the only site that showed consistently significant values at all five microsatellite
loci, while six of the eastern populations did not conform at locus CQU004.
4.3.2 Molecular Diversity
Common indices for eastern C. quadricarinatus populations computed in GenAlex
are presented in Table 4-4. Actual population sizes range from 18 (Elizabeth) to 34
(Mitchell) however, sample sizes (n) varied as amplification success varied at each
locus. Observed heterozygosity in eastern populations ranged from 0.00 – 0.94 and
was usually lower than expected heterozygosity (Table 4.4). Most loci exhibit lower
estimates of observed heterozygosity compared to expected heterozygosity. This
suggests that factors like selection, inbreeding or null alleles were influencing C.
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
62
quadricarinatus microsatellite diversity in eastern populations. The majority of
fixation values (F) were strongly positive suggesting possible inbreeding, selection
or undetected alleles. A few populations exhibited negative fixation values, indicative
of an excess of heterozygosity under HW equilibrium.
4.3.3 Null Alleles
Proportions of null alleles of up to 79% (locus CQU002; Elizabeth population) were
detected, as shown in Table 4-4. This high number of null alleles detected in some
populations is likely to explain the relatively high level of HWE deviations observed
here.
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
63
Table 4-4: Common indices for eastern C. quadricarinatus populations; sample size (N), number of alleles (Na), number of effective alleles (Ne), observed heterozygosity (HO), expected heterozygosity (HE), and Fixation Index (F) and Brookfield’s (1996) estimate of null allele proportions (r). Values in bold indicate upper values for each locus. N/A-monomorphic at that locus.
N Na Ne HO HE F r CQU001 Flinders 31 2 1.290 0.258 0.225 -0.148 -0.069 Norman 32 6 2.955 0.563 0.662 0.150 0.081 Elizabeth 18 2 1.528 0.333 0.346 0.036 0.018 Gilbert 33 5 1.424 0.212 0.298 0.288 0.168 Chillagoe 32 4 2.528 0.281 0.604 0.535 0.365 Mitchell 34 7 4.718 0.441 0.788 0.440 0.282 Weipa 30 3 1.835 0.533 0.455 -0.172 -0.079 Calvert 22 5 3.163 0.591 0.684 0.136 0.073 Gregory 21 9 6.682 0.714 0.850 0.160 0.087 McArthur 8 6 3.765 0.625 0.734 0.149 0.080 CQU002 Flinders 31 1 1.000 0.000 0.000 N/A N/A Norman 32 6 4.312 0.813 0.768 -0.058 -0.028 Elizabeth 18 3 1.982 0.056 0.495 0.888 0.798 Gilbert 34 8 4.827 0.765 0.793 0.035 0.018 Chillagoe 32 8 4.055 0.750 0.753 0.005 0.002 Mitchell 32 9 3.779 0.469 0.735 0.363 0.221 Weipa 27 4 1.997 0.222 0.499 0.555 0.384 Calvert 21 6 2.706 0.524 0.630 0.169 0.092 Gregory 20 7 4.444 0.650 0.775 0.161 0.088 McArthur 13 7 5.930 0.615 0.831 0.260 0.149 CQU003 Flinders 32 1 1.000 0.000 0.000 N/A N/A Norman 32 15 7.186 0.781 0.861 0.092 0.048 Elizabeth 18 5 3.661 0.944 0.727 -0.299 -0.130 Gilbert 34 16 8.996 0.647 0.889 0.272 0.157 Chillagoe 32 15 9.022 0.875 0.889 0.016 0.008 Mitchell 33 16 8.442 0.879 0.882 0.003 0.002 Weipa 28 8 3.950 0.821 0.747 -0.100 -0.048 Calvert 21 12 9.910 0.476 0.899 0.470 0.308 Gregory 16 11 7.758 0.438 0.871 0.498 0.331 McArthur 20 12 6.897 0.750 0.855 0.123 0.065 CQU004 Flinders 31 5 3.593 0.677 0.722 0.061 0.032 Norman 30 12 5.000 0.667 0.800 0.167 0.091 Elizabeth 18 5 2.723 0.167 0.633 0.737 0.583 Gilbert 34 7 2.181 0.324 0.542 0.403 0.252 Chillagoe 32 12 6.990 0.656 0.857 0.234 0.133 Mitchell 34 13 7.837 0.471 0.872 0.461 0.299 Weipa 26 7 3.654 0.692 0.726 0.047 0.024 Calvert 16 4 2.381 0.125 0.580 0.785 0.645 Gregory 6 7 5.143 0.333 0.806 0.586 0.415 McArthur 19 5 2.625 0.526 0.619 0.150 0.081 CQU006 Flinders 31 5 2.458 0.548 0.593 0.075 0.039 Norman 30 8 4.390 0.133 0.772 0.827 0.706 Elizabeth 18 3 2.418 0.444 0.586 0.242 0.138 Gilbert 34 8 3.899 0.853 0.744 -0.147 -0.069 Chillagoe 31 9 5.018 0.484 0.801 0.396 0.247 Mitchell 34 11 4.129 0.353 0.758 0.534 0.364 Weipa 30 5 2.308 0.600 0.567 -0.059 -0.029 Calvert 18 6 2.132 0.444 0.531 0.163 0.089 Gregory 2 2 1.600 0.500 0.375 -0.333 -0.143 McArthur 22 6 1.820 0.364 0.450 0.193 0.107
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
64
4.3.4 Population differentiation
Given that the mutation model for C. quadricarinatus microsatellites was unknown,
FST estimates to determine population differentiation were employed. Table 4-5
details pairwise FST estimates for eastern C. quadricarinatus populations. An FST of
1 indicates fixation of alternate alleles in subpopulations and an FST of 0 indicates
the same alleles occur in both populations at identical frequencies. FST values
among paired eastern sites ranged from 0.046 between Chillagoe and Mitchell
(populations within the same river system) to 0.545 between Flinders and Elizabeth.
Table 4-5: Population differentiation for eastern C. quadricarinatus populations. FST values are below the diagonal. Probability values based on 1000 permutations showed significant differentiation (p<0.01) at all pairwise comparisons. Values in bold represent highest and lowest values.
Flinders Norman Elizabeth Gilbert Chillagoe Mitchell Weipa Calvert McArthurFlinders Norman 0.334 Elizabeth 0.545 0.225 Gilbert 0.445 0.141 0.198 Chillagoe 0.405 0.116 0.145 0.120 Mitchell 0.387 0.121 0.161 0.148 0.046 Weipa 0.509 0.264 0.338 0.308 0.212 0.149 Calvert 0.465 0.188 0.314 0.272 0.195 0.172 0.247 McArthur 0.474 0.223 0.341 0.275 0.221 0.194 0.276 0.193
4.3.5 Genetic Distance
Chord distance (Cavalli-Sforza and Edwards 1967) was estimated to determine how
genetically similar C. quadricarinatus populations were to each other. Table 4-6
shows the chord distance estimates among eastern C. quadricarinatus populations.
Values close to zero imply two populations are genetically very similar.
Chord estimates reveal a pairwise genetic distance measure of 0.037 for Mitchell
and Chillagoe. Since Chillagoe is a tributary within the Mitchell River catchment,
genetic distance estimates were expected to be low. This result concurs with the
observed FST values (Table 4.5). The highest Chord genetic distance seen was
evident between Flinders and Weipa, two ‘eastern’ sites separated by a large
geographic distance (~700km).
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
65
Table 4-6: Chord distance estimates using data from five microsatellite loci for ‘eastern’ C. quadricarinatus populations. Figures in bold highlight the highest and lowest values.
Flinders Norman Elizabeth Gilbert Chillagoe Mitchell Weipa Calvert McArthurFlinders Norman 0.0855 Elizabeth 0.1292 0.0939 Gilbert 0.1030 0.0553 0.0709 Chillagoe 0.1191 0.0666 0.0589 0.0426 Mitchell 0.1174 0.0713 0.0587 0.0567 0.037 Weipa 0.1499 0.1236 0.1177 0.1110 0.099 0.0815 Calvert 0.1459 0.1132 0.1198 0.1113 0.103 0.0885 0.1005 McArthur 0.1176 0.0928 0.1074 0.0803 0.082 0.0777 0.0955 0.0736
4.3.6 Isolation by Distance
4.3.6.1 Mantel tests
Chord distance was used to determine if coastline distance was correlated with
genetic distance among sampled ‘eastern’ C. quadricarinatus populations. A
significant p value was negated by the very small R2 value so the hypothesis of
isolation by distance among eastern C. quadricarinatus populations was rejected (Z
= -78.9221, r = 0.4835, one-sided p = 0.0150). 4.3.6.2 FST values graphed against geographic distance A scatterplot pattern for coastline distance against FST estimates among eastern
populations (Figure 4-1) shows allele frequencies in each population have drifted
independently and are not correlated with the geographic distances separating
sampled populations.
Figure 4-1: Graphical representation of genetic differentiation, estimated by FST and geographic distances (km) of eastern population pairs.
Eastern C. quadricarinatus populations
R2 = 0.0043
0
0.1
0.2
0.3
0.4
0.5
0.6
0 200 400 600 800 1000 1200 1400
coastline distance (km)
Fst
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
66
4.3.7 AMOVA
Variation within and among populations/regions was partitioned by Analysis of
Molecular Variance - AMOVA. Within population variation accounted for 73% of the
total genetic variation for the eastern lineages. Of the remaining 27%, 22% was
accounted for by variation among populations within regions. Variation among
regions accounted for only 4.6% (Table 4-7).
Table 4-7: AMOVA showing the partitioning of variation within and among eastern populations of C. quadricarinatus. The populations were grouped into western Gulf (McArthur and Calvert), southern Gulf (Flinders, Norman, Gilbert and Elizabeth) and northern Gulf (Chillagoe, Mitchell and Weipa) NB Gregory was not included in this analysis
Source of Variation (eastern) d.f. Variance % Φ statistic P Among Regions (ΦCT) 3 4.65 0.04644 < 0.010 Among Pops./ Within Regions (ΦSC) 5 22.03 0.23105 < 0.010 Within Populations. (ΦST) 511 73.32 0.26677 < 0.010
4.3.8 Bottleneck analysis
Populations were tested for heterozygosity excess and loss of allelic diversity at
microsatellite loci as might occur immediately following a severe bottleneck or
founder event, see Table 4-8.
Excess heterozygosity was statistically significant for the Wilcoxon’s signed rank test
for Norman (p= 0.031), Elizabeth (p=0.015), Chillagoe (p=0.015), Weipa (p=0.015)
and Gregory (p=0.046). A population contraction in the Flinders population was also
detected by the second method, the mode-shift indicator. Furthermore, the Flinders
population exhibited significant distortion of allele frequency distribution, but did not
reach significance with a Wilcoxon’s sign rank test (Table 4-8).
Table 4-8: Evidence for recent bottlenecks was indicated by significant heterozygosity excess or an allele distribution ‘mode shift’ (#graphs not shown).
Wilcoxon’s (p value)
‘mode-shift’ indicating bottleneck#
Flinders 0.062 yes Norman 0.031* no Elizabeth 0.015* no Gilbert 0.593 no Chillagoe 0.015* no Mitchell 0.046 no Weipa 0.015* no McArthur 0.312 no Calvert 0.312 no Gregory 0.046* no
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
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4.3.9 Genetic Diversity Estimates
Average microsatellite diversity for each population was calculated using the
Shannon information index (Table 4-9). Genetic diversity in the eastern populations
ranged from 0.584 to 1.8188.
Table 4-9: Shannon's Information index (Shannon and Weaver 1949) of eastern C. quadricarinatus populations for five microsatellite loci, their mean value and standard deviation. Values in bold are highest and lowest mean values (n/a – monomorphic)
CQU001 CQU002 CQU003 CQU004 CQU006 Mean St. Dev Flinders 0.3845 n/a n/a 1.3702 1.1653 0.7130 ±0.520 Norman 1.2710 1.6044 2.2746 1.9611 1.6829 1.7588 ±0.379 Elizabeth 0.5297 0.7683 1.4158 1.189 0.9810 0.9768 ±0.346 Gilbert 0.6742 1.7272 2.4148 1.1452 1.6051 1.5133 ±0.653 Chillagoe 1.0298 1.6812 2.4124 2.1364 1.8342 1.8188 ±0.523 Mitchell 1.6493 1.6281 2.3791 2.2923 1.8471 1.9592 ±0.355 Weipa 0.7027 0.8713 1.5863 1.5187 1.0993 1.1557 ±0.389 Calvert 1.3478 1.2242 2.3837 0.9941 1.1568 1.4213 ±0.552 McArthur 1.5111 1.8420 2.1510 1.2577 0.9744 1.5472 ±0.465
4.3.10 Microsatellite Analysis of Western Populations
4.3.10.1 Linkage Disequilibrium
Significant disequilibrium was found for 1 out of 12 tests (8.3%; after Bonferroni
correction). The loci CQU004 – CQU006 were found to be linked in the Howard
population (p=0. 00058; α=000416). The low number of populations in this group
makes this pair statistically significant, however, this result is most probably due to
chance.
4.3.10.2 Hardy Weinberg Departures
Four out of twelve tests (33%) in the western group were found to have p-values
significant at the 0.004 level after Bonferroni corrections (Appendix 3):
CQU006: Howard and Roper; CQU003: Howard; CQU004: Howard.
In the western populations, Howard deviated from HWE at all three loci, and 50% of
the populations deviating at CQU006.
4.3.10.3 Molecular Diversity
Common indices for western C. quadricarinatus populations are presented in Table
4-10. Actual population sizes range from 11 (Roper) to 30 (Howard), however,
sample sizes (n) varied as amplification success varied among loci. Observed
heterozygosity for western populations ranged from 0.25 – 0.79.
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
68
Most loci exhibited lower estimates of observed heterozygosity compared with
expected heterozygosity, suggesting factors such as selection, inbreeding or null
alleles had influenced C. quadricarinatus populations. This result concurred with
that observed for eastern populations (Table 4.4).
4.3.11 Null Alleles
Null allele proportions of up to 51% were estimated (locus CQU004; Roper
population) in western C. quadricarinatus populations, as shown in Table 4-10. The
proportion of null alleles detected in western populations was lower than that
detected in eastern populations (when comparing estimates of amplifiable loci in
western populations). Because western populations did not amplify at most
microsatellite loci, this was a surprising result
Table 4-10: Common indices for western C. quadricarinatus populations; sample size (N), number of alleles (Na), number of effective alleles (Ne), observed heterozygosity (HO), expected heterozygosity (HE), and Fixation Index (F), and Brookfield’s (1996) estimate of null allele proportion (r). Values in bold indicate upper values for each locus.
N Na Ne HO HE F r CQU003 Ord 22 5 2.367 0.682 0.577 -0.181 -0.082 Adelaide 24 10 5.731 0.792 0.826 0.041 0.020 Howard 29 12 7.680 0.483 0.870 0.445 0.286 Roper 8 6 4.923 0.750 0.797 0.059 0.030 CQU004 Ord 22 8 3.585 0.727 0.721 -0.009 -0.004 Adelaide 24 9 4.085 0.583 0.755 0.228 0.128 Howard 30 11 7.895 0.500 0.873 0.427 0.271 Roper 4 5 4.571 0.250 0.781 0.680 0.515 CQU006 Ord 22 3 1.909 0.364 0.476 0.236 0.134 Adelaide 24 7 4.299 0.750 0.767 0.023 0.011 Howard 28 11 7.293 0.750 0.863 0.131 0.069 Roper 9 7 4.765 0.444 0.790 0.438 0.280
4.3.12 Population differentiation
FST estimates to determine population differentiation are shown in Table 4-11.
Western FST values range from 0.108 between Roper and Howard, and 0.304
between Roper and Ord, the two most geographically distant (in terms of coastline
distance) populations.
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
69
Table 4-11: Population differentiation for western C. quadricarinatus populations. FST values are below the diagonal. Probability values based on 1000 permutations and all were significant (p<0.01). Values in bold represent highest and lowest values.
Ord Adelaide Howard Roper Ord Adelaide 0.274 Howard 0.159 0.116 Roper 0.304 0.184 0.108
4.3.13 Genetic Distance
Genetic distance estimates for western C. quadricarinatus populations are
presented in Table 4-12. Genetic distance estimates among western populations
were generally lower than eastern populations. Chord genetic distance estimates
correspond to FST measures, indicating Ord and Roper Rivers (0.927) are the most
genetically differentiated, while Ord and Howard (0.0526) were the most similar
populations.
Table 4-12: Chord distance estimates using data from three microsatellite loci for western C. quadricarinatus populations. Figures in bold indicate the highest and lowest values.
Ord Adelaide Howard Roper Ord Adelaide 0.0875 Howard 0.0526 0.0633 Roper 0.0927 0.0808 0.0594
4.3.14 Isolation by Distance
4.3.14.1 Mantel tests
An isolation by distance model was rejected among western C. quadricarinatus
populations (Z = -22.8130, r = 0.3822, one-sided p = 0.3440).
4.3.14.2 FST values graphed against geographic distance
The scatterplot pattern of western populations was inconclusive as sample size was
low, but the few points reflect genetic structuring similar to that observed for eastern
populations, where allele frequencies in each population have drifted independently
without relation to the geographic distances separating populations (Figure 4-2).
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
70
Figure 4-2: Graphic relationship between genetic differentiation FST and geographic distances (km) of western population pairs.
4.3.15 AMOVA
Analysis of molecular variance examined the partitioning of variation across various
scales of pooled samples and indicated that microsatellite allelic variation within
population variation accounted for 80% of the total genetic variation for the western
lineages. Of the remaining 20%, 11% was accounted for by variation among
populations within regions. Variation among the regions accounted for only 8%
(Table 4-13). This trend was also seen in AMOVA analyses for eastern populations.
Table 4-13: AMOVA showing the partitioning of variation within and among western populations of C. quadricarinatus. The western populations were grouped as western (Ord), northern (Adelaide and Howard) and eastern (Roper).
Source of Variation (western) d.f. Variance % Φ statistic P Among Regions (ΦCT) 2 8.04 0.0804 < 0.010 Among Pops./ Within Regions (ΦSC) 1 11.67 0.1268 < 0.010 Within Populations. (ΦST) 170 80.29 0.1970 < 0.010
4.3.16 Bottleneck analysis
Excess heterozygosity was statistically significant for the Wilcoxon’s signed rank test
for Howard (p=0.031), see Table 4-14. A bottleneck in the Roper population was
also detected by the second method, the mode-shift indicator. Loss of rare alleles
caused the allelic distribution to shift for the Roper population, and this was
statistically significant at the 5% level, see Table 4-14. The Roper population
exhibited significant distortion of allele frequency distribution, but did not reach
significance with a Wilcoxon’s sign rank test.
Western C. quadricarinatus populations
R2 = 0.08
00.050.1
0.150.2
0.250.3
0.35
0 2000 4000 6000 8000
coastline distance (km)Fs
t
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
71
Table 4-14: Evidence for recent bottlenecks was indicated by significant heterozygosity excess or an allele distribution ‘mode shift’ (#graphs not shown).
Wilcoxon’s test
p value ‘mode-shift’ indicating
bottleneck# Ord 0.937 no Adelaide 0.906 no Howard 0.031* no Roper 0.062 yes
4.3.17 Genetic Diversity Estimates
Average microsatellite diversity was calculated using the Shannon Information index
for each population (Table 4-15). Genetic diversity in the western populations
ranged from 1.1531 to 2.1978. Values were generally higher than those seen in
eastern populations.
Table 4-15: Shannon's Information index (Shannon and Weaver 1949) of western C. quadricarinatus populations for three microsatellite loci, their mean value and standard deviation. Values in bold are highest mean values
CQU003 CQU004 CQU006 Mean St. Dev Ord 1.1471 1.5366 0.7755 1.1531 ±0.3806 Adelaide 1.9794 1.7157 1.6178 1.7710 ±0.1870 Howard 2.2421 2.2012 2.1501 2.1978 ±0.0461 Roper 1.6675 1.5596 1.7249 1.6507 ±0.0839
4.3.18 Gene Flow Estimates
In some studies a value for gene flow among populations is often calculated on the
basis of the relationship between FST and Nem. This model assumes, however, that
populations are at equilibrium with respect to gene flow and genetic drift, i.e. that the
divergence due to drift is equal to the convergence due to gene flow (Nei et al.,
1977; Rousset, 1996). A significant number of C. quadricarinatus populations
deviated from expected Hardy-Weinberg equilibrium, thus it is not appropriate to
estimate gene flow here.
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
72
4.4 Discussion Genetic markers with intrinsically different rates of mutation and/or mode of
inheritance provide greater power for hypothesis testing when levels and patterns of
genetic structuring among populations are examined. Microsatellite data generated
here concur with mtDNA results reported earlier (Chapter 3), and add further
support to the existence of two highly divergent C. quadricarinatus gene pools in
Australia; referred to as an ‘eastern’ lineage and a ‘western’ lineage. Western
populations (Ord, Howard, Adelaide and Roper Rivers) failed to amplify at 75% of
the C. quadricarinatus specific microsatellite loci developed from an ‘eastern’ C.
quadricarinatus individual. This is an unusual outcome as microsatellite loci have
even been reported to amplify across divergent taxa such as bovine specific loci
amplifying sheep and goat DNA (Moore et al., 1991); and marine turtle markers
amplifying in freshwater turtles (FitzSimmons et al., 1995). The failure to amplify
some loci in western populations probably reflects ancient mutations in the priming
sites (assumed conserved regions) of microsatellites developed for eastern C.
quadricarinatus stocks.
Until now, the few genetic studies of wild C. quadricarinatus populations have
revealed relatively low levels of genetic variation. Austin (1996) used five variable
allozyme loci to detect an average of 2.2 alleles per locus across eleven C.
quadricarinatus populations, including one population from PNG. Macaranas et al.
(1996) used six variable allozyme loci to reveal a mean number of 2.5 alleles per
locus, heterozygosity estimates of up to 0.058 and FST estimates between 0.000 –
0.075 for 12 Australian C. quadricarinatus populations. In the same study RAPDs
detected relatively high levels of variation among C. quadricarinatus populations
(13.3 variable loci/primer pair), but problems with PCR amplification and
repeatability proved problematic for this method (Macaranas et al. 1996). Despite
the western lineage of populations not amplifying at all loci in this study,
microsatellite loci have proven informative and identified a high level of genetic
structuring among Australian C. quadricarinatus populations. C. quadricarinatus
populations sampled across northern Australia possessed a mean number of 30.6
alleles/locus and 7.3 alleles/population (eastern: 7.2; western 7.8), high levels of
heterozygosity (up to 0.944; average of 0.523) and significant levels of differentiation
among populations (FST values up to 0.545; average of 0.25). The mean number of
alleles per locus and heterozygosity levels detected by microsatellite loci were about
10 times as high as those for allozyme data, suggesting that the C. quadricarinatus
microsatellite loci developed here have a high resolving power for detecting genetic
diversity.
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
73
Approximately one third of the alleles detected here were shared between eastern
and western lineages. Microsatellite loci, by virtue of their high mutation rate, are
susceptible to problems of homoplasy, where alleles of identical size result from
independent mutational processes (Schlötterer et al., 1998). Queney et al. (2001)
observed homoplasy at microsatellite loci between two well-supported phylogenetic
clades of rabbit populations on the Iberian Peninsula. Considering the high level of
divergence detected at two mtDNA loci and microsatellite markers here, it is unlikely
that all shared alleles at microsatellite loci are identical by descent as a direct
consequence of dispersal. Instead, the occurrence of some identical sized alleles
probably results from homoplasy.
The high level of genetic variation detected in C. quadricarinatus using
microsatellites is consistent with microsatellite studies in other species, including
other freshwater crayfish. Five microsatellite markers used to assess the population
genetic structure of the European white-clawed crayfish (Austropotamobius pallipes)
revealed a mean heterozygosity value of 0.394 (Gouin et al. 2000; Gouin et al,
2002). Microsatellites also detected a high level of heterozygosity (ranging from 0.25
- 1.0) in the red swamp crayfish, Procambarus clarkii (Beliore and May, 2000).
Extensive polymorphism (heterozygosity up to 0.799) was also detected in Cherax
tenuimanus using two microsatellite loci (Imgrund et al., 1997).
A significant number of C. quadricarinatus populations deviated from expected
Hardy-Weinberg equilibrium (HWE). Samples sizes may not have been sufficiently
large to reflect a true representation of genotypic proportions present in the sampled
populations due to the highly variable nature of microsatellite loci. However,
deviations from HWE equilibrium can also result from null alleles, such that many
apparent homozygotes are, in reality, heterozygotes between a visible and a null
allele (Callen et al., 1993; Pemberton et al., 1995). Null alleles estimates (Table 4-4
and 4-3) indicate a large proportion of null alleles may be present in the C.
quadricarinatus populations analysed here. Null alleles may also explain ‘dropouts’ -
the inability to amplify some individuals at some loci even though PCR conditions
were re-optimised and the same DNA sample amplified at other loci inferring that
DNA quality was not the problem.
Non-amplifying alleles are thought to occur when mutations prevent primers from
binding (Callen et al, 1993), and have been observed in a wide variety of species
(white shrimp, (Ball et al., 2003); humans, Callen et al, 1993; bears, (Paetkau &
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
74
Strobeck, 1995). Null allele frequencies of up to 25% have been reported in the
literature (swallow Hirundo rustica; (Primmer et al., 1995)). Frequency estimates for
null alleles in C. quadricarinatus were extremely high, up to 71% in eastern
population and 51% in western populations. These frequencies are based on HW
expectations; if C. quadricarinatus populations are not at equilibrium (for any other
reason) then estimates will be biased. Wolfus et al. (1997) observed null alleles in
breeding trials of the Penaeid shrimp, P. vannamei. Offspring from homozygote
parents for their respective alleles were not all heterozygous for maternal and
paternal alleles. Many studies however do not have the advantage of pedigree
information to determine if null alleles are present in their datasets and this can
potentially lead to false assumptions about inferred population structure. A family
pedigree analysis of C. quadricarinatus is needed to confirm the existence and
extent of null alleles in these populations. This action will be particularly important
before the markers are considered for application in breeding programs for cultured
stocks.
Even if proportions of null alleles in C. quadricarinatus populations have been
overestimated, it is obvious from the data that populations are carrying mutations in
priming sites that influence the level of differentiation among populations. Null alleles
can bias statistics that assume HWE. While caution should be taken interpreting the
results as it could be argued that high proportions of null alleles could compromise
the integrity of the C. quadricarinatus microsatellite data. However, the levels and
patterns of genetic variation across C. quadricarinatus microsatellite loci is
essentially consistent and indicates populations of C. quadricarinatus from discrete
drainages are highly divergent. Also the results are consistent with other genetic
markers (nDMA, mtDNA). The high mutation rate at microsatellite loci, that makes
them attractive markers for population and pedigree studies in itself will produce null
alleles in divergent populations over evolutionary time.. With little or no gene flow,
there is no exchange of alleles among populations, and this can increase the levels
of null alleles in a population by allowing mutations in priming sites to accumulate.
Although FST and other statistical estimates may be over inflated, these
microsatellite data indicate C. quadricarinatus populations are highly divergent. This
high degree of divergence is in agreement with 16s and COI genes (Chapter 3),
which also revealed a high degree of divergence, where a western and an eastern
form of C. quadricarinatus were detected. The western form failed to amplify at two
C. quadricarinatus specific microsatellite loci. Although there is potential for null
alleles to overstate the degree of divergence among C. quadricarinatus populations,
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
75
there is a clear and consistent argument that populations are evolving
independently. These microsatellite data are also in accord with genetic divergence
detected among populations of other freshwater organisms. High levels of genetic
divergence are indicative of populations that are evolving independently like those of
freshwater organisms inhabiting dendritic rivers systems.
Genetic diversity among the sampled C. quadricarinatus populations may have been
underestimated due to the high levels of null alleles observed here. Flinders River
had the lowest genetic diversity estimate, which corresponds with a recent
bottleneck detected. In comparison with genetic diversity estimates for the European
freshwater crayfish A. pallipes (using RAPDs (Gouin et al., 2001)), sampled C.
quadricarinatus populations had four times the amount of genetic diversity. A.
pallipes is, however, endangered, due to overfishing, making it difficult to draw
comparisons with wild C. quadricarinatus populations. Diversity values can,
however, provide a baseline for future reference for managing and monitoring the
‘genetic health’ of wild C. quadricarinatus populations and/or when sourcing
broodstock for culture purposes.
High FST and genetic distance estimates observed among pair wise analyses of C.
quadricarinatus populations is consistent with limited or no gene flow occurring
among river drainages within regions. Speculation that C. quadricarinatus may
disperse between adjacent or nearby drainages at times of flood, either across
floodplains, or via flood plumes therefore seems highly unlikely in populations
examined here. A wide variety of freshwater taxa including fish (Waples, 1991;
Hughes, 1996; McGlashan & Hughes, 2002; Costello, 2003), insects (Hughes et al.,
1999), molluscs (Hughes et al., 2004) and crustaceans (Campbell et al., 1994;
Hughes, 1996; Daniels et al., 1999) also exhibit high levels of genetic subdivision
due to the isolating effects of independent riverine drainages. Although
metapopulation processes such as extinction and colonisation events can result in
elevated estimates of FST (Whitlock & McCauley, 1990), and lead to inaccurate
estimates of real gene flow rates, the extensive and consistently high levels of
differentiation observed here among drainages argue for a high degree of genetic
isolation of C. quadricarinatus populations present in discrete drainages.
Seasonal harsh climatic conditions experienced in ephemeral rivers across C.
quadricarinatus’ distribution could induce bottleneck events. Recent genetic
bottlenecks were detected in six eastern populations (Norman, Elizabeth, Chillagoe,
Weipa, Gregory and Flinders Rivers) and two western populations (Howard and
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
76
Roper Rivers) supporting the hypothesis that C. quadricarinatus populations have
been subjected to periodic population crashes in the recent past.
AMOVA results indicated that there are high levels of genetic diversity in the wild
populations of C. quadricarinatus studied here and that this diversity was higher
within rather than between populations. Results of AMOVA revealed significant
differences (p<0.01) in genetic variation within populations for both eastern and
western lineages. This coupled with high FST estimates suggest wild C.
quadricarinatus populations are evolving independently. It is difficult to assess the
individual effects of gene flow and drift on populations, especially when most natural
populations, including C. quadricarinatus are not at equilibrium (McCauley, 1993).
Both Mantel tests calculated in IBD and Hutchison and Templeton’s (1999) method
for evaluating relative historical influences of gene flow and drift showed no
significant correlation between geographical distance and genetic distance among
populations within eastern or western lineages. Thus C. quadricarinatus populations
apparently follow an island-like model where gene flow is independent of geographic
distance among populations and where genetic divergence occurs to a greater or
lesser extent as a result of genetic drift. The river systems that C. quadricarinatus
inhabit are generally large, with the confluence of branches near the mouth of the
drainage, essentially making branches within a drainage, discrete rivers. More
extensive sampling within drainages and along branches would be needed to test
for a Stream Hierarchy Model of genetic isolation, but it is likely that C.
quadricarinatus individuals disperse within a drainage rather than between discrete
drainages.
Both intrinsic and extrinsic factors appear to limit contemporary gene flow among C.
quadricarinatus populations inhabiting different drainages. Intrinsic characteristics of
C. quadricarinatus include life history traits and low dispersal capabilities. Due to
the recognition that C. quadricarinatus do not apparently migrate to mate, fully
formed larvae hatch on the mothers’ abdomen (in contrast to pelagic larvae that
disperse on water currents) and because they are intolerant to prolonged salinity, C.
quadricarinatus have low dispersal capabilities and hence wild populations are
structured. Extrinsic factors reinforce the low vagility of C. quadricarinatus’ life
history traits. With a rise in sea level to present day sea levels, land connections
between Australia and PNG were broken and the Gulf of Carpentaria formed. This
severed freshwater connections among rivers where C. quadricarinatus occurred,
leaving obligate freshwater inhabitants of the outer branches of extensive ancient
Chapter 4 – Microsatellite analysis of C. quadricarinatus population
77
river systems to evolve in isolation. One potential consequence of the evolution of
discrete populations is the potential for inbreeding. The patterns observed here,
however, suggest that any deleterious effects of inbreeding are not significant under
natural conditions. Perhaps the effective size of most populations is sufficiently large
to minimise inbreeding, or populations may be able to tolerate raised inbreeding
levels if inbreeding accumulates at a slow rate.
A number of wild C. quadricarinatus populations are under threat from
anthropogenic practices such as impoundment, overfishing, and pollution from
agricultural run off (Yen & Butcher, 1997). With limited (if any) gene flow occurring
among sampled C. quadricarinatus populations, independent evolution C.
quadricarinatus in drainage catchments have important management repercussions
for conserving genetic diversity in situ. Since genetic diversity is partitioned among
drainages, if populations within a drainage go extinct, it is likely that they will only be
recolonised by individuals from within the same drainage. This is an important
consideration if restocking of wild populations was considered as a conservation
strategy. Drainages would need to be restocked with individuals from the same
drainage, to not only conserve and maintain genetic integrity of wild C.
quadricarinatus, but because independent evolution probably reflects local
adaptation within drainages. Admixture of genetic divergent individuals of the same
species can have detrimental consequences on the fitness of offspring and speed
up extinction rather than enhance populations that are being restocked (McGinnity
et al., 2004).
Chapter Five: Genetic diversity of cultured stocks
78
5.0 Genetic diversity in cultured C. quadricarinatus stocks compared with wild populations 5.1 Introduction Many studies that have investigated genetic diversity in hatchery fish stocks and
their wild relatives have reported that farmed stocks possess much lower levels
of genetic diversity when compared with that present in their wild progenitors
(Allendorf & Phelps, 1980; Cross & King, 1983; Garcia-Marin et al., 1991;
Coughlan et al., 1998). In small populations, like most that are brought into
culture, genetic drift will tend to reduce allelic diversity over time by
approximately ½ Ne per generation, where Ne is the effective population size
(Frankham, 1996). Effective population size is influenced by a number of factors
including, family size, sex ratio and changes in population size across
generations (Lande & Barrowclough, 1987). Small effective population sizes are
of particular concern when fecundity is high, as is the case for many aquatic
species, because a few breeding individuals are capable of producing large
numbers of offspring, only a small number of founders are usually brought into
captivity. This can accelerate the loss of genetic variation, if not managed
appropriately. Small effective population sizes can also lead to increased levels
of inbreeding, which may further erode genetic variation. Loss of genetic
diversity can limit, or even reduce the productivity of culture stocks, particularly if
subsequent breeding management strategies are not aimed at maintaining or
enhancing genetic diversity.
In culture, it is just as important to prevent production losses due to inbreeding,
as it is to actively promote productivity via genetic improvement practices.
Implementation of selective breeding will reduce levels of genetic variation in the
target stocks via two major processes. First, most domesticated terrestrial
species are highly selected for a few economically important traits (eg growth
rate), which decreases overall genetic diversity as a consequence of directional
selection. Secondly, most populations within particular breeds tend to be almost
genetically uniform as a result of high levels of inbreeding and artificial selection
favouring high-performing reproductive individuals. The high levels of artificial
selection and intensive use of elite broodstock have greatly reduced the
effective population size of many terrestrial domestic breeds. For example, the
USA Holstein cattle population of approximately 10 million individuals has an
effective population size smaller than 1000 individuals (Georges & Anderson,
1996). While productivity may remain high, future improvement in important
Chapter Five: Genetic diversity of cultured stocks
79
traits are likely to be small as levels of exploitable variation decline each
generation and is not supplemented from outside (eg. by periodically introducing
unrelated individuals). Unfortunately, in the past little attention has been paid to
the levels of genetic diversity in initial broodstock populations for most
aquaculture species and these issues are seldom considered until much later
when serious problems may already have developed (eg Oreochromis niloticus,
(Eknath et al., 1993); Cyprinus carpio (Hulata, 1995b); Paralichthys olivaceus
(Sekino et al., 2002))
Low levels of genetic variation in broodstocks can limit the potential for future
genetic gains from artificial selection. The extent to which genetic improvement
can be achieved for any single quantitative trait in a breeding program will
depend on the amount of genetic variation that exists for the desired trait/s
(Davis & Hetzel, 2000). Wild populations offer a range of genetic diversity
distributed both within and among populations as they will have been exposed to
the natural process of evolution. As a consequence of evolution, populations
become locally adapted to a wide range of environments and often show high
levels of phenotypic variability and high fitness in natural environments. Utilising
this genetic diversity in culture stocks effectively is the key to sustainable
aquaculture because it enables farmers to adapt stocks to suit their own
ecological needs and culture conditions. Without extensive genetic diversity in
the founding brood stock at the beginning however, options for long term
productivity of culture stocks in a variety of environments are likely to be
compromised.
5.1.1 Current status of C. quadricarinatus culture stocks
C. quadricarinatus has many attributes that make it well suited to aquaculture.
The species is physically robust, possesses a simple life cycle, requires basic
production technology, a simple diet and is economical to produce (Jones &
Curtis, 1994). In Australia, C. quadricarinatus are commonly marketed in 20g
size grades ranging from 30-50g (at approximately $11.50/kg) to greater than
120g (at approximately $19.00/kg) (AFFA, 2002). At present 60% of C.
quadricarinatus are sold within Queensland, 10% interstate and 30% are
exported. While current production in Australia is primarily marketed
domestically, the growth potential for the industry lies largely with an expanding
export demand for this species. Potential export markets for C. quadricarinatus
have been reported to be capable of absorbing as much as 2000 tonnes
Chapter Five: Genetic diversity of cultured stocks
80
p.a. (AFFA, 2002). Existing export markets are in Europe and South East Asia,
but additional market development activity has also focussed on Japan, Korea,
Taiwan and the USA (Piper, 2000). International sales to date, however, have
been limited by Australia’s small production volume and the consequent risk of
an inconsistent supply of product.
Culture methodologies are well developed for C. quadricarinatus and include
polyculture with finfish (Brummett & Alon, 1994; Karplus et al., 1995; Rouse &
Kahn, 1998), monosex grow out for improved growth (pers. comm. Rouse) and
a selective line with improved growth rate (Jones et al., 2000). Since culture
practices have essentially been optimised, the next step will be to improve the
productivity of culture breeds. In most new species brought into culture, founder
effects, genetic drift, intentional selection and inadvertent selection as a result of
culture practices are likely to have reduced background genetic diversity levels.
Currently little is known about the genetic diversity levels that exist in cultured C.
quadricarinatus stocks in Australia compared with that present in the wild. No
systematic approaches were adopted to capture broad genetic diversity when
initial culture stocks were sourced, suggesting that genetic variation is likely to
be low compared with natural genetic variation in wild populations. Furthermore,
the practice of new producers sourcing their stock from existing producers, thus
imposing sequential bottlenecks on culture stocks is likely to have eroded the
remaining genetic variation further in many culture stocks and lead theoretically
at least to high levels of inbreeding. Some circumstantial evidence from
overseas producers has suggested that this scenario may already have
eventuated in some places with reports of declines in stock productivity, early
onset of maturation and morphological abnormalities occurring in increasing
frequency (Hulata pers. comm.)
Many Queensland C. quadricarinatus farm stocks were derived from a single C.
quadricarinatus producer in south east Queensland. This stock was developed
originally from wild collections of individuals from several southern Gulf Rivers
(pers. comm. Hutchings). Understanding how the levels of genetic diversity in
culture stocks compare with those present in wild stocks will therefore provide
baseline information on which to base future choices about how productivity of
cultured stocks can be enhanced.
The current study used microsatellite markers to compare the levels and
patterns of genetic diversity in a number of Australian and overseas cultured C.
Chapter Five: Genetic diversity of cultured stocks
81
quadricarinatus stocks. Estimates of genetic diversity were also compared with
data from wild C. quadricarinatus populations in an attempt to determine how
much genetic variation has been exploited in culture stocks to date and how
much may remain to be exploited in the future.
5.2 Methods
5.2.1 Sampling of cultured stocks
Samples of culture stocks were taken from four local farms or Research
Agencies and three major producers outside Australia.
Yandina 1996 (sampled in 1996) – Yandina on the Sunshine coast, south east
Queensland. Ross Rickard, manager/owner of this stock, collected broodstock
personally from the wild. This stock was sourced directly from the wild to
maximise the genetic diversity in the founding stock, unlike most other
producers in Australia who have obtained cultured stock from established farms.
Yandina 2002 (sampled in 2002) – the Yandina stock was sampled 6 years later
to investigate temporal effects of culture on genetic diversity levels.
Parkridge (sampled in 1996) – situated south west of Brisbane in south east
Queensland. A relatively small hobby farm in a ‘rural’ suburb of Brisbane. A
second sample in 2002 was sought, but by this time the farm had ceased
operation. The origins of farm broodstock are unknown.
Walkamin (sampled in 2002) - Second generation of the Walkamin selected
strain from Queensland Department of Primary Industries (QDPI) at Walkamin.
In 1993, a strain evaluation of wild C. quadricarinatus populations from the
southern Gulf of Carpentaria was undertaken by QDPI. Later a selective
breeding programme was initiated that resulted in a significant improvement in
growth rate compared with existing culture stocks. Wild Flinders and Gilbert
River strains exhibited the best culture performance in comparative trials and
were chosen consequently for inclusion in the selective breeding experiment.
Approximately 500 crayfish (100 males and 400 females) representing
unselected stocks of a mixture of Flinders and Gilbert River strains were crossed
reciprocally to create a synthetic ‘Walkamin Strain’. The aim was to cross the
chosen lines of the Flinders and Gilbert strains, to minimise inbreeding and to
maximise any potential heterotic attributes. This study was initiated without any
Chapter Five: Genetic diversity of cultured stocks
82
knowledge of the relative levels of genetic diversity within or between the wild
stocks chosen for inclusion.
Hutchings (sampled in 2002) – Aratula, southeast Queensland. Robin
Hutchings was the first farmer to trial farming C. quadricarinatus commercially in
the mid 1980s, after a failed attempt to culture C. tenuimanus, a species that
proved intolerant of the extreme Queensland summer temperatures. The
Hutchings farm has supplied many of the farms in southeast Queensland with
broodstock after C. tenuimanus stocks failed and has also supplied live C.
quadricarinatus broodstock to many overseas producers. Hutchings collected
and crossed C. quadricarinatus from the southern Gulf of Carpentaria to
produce the stock that many SE Queensland farms use today (Hutchings pers
comm.). No reports were made, of the number, locality or sex of individuals that
comprised his original founding broodstock.
In addition to Australia, C. quadricarinatus are also farmed in the United States,
South Africa, Mexico, New Zealand, China, Israel and Ecuador (Rouse, 1995,
Karplus et al, 1995, Rubino, 1992; Macaranas et al, 1995). Tissue samples
were obtained from the following farms overseas:
Israel (samples obtained in 2002) – an unknown number of C. quadricarinatus
from Hutchings farm (Karplus, pers com) were introduced to Israel in 1993.
There have been reports of loss of stock productivity and physical abnormalities
in this culture stock that could reflect negative effects of inbreeding (Hulata, pers
com). The stock is kept essentially for research but there has been interest from
Israeli fish farmers in developing the species in culture there.
Ecuador (samples obtained in 2003) – Also sourced originally from Hutchings
farm, precise number and sex of broodstock could not be confirmed. Many large
farms are being developed in Ecuador to meet rising demand from the US
market.
Mexico (samples obtained in 2003) – C. quadricarinatus were imported into
Mexico in the early 90’s and are believed to have originated indirectly via
Switzerland (Garcia, pers com). C. quadricarinatus culture is still an expanding
industry in Mexico (Garcia, pers. com). Additional information about the likely
origins of the Mexican C. quadricarinatus could not be confirmed.
Chapter Five: Genetic diversity of cultured stocks
83
Producers in Europe could not be identified to supply tissue samples for genetic
analysis for this study.
5.2.1 Analysis of genetic diversity in cultured C. quadricarinatus stocks
5.2.1.1 DNA extraction and microsatellite analysis
DNA extraction and microsatellite amplification procedures were the same as
used for wild populations (see Chapter 4.2.2). All five microsatellite loci used to
assess genetic diversity in the wild eastern Australian populations amplified
culture populations successfully, indicating that the culture stocks examined
here had most likely been derived originally from wild ‘eastern’ populations (see
Table 5-1).
Table 5-1: Five C. quadricarinatus microsatellite loci were successfully used to determine the levels of genetic variability in C. quadricarinatus cultured stocks.
5.2.2 Statistical analyses
5.2.2.1 Molecular diversity of cultured stocks
Common indices of genetic variation including: mean number of alleles per
locus, number of effective alleles and mean heterozygosity (Ho and He) were
estimated for culture stocks for each microsatellite locus using GenAlEx (Peakall
and Smouse, 2001). Brookfield’s (1996) equation (as described in Chapter
4.2.6.3) was implemented to estimate null allele frequencies (r).
5.2.2.2 Linkage disequilibrium of cultured stocks
Linkage disequilibrium measures the statistical dependence of two loci. Tests
were performed using GENEPOP ver. 3.1 (Raymond and Rousset, 1995).
5.2.2.3 Hardy-Weinberg Equilibrium (HWE) of cultured stocks
HWE departures can be measured using Wright’s F-indices (Wright, 1965). FIS
and FIT measure such a departure within subpopulations and in the whole
populations, respectively. These indices were estimated according to Weir and
Cockerham (1984) and unbiased estimates of the exact P-values calculated
Locus Repeat TA (oC) MgCl2 mM Amplified
CQU.001 (GT)11~(GT)18 55 3 Yes CQU.002 (CA)27 50 2 Yes CQU.003 (CA)29 50 2 Yes CQU.004 (CA)32 50 3 Yes CQU.006 (CT)11 55 3 Yes
Chapter Five: Genetic diversity of cultured stocks
84
using a Markov chain randomisation method to determine if Hardy-Weinberg
expectations were met (Guo & Thompson, 1992). All results were adjusted for
multiple simultaneous comparisons using a sequential Bonferroni correction
(Rice 1989) implemented in GENEPOP ver. 3.1 (Raymond and Rousset 1995).
5.2.2.4 Testing for bottlenecks
To determine if C. quadricarinatus culture stocks had experienced a recent
bottleneck, a Wilcoxon’s sign-rank test was implemented and a qualitative
descriptor of allele frequency distributions (‘mode-shift’ Indicator) that can
discriminate bottlenecked populations from stable populations were conducted
using ‘BOTTLENECK’ (Piry et al, 1999).
5.2.2.5 Shannon-Weaver Index of genetic diversity
Loss of genetic diversity in domesticated stocks can impact negatively on the
long term productivity of culture stocks. The Shannon-Weaver Index (Shannon
and Weaver 1949) was calculated in GenAlEx (Peakall and Smouse, 2001).
5.2.2.6 Origins of culture stocks – assignment testing
Multi locus genotypes from individuals can be used to build up genetic profiles to
identify exclusive groups within a sample and to assign individuals to the group
from which it is most likely to have been derived. The power of assignment
testing using multiple independent microsatellite loci is positively correlated with
the degree of genetic structure present among groups in a sample (Maudet et
al., 2002). Assignment testing in this study was conducted using Cornuet et al’s
(1999) exclusion-simulation method to obtain likelihood probabilities for each
individual assignment as implemented in GENECLASS 1.0.02 (Cornuet et al.,
1999). Since each locus is assumed to be independent, the likelihood of an
individual’s multi locus genotype occurring in a given population is calculated as
the product of likelihood estimates measured at each of the separate loci.
Assignment probabilities by this method are however confounded by the
presence of alleles endemic to a single population and can be overcome by
artificially inserting a single representative of endemic alleles to all samples
where it is absent (“Add one in”) as recommended by Cornuet et al. (1999).
5.2.2.7 Comparison of culture stocks and wild populations
Differences in the mean number of alleles per locus, mean heterozygosity and
mean diversity index estimates were compared among wild C. quadricarinatus
populations, Australian and C. quadricarinatus culture stocks obtained from
Chapter Five: Genetic diversity of cultured stocks
85
overseas using a one-way analysis of variance in SPSS for Windows Version
11.5 (Lead Technologies).
5.3 Results
5.3.1 Molecular diversity of culture stocks
Common indices derived from five microsatellite loci in five Australian and three
overseas cultured C. quadricarinatus stocks are presented in Table 5-2. Mean
number of alleles per locus for all culture stocks ranged from 3 – 14, averaging
6.9 alleles/population. Australian C. quadricarinatus culture stocks contained an
average of 7.6 alleles/stock per locus, while overseas C. quadricarinatus culture
stocks contained only 5.4 alleles/stock. The effective number of alleles (Ne),
ranged from 1.4 – 6.8 and observed heterozygosity ranged from 0.219 – 1.00,
averaging 0.56. Heterozygosity is a measure of individual diversity. While
observed heterozygosity levels were relatively high, in most cases they were
less than the expected heterozygosity estimates based on observed allelic
diversity. Such deficiencies can indicate inbreeding, selection or presence of null
alleles, but since expected heterozygosity is based on populations at HW
equilibrium (and most C. quadricarinatus stocks did not conform to HWE), such
interpretations may not be appropriate here.
The majority of fixation values (F) were positive also suggesting inbreeding,
selection or undetected alleles; negative values indicate an excess of
heterozygosity, (Table 5-2). Since culture stocks have been derived from wild
populations where null alleles are likely (see Chapter 4), and exposed during
domestication to processes of selection and small effective population sizes,
random breeding was not expected. Null allele proportions of up to 45% (locus
CQU004; Yandina) were detected, presented as ‘r’ in Table 5-2. Brookfield’s
(1996) method for estimating null alleles assumes populations are in HW
equilibrium, since the artificial populations here probably violate HW
assumptions (ie no selection, and random mating), the number of null alleles
may be an overestimation. A pedigree study could directly measure the
proportion of null alleles if necessary.
5.3.2 Linkage Disequilibrium
Linkage disequilibrium was observed at only one pair of loci (Israel cqu002-
cqu006 p= 0.000) out of a possible 40 tests, a result expected by chance.
Chapter Five: Genetic diversity of cultured stocks
86
Table 5-2: Common indices for cultured C. quadricarinatus stocks; sample size (N), number of alleles (Na), number of effective alleles (Ne), observed heterozygosity (HO), expected heterozygosity (HE), and Fixation Index (F) and Brookfield’s (1996) ‘r’ estimating the frequency of null alleles. Values in bold indicate upper values for each locus.
N Na Ne Ho HE F r CQU001 Yandina 1996 30 6 2.970 0.633 0.663 0.045 0.023 Yandina 2002 30 6 2.594 0.500 0.614 0.186 0.103 Parkridge 30 6 3.403 0.567 0.706 0.197 0.110 Walkamin 30 6 4.545 0.700 0.780 0.103 0.054 Hutchings 32 6 3.717 0.750 0.731 -0.026 -0.013 Israel 25 6 5.482 0.680 0.818 0.168 0.092 Ecuador 20 7 3.361 0.850 0.702 -0.210 -0.095 Mexico 39 6 2.878 0.385 0.653 0.411 0.258 CQU002 Yandina 1996 29 7 2.010 0.310 0.502 0.382 0.236 Yandina 2002 28 5 3.638 0.500 0.725 0.310 0.184 Parkridge 30 5 2.651 0.533 0.623 0.144 0.077 Walkamin 30 7 4.206 0.633 0.762 0.169 0.092 Hutchings 32 3 1.373 0.219 0.271 0.194 0.108 Israel 25 5 2.809 0.520 0.644 0.193 0.107 Ecuador 20 3 1.766 0.300 0.434 0.308 0.182 Mexico 40 2 1.694 0.425 0.410 -0.037 -0.018 CQU003 Yandina 1996 30 14 3.766 1.000 0.734 -0.362 -0.153 Yandina 2002 30 14 5.158 0.867 0.806 -0.075 -0.036 Parkridge 30 3 1.869 0.533 0.465 -0.147 -0.068 Walkamin 30 10 4.762 0.733 0.790 0.072 0.037 Hutchings 32 3 1.474 0.313 0.322 0.029 0.015 Israel 25 5 2.306 0.440 0.566 0.223 0.126 Ecuador 20 3 1.956 0.450 0.489 0.079 0.041 Mexico 40 4 2.341 0.550 0.573 0.040 0.020 CQU004 Yandina 1996 30 7 5.114 0.300 0.804 0.627 0.457 Yandina 2002 30 7 4.592 0.600 0.782 0.233 0.132 Parkridge 30 7 5.921 0.333 0.831 0.599 0.427 Walkamin 29 4 3.609 0.276 0.723 0.618 0.448 Hutchings 32 9 6.225 0.656 0.839 0.218 0.122 Israel 23 7 4.898 0.348 0.796 0.563 0.392 Ecuador 20 9 5.369 0.650 0.814 0.201 0.112 Mexico 40 8 3.628 0.400 0.724 0.448 0.288 CQU006 Yandina 1996 30 12 6.498 0.700 0.846 0.173 0.095 Yandina 2002 30 13 6.844 0.700 0.854 0.180 0.099 Parkridge 30 6 3.523 0.533 0.716 0.255 0.146 Walkamin 30 14 5.921 0.767 0.831 0.078 0.040 Hutchings 32 9 5.520 0.469 0.819 0.428 0.272 Israel 23 8 5.658 0.652 0.823 0.208 0.116 Ecuador 20 6 4.255 0.750 0.765 0.020 0.010 Mexico 39 9 4.899 0.821 0.796 -0.031 -0.015
Chapter Five: Genetic diversity of cultured stocks
87
5.3.3 Hardy Weinberg Equilibrium
Deviations for Hardy-Weinberg equilibrium were observed in seventeen out of
forty comparisons (42%), (Table 5-3). Significant deficiencies of heterozygotes
were observed in the sampled culture stocks. While null alleles are probably the
likely explanation in wild C. quadricarinatus populations, cultured stocks are
likely to also be influenced by artificial admixture, intentional or unintentional
selection, inbreeding, or a combination of all of these factors to some extent.
Table 5-3: Results of Hardy-Weinberg equilibrium exact tests given as p-values (significance indicated by * after Bonferroni adjustment p= 0.01)
Yandina
1996 Yandina
2002 Parkridge Walkamin Hutchings Israel Ecuador Mexico CQU001 0.5076 0.3581 0.0163 0.3737 0.0182 0.0000* 0.1483 0.0000* CQU002 0.0000* 0.0000* 0.0089* 0.0032* 0.1497 0.0207 0.2414 1.0000 CQU003 0.0467 0.6631 1.0000 0.0022* 0.2022 0.0214 0.5176 0.0579 CQU004 0.0000* 0.0466 0.0000* 0.0000* 0.0000* 0.0000* 0.0364 0.0000* CQU006 0.0592 0.0000* 0.0000* 0.1840 0.0000* 0.0000* 0.6617 0.0169
5.3.4 Genetic distance among cultured stocks
Cavalli-Sforza and Edwards’ (1967) Chord distance (DCE) estimates are
presented in Table 5-4. The Walkamin stock displayed was most divergent
(0.067) from both the Parkridge and Hutching stocks. Overseas stocks (in
Italics), Israel, Ecuador and Mexico show little genetic divergence from each
other and were most similar to the Hutchings stock (0.042, 0.013, 0.017
respectively), adding weight to the preconception that they had been derived
from the Hutchings stock.
Table 5-4: Genetic distance measures of C. quadricarinatus culture stocks using Chord distance algorithm. Values in bold indicate the largest values.
Yandina
1996 Yandina
2002 Parkridge Walkamin Hutching Israel Ecuador Mexico Yandina 96 0.000 Yandina 02 0.030 0.000 Parkridge 0.034 0.032 0.000 Walkamin 0.051 0.043 0.067 0.000 Hutching 0.040 0.057 0.047 0.067 0.000 Israel 0.035 0.048 0.040 0.064 0.042 0.000 Ecuador 0.040 0.050 0.042 0.065 0.013 0.042 0.000 Mexico 0.038 0.048 0.047 0.058 0.017 0.036 0.010 0.000
Chapter Five: Genetic diversity of cultured stocks
88
5.3.5 Testing for genetic bottlenecks
Significant heterozygosity was detected Parkridge (p=0.015), Israel (p=0.015),
Ecuador (p=0.015) and Mexico (p=0.015) cultured stocks, see Table 5-5. A
significant distortion of allele frequency distribution further supports a recent
bottleneck occurred in the Parkridge stock (Table 5-5).
Table 5-5: Evidence for recent bottlenecks was indicated by significant heterozygosity excess or an allele distribution ‘mode shift’ (#graphs not shown).
Wilcoxon’s test p valuemode-shift indicating a
bottleneck# Yandina 96 0.687 no Yandina 02 0.078 no Parkridge 0.015* yes Walkamin 0.031* no Hutchings 0.078 no Israel 0.015* no Ecuador 0.015* no Mexico 0.015* no
5.3.6 Genetic diversity estimates: Shannon’s Index
Shannon's Information index (Peakall and Smouse, 2001) calculated for C.
quadricarinatus culture stocks are presented in Table 5-6. Shannon’s index is a
numerical value that estimates genetic diversity; higher values represent higher
genetic diversity. The Yandina, Yandina 2002 and Walkamin stocks possess the
highest diversity, while Parkridge, Hutchings, and the overseas stocks contain
reduced amounts of genetic diversity. Diversity in the Yandina stock apparently
increased over time, but the increase was not statistically significant and so may
be a sampling issue. Walkamin, the intentionally hybridised and selected strain
and the Yandina stocks, where management strategies were employed to
actively maintain or increase allelic diversity (via wild collections), contained the
highest amount of allelic richness at all loci screened expect for locus CQU004.
Chapter Five: Genetic diversity of cultured stocks
89
Table 5-6: Shannon Index (Shannon and Weaver 1949) of genetic diversity of cultured populations for 5 microsatellite loci and their mean. Values in bold are highest mean values
CQU001 CQU002 CQU003 CQU004 CQU006 Mean St. DevYandina 1996 1.346 1.116 1.836 1.723 2.141 1.6324 ±0.405 Yandina 2002 1.134 1.436 2.092 1.694 2.188 1.7088 ±0.442 Parkridge 1.413 1.243 0.819 1.857 1.437 1.3538 ±0.374 Walkamin 1.602 1.605 1.882 1.332 2.123 1.7088 ±0.302 Hutchings 1.479 0.512 0.61 1.997 1.866 1.2928 ±0.695 Israel 1.744 1.203 1.017 1.705 1.862 1.5062 ±0.372 Ecuador 1.436 0.697 0.847 1.847 1.594 1.2842 ±0.492 Mexico 1.345 0.600 1.049 1.567 1.763 1.2648 ±0.465
5.3.7 Comparing genetic diversity between Australian and overseas culture stocks
ANOVAs were performed to test for differences in mean number of alleles,
observed heterozygosity and Shannon’s Indices of diversity among Australian
and overseas culture stocks. 5.3.7.1 Number of alleles per locus
No significant difference in the number of alleles was observed when comparing
Australian wild populations to overseas C. quadricarinatus culture stocks
(p=0.335; F=1.108).
5.3.7.2 Levels of heterozygosity
A one-way ANOVA to compare levels of heterozygosity among wild C.
quadricarinatus populations and farmed C. quadricarinatus stocks showed no
significant difference, although culture stocks generally exhibited higher levels of
heterozygosity (p=0.538; F=0.624).
5.3.7.3 Shannon Index estimates
No significant difference in diversity indices was observed between Australian
wild and overseas C. quadricarinatus culture stocks (p=0.517; F=0.665).
5.3.8 Assignment of C. quadricarinatus stocks to wild populations sampled
Assignment tests were performed to determine if wild population origins of
cultured stocks could be assigned to discrete wild populations. Results are
presented in Table 5-7.
Chapter Five: Genetic diversity of cultured stocks
90
Table 5-7: Proportion of C. quadricarinatus culture individuals assigned a river drainage based on 5 microsatellite loci performed in GENECLASS. (NB: the largest proportion for each farmed stocks is indicated in bold and only estimates larger than 5% are shown)
Yandina Yandina 02 Parkridge Walkamin Hutchings Israel Ecuador MexicoFlinders 0.80 0.63 0.93 0.33 0.94 0.84 0.65 0.88 Norman 0.12 0.05 Gilbert 0.06 0.37 0.50 0.08 0.05 0.05 Mitchell 0.17 Weipa Calvert McArthur 0.08 0.25 0.08
Chapter Five: Genetic diversity of cultured stocks
91
5.4 Discussion The growing economic potential of C. quadricarinatus culture, both domestically and
internationally, prompted the current study into relative levels of genetic diversity in
commercial C. quadricarinatus stocks. The study employed five microsatellite
markers to quantify genetic diversity in five Australian and three overseas C.
quadricarinatus culture stocks. Genetic diversity levels were then compared with
those documented for wild populations presented earlier (Chapter 4).
Microsatellite analysis showed that C. quadricarinatus stocks are not at Hardy-
Weinberg equilibrium. Many wild populations analysed in Chapter 4 also deviated
from Hardy-Weinberg equilibrium, however, the impact of domestication can
compound this situation. C. quadricarinatus culture stocks have most probably been
exposed to repeated small effective population sizes, and may have experienced
intentional and/or unintentional selection during domestication, Deviations from HW
equilibrium have been reported in other culture species, including farmed abalone in
Australia, Haliotis rubra and South Africa, H. midae (Evans et al., 2004). This result
suggests that many standard population genetic parameters which assume HWE
may be inappropriate statistics for assessing domesticated stocks. So a comparative
approach could be more informative. One of the major concerns during domestication is loss of genetic diversity because
the small number of individuals commonly brought into culture is unlikely to carry a
true representation of the genetic diversity present in ancestral population/s. Loss of
genetic diversity can induce kinship among breeders and result in inbreeding.
Inbreeding, characterised by an excess of homozygotes, can have negative (ie
costly) impacts on culture stocks including loss of productivity (Gjedrem, 1997;
Doyle et al., 2001; Sugaya, 2002). In contrast, the average level of observed
heterozygosity observed for C. quadricarinatus cultured stocks was not significantly
lower in cultured C. quadricarinatus stocks than for the wild populations. If anything,
culture stocks possess slightly higher average heterozygosity levels (culture stocks
ranged from 0.22 – 1.00; average: 0.56, than wild populations (ranged from 0.00 -
0.944; average: 0.523). This slight increase may be a consequence of the
domestication process where culture stocks when wild individuals from different
drainages were introgressed. Intentional mixing of wild germplasm is a common
practice during the domestication process, as heterosis or an increase in genetic
diversity may result. However, for C. quadricarinatus this practcie should be
undertaken with caution due to the presence of two morphologically similar yet
genetically divergent lineages in northern Australia.
Chapter Five: Genetic diversity of cultured stocks
92
Fortunately, wild populations from discrete drainage systems that belong to the
same genetic lineage were hybridised to generate the commercial C.
quadricarinatus stock in Queensland. Recently however efforts have been made to
domesticate wild C. quadricarinatus stocks in the Northern Territory where ‘western’
C. quadricarinatus occur. This increases the potential for contamination of unique
gene pools in the future where ‘eastern’ and ‘western‘ forms could be mixed in
culture or more seriously, individuals of the alternative morph escape into wild
populations after translocation. If this occurred, given the extent of genetic
differentiation between ‘eastern’ and ‘western’ C. quadricarinatus there is potential
for outbreeding depression. A recent example of such an outcome occurred in the
catfish culture industry in Thailand. Breeders had determined that hybrids developed
by artificially crossing males of an alien species, the African catfish (Clarias
gariepinus), with females of a native species, the Thai walking catfish (C.
macrocephalus) grew much faster and possessed high disease resistance in culture
than did individuals of either of the pure species (Senanan et al., 2004), so
enhancing productivity in culture. Although farmed hybrid catfish dominate the
domestic catfish markets in Asia, the native walking catfish (C. macrocephalus) also
remains important in this industry because it provides the broodstock for the females
used to generate hybrid catfish. Recently, concerns have been raised that escapee
hybrid catfish from fish farms could threaten wild populations of Thai walking catfish
due to competition, predation, and genetic introgression due to interbreeding
(Senanan, 2004). It is feared that some escaped hybrids have backcrossed with
native catfish and fish that look like a native catfish may be, in reality, introgressed
individuals bearing genetic material from the introduced African species. This
process of introgressive hybridisation may ultimately cause the loss of genetic
distinctiveness of the native C. macrocephalus, putting wild stocks at risk of
extinction and could result in the use of unrecognized introgressed individuals as
aquaculture broodstock. By inadvertently crossing an introgressed individual of C.
macrocephalus with pure C. gariepinus, fish farmers would be diluting the genetic
contributions of C. macrocephalus, and therefore, could lose desirable traits in the
hybrids. This example may serve as an important warning for mixing ‘eastern’ and
‘western’ lineages of C. quadricarinatus in the future.
Hedgecock and Sly (1990) believe measures for assessing relative genetic diversity,
particularly percent heterozygosity, are insensitive to substantial genetic changes
that may occur in cultivated aquatic stocks. Vuorinen (1984) states that total
extinction of any allele should be considered more harmful than a simple reduction
Chapter Five: Genetic diversity of cultured stocks
93
in overall heterozygosity. Loss of unique alleles is probably a more meaningful
measure of how well genetic variation is being maintained in a hatchery/cultured
stock than is changes in heterozygosity levels. Probability predicts that rare or low
frequency alleles are usually first to be lost as genetic diversity declines in a
population. It is crucial to recognise that once started, this process affects all
polymorphic loci in the same way, both coding and non-coding sequences.
Only a small reduction in the mean number of alleles per population/stock was
observed when cultured stocks (6.9 alleles/stock) and wild populations (7.2
alleles/population in ‘eastern’ (5 loci); 7.8 alleles/population in ‘western’ (3 loci))
were compared. It is often expected that domestication erodes genetic diversity, as
seen in a number of cultured species, Atlantic salmon - Salmo salar (Cross & King,
1983) marine prawns - Penaeus japonicus (Sbordoni et al., 1986) and oysters -
Crassostrea gigas (Hedgecock and Sly, 1990). However, other studies have
revealed no significant differences in genetic diversity between wild and hatchery
populations such as for turbot, Scophthalmus maximus (Bouza et al., 1997;
Coughlan et al., 1998). While no statistically significant difference was seen in the
mean number of alleles between wild and cultured C. quadricarinatus stocks, a
slight reduction was apparent in culture, especially if wild stocks were compared
directly to just overseas culture stocks.
Cultured C. quadricarinatus stocks are likely to have experienced population crash
inducing genetic bottlenecks, when a small number of founders were first brought
into captivity. Evidence of recent bottlenecks were observed in the Parkridge and
Walkamin stocks. However, the intentional hybridisation of two wild river populations
to create the Walkamin strain probably accounts for the significant heterozygote
excess in this stock. The bottleneck in the Parkridge stock was detected in both
bottleneck tests and is probably true as it is thought that this population was derived
from the Yandina stock. All three overseas culture stocks indicate recent
bottlenecks, again these are populations derived from an existing stock (the
Hutchings stock). This is suggesting there is an increased risk of the detrimental
effects of small effective population sizes (eg. reduced genetic variation) as new
stocks are obtained from existing ones.
Genetic differentiation estimates among culture stocks and assignment tests (Table
5-4) indicate that overseas culture stocks have been most likely derived from the
Hutchings stock – a known supplier of live C. quadricarinatus to overseas
Chapter Five: Genetic diversity of cultured stocks
94
producers. The Parkridge stock is closely related to the Yandina stock (1996)
suggesting Yandina might be the source of the Parkridge stock.
Assignment results indicate that all C. quadricarinatus culture stocks possess alleles
that have originated from the Flinders River (proportions of 33-94%). Alleles
consistent with those from the Gilbert River drainage are also present in significant
proportions in the Yandina 1996 (37%) and Walkamin (50%) culture stocks.
Assignment testing suggested all culture stocks were derived from more than a
single wild population. However note that this test can only conclude the most likely
origin from the set of wild populations sampled, and without extensive sampling
exact origins cannot be confirmed.
In conclusion, domestication of C. quadricarinatus to date has not apparently
resulted in significant reductions in exploitable genetic diversity (heterozygosity or
alleles richness) when compared to the wild populations sampled in this study.
Since wild populations are essentially evolving independently, and are subjected to
harsh seasonal environmental fluctuations, with little or no gene flow, they are also
probably exposed to repeated small effective populations sizes and possible
periodical inbreeding effects. Comparing culture stocks to wild population to gauge
‘genetic health’ may not be a suitable measurement scale for evaluating genetic
diversity in culture stocks. This study does however indicate a large amount of
genetic diversity that has yet to be exploited is distributed among wild populations.
This diversity provides a resource for future stock improvement programs for C.
quadricarinatus culture.
Chapter Six: General Discussion
95
6.0 General Discussion Over exploitation by humans of many wild aquatic resources has resulted in
declines in catches or reduced catch quotas, placing increased pressure on farmed
aquatic resources to meet the demand for seafood (Pauley and Christensen, 1995).
Australia is in a unique position to develop aquaculture as a first rate primary
industry because our environments are relatively unpolluted, policies are in place to
reduce the risk of disease and Australia possesses a suite of native species suitable
for culture that can be marketed domestically and internationally. A major constraint
on aquaculture to meet increasing demand for seafood is the relatively low
productivity of many current aquaculture stocks. Most production is carried out
using stocks recently captured from natural environments. Even though aquatic
species have greater potential for genetic improvement than most terrestrial species
(see Hulata, 2001), aquaculture stocks (mainly from the northern hemisphere) have
only recently begun to benefit from genetic improvement programs (Gjedrem, 2000;
Fjalestad et al., 2003b).
Harnessing wild variants in stock improvement programs can improve efficiency and
make culture stocks more productive and economically viable to ensure the
increasing demand for seafood can be met. Understanding the levels and patterns
of genetic diversity in wild stocks can assist in developing sustainable aquaculture
industries because wild stocks can be an important resource for improving culture
stocks. Currently, such data are either very limited or totally absent for most native
Australian cultured species and has only been investigated in the major culture
species overseas (salmon, carp, some marine prawns etc). This is usually only
investigated out of necessity, for example when performance of culture stocks has
declined (eg. O. niloticus; Eknath,1993). The current study investigated the levels
and patterns of genetic diversity in wild Australian C. quadricarinatus populations
and in culture stocks in Australia and overseas.
Previous systematic studies of C. quadricarinatus have been conflicting. Reik (1969)
investigated morphological differences among wild C. quadricarinatus populations in
Australia and recognised two discrete taxa. Later Austin (1996) used allozyme
electrophoresis to contradict this and conclude C. quadricarinatus in Australia
consisted of a single gene pool. These opposing conclusions have important
ramifications for fisheries and aquaculture policy and management of wild
populations.
Chapter Six: General Discussion
96
Molecular markers (mtDNA and microsatellites) examined in the current study
support Reik’s (1969) recognition of the existence of two divergent C.
quadricarinatus gene pools in northern Australia. Analysis of two mtDNA gene
portions (16s and COI) revealed two divergent lineages in northern Australia, that
last shared a common ancestor during the Tertiary (approximately 2.8 – 7.5 million
years ago). The two discrete genealogical lineages in Australia correspond
geographically to a ‘western’ lineage (from the Ord river in WA to the Roper River in
the Northern Territory) and an ‘eastern’ lineage (from the McArthur River in NT to tip
of Cape York in northern QLD). While arguing species/subspecies status was not
the purpose of this study, the results show conclusively that C. quadricarinatus
lineages in Australia are not a single homogenous gene pool and this finding
warrants a reassessment by of C. quadricarinatus systematics. At the very least, the
level of mtDNA divergence observed means that C. quadricarinatus lineages should
be considered as evolutionary significant units (Moritz, 1994).
This study also examined whether contemporary gene flow is ongoing among wild
C. quadricarinatus populations. Genetic parameters estimated from microsatellite
data indicated little if any ongoing gene flow occurs among discrete river drainages
so populations in discrete drainages are evolving independently. The microsatellite
data, in contrast to previous allozyme studies, suggests that genetic diversity is
generally high in wild populations and most diversity is higher within than between
populations.
6.1 Significance for wild populations Genetic analysis of wild C. quadricarinatus populations within the eastern and
western lineages indicate that populations, from major drainage basins, best fit an
island model of population structure i.e. discrete populations with very limited
interchange. This means that management of wild stocks should be based at a
drainage basin level i.e. self-recruiting drainages rather than a broader
metapopulation structure. The management importance of recognising an island
population structure is that if over-harvesting in one drainage occurs, populations
are unlikely to be replenished naturally by recruitment from adjacent drainages in a
meaningful time period, if at all.
Restocking to maintain populations densities of desired species (a common practice
for replenishing depleted recreational fishing species) would therefore need to use
C. quadricarinatus derived from local drainages as opposed to restocking with C.
quadricarinatus sourced from other drainages from within the respective lineage.
Chapter Six: General Discussion
97
Any restocking attempts for C. quadricarinatus need to be carefully considered as
outbreeding depression may result when C. quadricarinatus from different drainage
basins are mixed. Although not currently practiced for C. quadricarinatus, re-
stocking wild C. quadricarinatus populations may soon be necessary. Experimental
crosses of even and odd year pink salmon from the same river, demonstrated the
potential negative consequences of restocking, if restocking occurs without a full
understanding of possible genetic incompatibility between the indigenous and
restocked individuals (Gharrett et al, 1999). Gharrett et al. (1999) reported fewer F2
hybrids from even year and odd year broodstock pink salmon (Oncorhynchus
gorbuscha) crosses (two lines that are temporally isolated by Pacific salmon’s strict
two-year life cycle) survived than F2 controls, suggesting a reduction in fitness or
outbreeding depression.
Limited experimental breeding trials between ‘western’ and ‘eastern’ C.
quadricarinatus stocks resulted in either no offspring or offspring that exhibited
reduced fitness (Ogden 2000). Therefore, the long term impact of translocating C.
quadricarinatus river strains and releasing them to the wild to restock depleted wild
populations, could result in irreversible declines in fitness of some wild C.
quadricarinatus populations or even local extinctions of indigenous wild populations.
It is highly recommended therefore, that C. quadricarinatus are only restocked with
indigenous river strains.
6.2 Significance for aquaculture/fisheries policy 6.2.1 Aquaculture
Commercial C. quadricarinatus culture stocks are currently a genetic mix of a few
individuals from river drainages (with the major contributor the Flinders River). Most
have been exposed to some form of selection (intentional or unintentional) and
therefore should not be allowed to interbreed with wild C. quadricarinatus. To avoid
escapees from farms interbreeding with wild C. quadricarinatus, genetic risk
assessments should be carried out on existing and new farms. A genetic risk
assessment is the process of identifying and describing vulnerability to extinction,
loss of genetic diversity within wild populations, loss of genetic diversity among
populations and loss of fitness of wild populations from artificial propagation or other
human intervention (Shaklee et al., 1999; Mace, 2001). The greatest potential
genetic threat to wild C. quadricarinatus, would appear to be the potential for
interbreeding of eastern and western lineages. Therefore, each culture strain should
Chapter Six: General Discussion
98
not be farmed outside its ‘natural’ distribution to limit potential for introgression of
discrete genetic lineages if cultured individuals escape.
6.2.2 Fisheries
Accidental genetic pollution of wild genetic resources can also occur during
transportation of individuals for culture or recreational fishing. Policies currently in
place for using live bait in freshwater systems demand that bait should be caught
locally, with no translocations among rivers. Translocation of C. quadricarinatus into
private water bodies should also adhere to the ‘local’ policy so that floods etc don’t
allow foreign C. quadricarinatus access to the wild.
6.3 Recommendations for C. quadricarinatus culture industry To conserve natural wild stocks, it is recommended that at least two centralised
hatcheries be set up, one for western and one for eastern commercial C.
quadricarinatus stocks. These hatcheries could monitor and maintain genetic
diversity in their broodstocks, conserve economically important strains and initiate
breeding programs independently. This will reduce the need for private hatcheries to
collect wild germplasm for broodstock and limit potential for accidental introgression
of the two discrete C. quadricarinatus lineages.
Each hatchery would evaluate wild C. quadricarinatus populations for desired
economic or indirect economic traits that may allow for the development of culture
strains best suited to different culture environments (eg. cold tolerance). Conserving
as much genetic diversity as possible essentially is an insurance against future
directions not yet known, such as changing market requirements. Currently the main
markets for C. quadricarinatus are within Australia and SE Asia, but European
markets are large and have different market requirements (eg preference for large
head for Europe rather than the large tail for Australia/ SE Asia) (pers. comm.
Hutchings).
Hatcheries could evaluate crosses between various wild C. quadricarinatus
populations for potential heterosis, ideally mono-sex (all-male or all-female) or sterile
offspring. For example, hybrids between female Cherax rotundus, and male Cherax
albidus produced all male progeny. This is a highly desirable result as it offers
considerable potential for eliminating the growth suppressing uncontrolled
reproduction that can occur in commercial ponds prior to harvest. Experiments
concluded that all-male hybrid progeny were almost twice as large (50±2.2g) as
mixed sex C. albidus crayfish (27.2 ±1.7g) (Lawrence et al., 2000) at the same age.
Chapter Six: General Discussion
99
In parallel, hatcheries could develop a synthetic C. quadricarinatus culture stock as
the precursor for future stock improvement programs. An important prerequisite for
achieving genetic improvement in breeding studies is that the starting population
has high levels of genetic variation for the traits of interest. An example of a
comprehensive genetic improvement program was conducted for tilapia (O.
niloticus) in the Philippines. The Genetically Improved Farmed Tilapia (GIFT) Project
of ICLARM (now Worldfish Centre) was started in 1988, and intentionally collected
from throughout O. niloticus’ natural range in Africa, to create the starting population
for the selection program (Bentsen et al., 1998). In each generation (excluding the
first) strong selection for growth rate was implemented. The selection response in
growth rate during five generations averaged 13.2% per generation (Eknath et al.,
1993; Bentsen et al., 1998). This level of genetic gain has been repeated for several
fish species (see review by,Hulata, 2001). The GIFT program demonstrated that
strategic exploitation of natural genetic diversity in wild stocks can be a very
effective way of improving culture performance of aquatic species and a similar
approach should be applicable to C. quadricarinatus as high levels of genetic
variation in the wild have been detected here.
6.4 Future research 1) Research into potential heterosis or outbreeding depression among crosses of
eastern and western C. quadricarinatus should be pursued providing the studies are
undertaken in strict quarantine facilities. Correlating level of genetic distance to
potential for hybrid vigour or outbreeding depression will aid future genetic
improvement programs for culture stocks (i.e. aid in choice of compatible wild strains
for combining in breeding programs).
2) A diagnostic test for quantifying introgression of eastern and western genes in
should be evaluated. The current study suggests that a combination of mtDNA and
microsatellite markers could be used for this purpose. The ability to assess
introgression of unwanted genes” in the wild would be of benefit for monitoring and
conservation management of wild populations in the future.
3) The relative level of inbreeding in C. quadricarinatus culture stocks should also be
investigated. An important question, when trying to observe a biologically
meaningful difference in diversity levels, is to determine the degree of inbreeding C.
quadricarinatus can tolerate, as this can vary among species (Frankham, 1995). It
has been suggested that to avoid dramatic inbreeding depression effects, the
Chapter Six: General Discussion
100
observed average rate of loss of heterozygosity should not exceed 1% per
generation, which is considered an acceptable level of inbreeding (Franklin, 1980).
Allelic diversity instead of heterozygosity could be used as the test indicator for
monitoring broodstock and ensuring sufficient sample sizes to maintain diversity
levels. However, one important issue to consider first is defining a biologically
meaningful difference in diversity level, as the degree of inbreeding a species can
tolerate varies widely (Frankham, 1995). A species such as C. quadricarinatus,
considering its life history, may be biologically capable of tolerating relatively high
levels of inbreeding as natural populations crashes across evolutionary time frames
in harsh environments, probably mean that local populations have been exposed
naturally to high levels of inbreeding. Acceptable threshold levels for representative
genome sampling could be set. The criteria could determine the proportion of
neutral allelic diversity that should be included in new culture broodstocks. Different
criteria could be set for short term or long term breeding programs and for either
conservation or production purposes.
Chapter Seven: Conclusion
101
7.0 Conclusions Sequence analysis of C. quadricarinatus 16s and COI genes resolved two distinct
genealogical lineages in Australia and three in PNG. The two lineages in Australia,
western and eastern, are in agreement with the original taxonomic description of
Reik (1969), who based taxonomy on external morphological characters. The three
C. quadricarinatus populations sampled in PNG were all genetically distinct from
each other, with one also showing a close genetic relationship with the eastern
Australia lineage. Physical barriers in the form of extensive mountain ranges in PNG
will have reduced dispersal capabilities for C. quadricarinatus allowing genetic
differences to accumulate there over time. The close genetic relationship between
PNG and Australian C. quadricarinatus support a recent freshwater connection
between northern Australia and PNG. During times of lowered sea level, Australia
and southern PNG were linked as a single landmass with terrestrial and freshwater
organisms theoretically were able to disperse over land and via freshwater
connections among the two regions.
Genetic parameters estimated from microsatellite data indicated that there are high
levels of genetic diversity in wild of C. quadricarinatus populations and that this
diversity is higher within than between populations, indicating limited or no gene
flow. Speculation that C. quadricarinatus may disperse between adjacent or nearby
drainages at times of flood, either across floodplains, or via flood plumes seems
highly unlikely given the high genetic differentiation among C. quadricarinatus
populations. No significant correlation was formed between geographic distance and
genetic distance among wild C. quadricarinatus populations. C. quadricarinatus
populations sampled most closely resemble an island-like model, where gene flow is
independent of geographic distance among populations and where genetic
divergence occurs to a greater or lesser extent as a result of genetic drift.
Domestication of C. quadricarinatus to date would appear not to have resulted in
significant reductions in levels of genetic diversity (heterozygosity or alleles
richness) when compared to wild populations sampled in this study. However,
comparing culture stocks to wild populations to gauge their ‘genetic health’ may not
be a suitable measuring scale for evaluating genetic diversity in culture stocks. Wild
populations are essentially evolving independently, and are subjected to harsh
seasonal environmental fluctuations, with little or no gene flow. They are also
probably exposed to small effective population sizes and potentially to periodic
inbreeding as a consequence. The current study does however indicate that there is
Chapter Seven: Conclusion
102
a large amount of genetic diversity distributed among wild populations that has yet
to be exploited in culture. Genetic diversity in wild populations provides a resource
for future stock improvement programs for C. quadricarinatus culture and should be
conserved and managed accordingly. This resource provides Australian producers
with a competitive advantage over the international counterparts, because their
access to wild stocks is limited.
Farming genetically improved C. quadricarinatus stocks (instead of essentially wild
stocks) would mean an increased economic return for a similar outlay for farmers
and potentially provide the Australian C. quadricarinatus industry a chance to better
complete with the cheaper labour and production costs of C. quadricarinatus
industries in developing countries. This competitive advantage relies on access to
wild gene pools as a resource for future stock improvement programs. Wild C.
quadricarinatus populations are a resource the Australian C. quadricarinatus
industry can utilise for a long term improved and sustainable economic return.
Understanding how historical processes have shaped contemporary genetic
structure in the wild allows for better management strategies to conserve the
maximum amount of natural genetic diversity. An economically lucrative C.
quadricarinatus industry should, therefore, ensure the conservation of wild C.
quadricarinatus populations, as wild populations can serve as an important resource
for a culture industry to develop and expand with changing market demands.
103
8.0 Appendix 1 9 no issue no. 2000 865 primer note primer note 1 4 Graphicraft Limited, Hong Kong
Characterization of microsatellite loci in the redclaw crayfish, Cherax quadricarinatus N. BAKER,* K. BYRNE,† S. MOORE† and P. MATHER* *School of Natural Resource Sciences, Queensland University of Technology, Brisbane 4001 Australia, †Tropical Agriculture, CSIRO, University of Queensland, Brisbane 4067 Australia Keywords: aquaculture, Cherax quadricarinatus, cross-species amplification, freshwater crayfish, microsatellites, primers Received 23 September 1999; revision accepted 20 October 1999 Correspondence: P. Mather. Fax: +61-73864-1535; E-mail: [email protected] Redclaw (Cherax quadricarinatus) is a tropical freshwater crayfish native to northern Australia and southern Papua New Guinea. Commercial culture of redclaw began in the early 1980s from an initial small collection of wild crayfish from north Queensland. Today, redclaw are cultured in many countries throughout the world, including the USA, Central America, South Africa, New Zealand, China, Israel and Ecuador (Medley et al. 1994). Knowledge of populations in the wild is limited and it is unlikely that much of the natural variation that exists across the large natural range of this species has been exploited in culture. Genetic markers that can characterize relative levels of population variation and differentiation in both wild and cultured stocks are needed to aid development of the culture industry and to assist con-servation of wild stocks. Decapod crustaceans have commonly displayed low levels of allozyme variation (Busack 1988) and the redclaw crayfish is no exception (Austin 1996; Macaranas et al. 1995). Microsatellite loci have been very useful for documenting genetic diversity in many species with relatively low levels of allozyme variation (Hughes & Queller 1993). Here we present the characterization of seven microsatellite loci developed for redclaw and their amplification in other closely related Cherax species. Redclaw genomic DNA from muscle tissue was digested with Sau3AI. Digested DNA ranging in size from 300 to 600 bp was excised from a 1% agarose gel, purified and ligated into an appropriately cut and phosphatased pUC19 vector (Pharmacia). Plasmids were transformed into Escherichia coli via electroporation (Bio-Rad Gen Pulsar) and the cells grown on Hybond N+ membranes overnight at 37 °C. Duplicate filters were made. Colonies were probed with (dC-dA)n . (dG-dT)n labelled with [α 32 P]-CTP, randomly primed using the Mega Prime Kit (Amersham). After secondary screening, positive clones were purified using an alkaline/PEG precipitation and sequenced using ABI (Applied Biosystems) automated DNA sequencing. Samples for sequencing were prepared according to the procedure in the Perkin-Elmer ABI PRISM dye terminator sequencing reaction kit. Forward and reverse sequences were aligned with the aid of the computer program Sequence Editor (version 1.0.3, Applied Biosystems Inc.). Primers were designed with the aid of MacVector (version 4.5.1 (1993) International Biotechnologies, Inc.). Microsatellite loci primers were optimized using: 50 ng of genomic DNA, 1.5× Biotech Tth Plus reaction buffer, containing 670 mm Tris-HCl (pH 8.8), 166 mm (NH4) 2 SO 4 , 4.5% Triton X-100 and 2 mg/mL gelatin, 2 mm dNTPs (dCTP labelled with α 32P), 3 mm MgCl2, 16 pmol of each primer, 0.02 U Biotech Tth Plus Polymerase; and ddH20 to a volume of 20 mL. PCR cycles were as follows: 1 min at 94 °C, 1 min at annealing temperature (see Table 1) and 2 min at 72 °C,
for 33 cycles with a 10-min extension at 72 °C. PCR products were electrophoresed through a 5% denaturing polyacrylamide sequencing gel, the gel dried and exposed to autoradiography film. Table 1 presents details of allelic diversity and hetero-zygosity estimates in seven loci in representatives of six wild and two cultured redclaw populations. Null alleles were detected at loci CQU.001, CQU.002, CQU.004 in two of the six wild stocks. Cross-species amplification of microsatellite loci has been reported in many closely related species (Moore et al. 1991; Laurent et al. 1995; and FitzSimmons et al. 1995). Limited cross-amplification using the redclaw microsatellite primers was achieved in a closely related Cherax species. Ten C. destructor individuals exhibited polymorphic alleles at the CQU.001 and CQU.007 loci when the annealing temperature was lowered by 5 °C. These trials demonstrate the utility of the seven redclaw microsatellite loci for characterizing levels and patterns of genetic diversity in both wild and cultured stocks. Significant cost benefits may also be achieved if cross-amplification of redclaw loci proves successful in related species of Cherax, a number of which are also important culture species (C. destructor and C. tenuimanus) in Australia. Acknowledgements We would like to thank all those who helped with sample collection: Clive Jones QDPI, Peter Hurley, John Short and Peter Davies at the Queensland Museum. Special thanks for advice and technical assistance from Vicki Whan and all at the Gerhman Labs, CSIRO. This work was funded by a research grant from the Australian Centre for International Agricultural Research (ACIAR-Grant No. Fis/96/165). References Austin C (1996) Systematics of the freshwater crayfish genus Cherax in northern and eastern Australia: electrophoretic and morphological variation. Australian Journal of Zoology, 44, 259–296. Busack C (1988) Electrophoretic variation in the red swamp and white river crayfish. Aquaculture, 69, 211–126. FitzSimmons NN, Moritz C, Moore SS (1995) Conservation and dynamics of microsatellite loci over 300 million years of marine turtle evolution. Molecular Biology and Evolution, 12 (3), 432–440. Hughes CR, Queller DC (1993) Detection of highly polymorphic microsatellite loci in a species with little allozyme polymorphism. Molecular Ecology, 2, 131–137. Laurent P, Amigues Y, Lepingle A, Berthier J, Bensaid A, Vaiman D (1995) Sequence conservation of microsatellites between Bos taurus (cattle) and Capra hircus (goat) and related species: Examples of use in parentage testing and phylogeny analysis. Heredity, 74 (1), 53–61. Macaranas JM, Mather PB, Hoeben P, Capra MF (1995) Allozyme and RAPD-DNA variation in the redclaw crayfish. Australian Journal of Marine and Freshwater Research, 46, 1217–1228. Medley P, Jones C, Avault J (1994) A global perspective of the culture of Australian redclaw crayfish, Cherax quadricarinatus: production, economics and marketing. World Aquaculture, 25 (4), 6–13. Moore SS, Sargeant LL, King TJ, Mattick JS, Georges M, Hetzel JS (1991) The conservation of dinucleotide microsatellites among mammalian genomes allows the use of heterologous PCR primer pairs in closely related species. Genomics, 10, 654–660. 9 no no. 2000 866 primer note primer issuenote 1 4 Graphicraft Limited, Hong Kong
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Table 1 Microsatellite loci in the redclaw crayfish, Cherax quadricarinatus
Baker, N., Byrne, K., Moore, S., & Mather, P. 2000. Characterization of microsatellite loci in the redclaw crayfish, Cherax quadricarinatus. Molecular Ecology, 9(4): 494-495
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