Post on 31-May-2020
ABIC 2008 Cork Ireland
Prunet PatrickINRA-SCRIBE, IFR 140, Equipe
Physiologie du stress et de l’adaptation,Rennes cedex.
Argicultural Biotechnology International Conference 2008 (ABIC)Cork, Ireland
Genomic in fish and shellfish: from research toaquaculture
ABIC 2008 Cork Ireland
Aquaculture production
• A continuously growing production (1 million tonnes in 1950; 60millions in 2004 –FAO-).
• Most of the production is from Asia (China: 70%, rest of Asia:22%)
• Western Europe production by value: 7.7%• European species: Atlantic Salmon, rainbow trout, mussels,
oysters, marine species (seabass, seabream…).• 5% of the world production come from managed breeding
programmes (Gjedrem, 2005) (traditional fish breeding and managementlead to degradation of the genetic quality of the stock)
• Domestication: a recent event which involve now more than 430different species and is now very successful (Duarte et al. 2006)
In a context of fisheries catches stagnation, aquaculturecontribute an increasing amount of fish and shellfish food.
ABIC 2008 Cork Ireland
The genome harbours a wealth of information on evolution,development and functioning
Information is useful for fisheries, aquaculture andconservation
Genomic tools have become accessible and affordable,such that whole genome studies are within reach
During the 10 last years, development of a large panel of genomic tools andmethodologies for model fish species (fugu, Tetraodon, zebrafish, medaka)and now aquaculture fish and shellfish species.
This picture is complicated by: the high evolutionary divergences between groups,genome duplication, the number of species available for aquaculture
Genomic resources
sardines, anchoviescarps, goldfish, zebrafish
catfishessalmon, trout
codsmulletsmedakaswordtail
three-spined stickleback
tilapiaEuropean sea bass
seabreamflatfishes
pufferfishes(Fugu, Tetraodon)
advanced stagegenome projects
comparativemapping !
From Volckaert et al., ISAG 2008
• From: « A white paper on genomics in European Aquaculture research » http://genomics.aquaculture-europe.org/
RESOURCES
SPE
CIE
S
Cra
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trea
virg
inic
a
Car
p
Cla
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Ost
rea
edul
is
Cod
Cra
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trea
giga
s
Mus
sel
Sene
gale
seso
le
Seab
ream
Turb
ot
Salm
on
Seab
ass
Trou
t
cDNA library, ESTs sequences 2 2 2 0 2 2 2 2 2 2 2 2 2Microarray, gene expression 2 0 0 0 2 2 2 2 2 2 2 2 2Genetic, linkage map 2 0 0 2 2 2 2 2 2 2 2 2 2Bioinformatics database 0 2 0 0 2 2 2 2 2 2 2 2 2BAC library 2 2 0 0 2 2 0 0 2 1 2 2 2SNP marker 2 0 0 0 2 2 0 0 2 2 2 2 2Microsatellite marker 2 0 2 2 0 0 0 0 2 2 2 2 2Bioinformatics tool 0 0 0 0 0 0 2 2 2 0 2 2 2Bioinformatic service 0 0 0 0 0 2 2 2 0 0 2 2 2QTL detection 0 0 0 0 0 0 0 0 0 2 2 2 2QTL map 0 0 0 0 0 0 0 0 0 2 2 2 2AFLP marker 0 0 0 2 0 0 0 0 0 2 0 2 2Candidate genes marker 0 0 0 0 0 0 2 0 0 2 0 2 2Physical map 0 0 0 0 0 0 0 0 0 0 2 2 2Special genetic background 0 0 0 0 0 2 0 0 0 0 0 2 2Radiation Hybrid Panel 0 0 0 0 0 0 0 0 2 0 0 2 0Segregating families 0 0 0 0 0 0 0 0 2 2 0 0 0Radiation hybrid map 0 0 0 0 0 0 0 0 2 0 0 0 0Transgenic lines 0 0 0 0 0 0 0 0 0 0 0 0 2Complete genome sequence 0 0 0 0 0 0 0 0 0 0 1 1 1Physical/genetic maps integration 0 0 0 0 0 0 0 0 0 0 0 0 1Microarray, genotyping (SNP) 0 0 0 0 0 0 0 0 0 0 0 0 0
Genomic resources available in important aquaculture species
ABIC 2008 Cork Ireland
Near future expectations in genomic tools and resources
• Whole genome sequences for new species (salmonid,cod, oyster…).
• Gene annotation: a necessary improvement.• Resources center: a need for an European action.• High throughout phenotype recording.• Scoring genetic diversity of species selected for
aquaculture and for wild population (impact of selectionand domestication).
AQUAGENOME project
During the 10 last years, several large research projects on fishgenetic/physiology/biology involving genomic approaches led to a large setof new genomic information.
Concertation Action on application of genomics to aquaculture(European Commission, 6th Framework Program):
AQUAGENOME project
Objectives: (1) Coordinate the ongoing and future national andinternational research projects (2) Foster the application of fundamentalresearch results to aquaculture industry.
Expected outputs:• Bring together research groups in the field of aquaculture genomicsfor exchanges of knowledges, resources, methodologies.• Critical appreciation of achievements in genomic research andidentification of further research needs to support industrial exploitation• Transfer of the knowledge to the European aquaculture productionsector.
Advancement of the project see:http://genomics.aquaculture-europe.org/
Major achievements: Inventory of the genomic resources on fish and shellfish within Europe. A White Paper on genomics in European aquaculture research:
Host-pathogen interaction, reproduction and breeding programmes, nutrition impact ongrowth, development and product quality, aquaculture-environment interaction,genomic tools and bioinformatic resources.
An industry-led collaborative roadmap to strengthen Europeanaquaculture through the application of genomics.
From a ‘Roadmaping Workshop’ (London, June 2008), several important themesemerged:
• Opportunities for ‘quick win’ through collaborative networking betweenresearch and industry.
• Aligning research to the needs of industry.• Effective networking and coordination between organisations and projects.• Promoters and blockers.
ABIC 2008 Cork Ireland
From functional genomic to genetic: Searchfor genetic factors involved in stress
resistance in rainbow trout.
INRA-SRIBE, Rennes, FranceINRA Laboratory of Fish Genetic, Jouy-en-Josas, France.CEH, University of Lancaster, UK.
ABIC 2008 Cork Ireland
Introduction
• Stress in fish aquaculture: •Adverse effects of chronic stress on fish. •Stressed animals exhibit a decreased immune response. negative impact on fish health, use of antibiotics and drugs in
aquaculture plans
• Genetic variation in sensitivity to stressors: A major determinantof production and welfare for fish aquaculture.
• Within AQUAFIRST project involving several europeanlaboratories, our objectives are:To characterize genetic markers for marker-assisted selective
breeding of disease and/or stress resistant individuals in fishand shellfish.
Identification of QTL (Quantitative Trait Locus = DNA closelylinked to the genes that underlie a specific trait)
ABIC 2008 Cork Ireland
• QTL analysis:The strategy is to relate genetic markers (whatever theirnature: neutral markers or known genes) to the phenotypicvalues of individuals in populations of adequate geneticstructure.
• The originality of the project: association between geneticand genomic approaches.
Functional genomic approaches will provide functionalcandidate genes useful for improving localisation of theQTL.
In the present study developped in trout:(i) characterization of genes involved in the functional
responses to stress exposure.(ii) From functional genomic information, identify new SNP.(iii) identification of QTL related to stress resistance in trout
ABIC 2008 Cork Ireland
Stressed4h, 8h, 24h, 96h, 168h, 504h
non-stressed as controlsreferense
(pool of the controls)
mRNA mRNA
cDNAcDNA cDNA
Statistical analysis for microarray (SAM)Analysis at each time point
Genes that were differentially expressed at at least one time point
Transcriptome analysis of trout interrenal or gill tissuesexposed to confinement stress
Cluster 1
Cluster 2
Cluster 3
Cluster 5
Cluster 4
Results following statistical analysis:255 genes with 89 annotated genes.
StressedControl
ABIC 2008 Cork Ireland
-0.4
-0.2
0
0.2
0.4
0.6
0.8
control_4
h
contro
l_8h
control_24h
control_96
h
control_168h
contro
l_504h
stress_
4h
st ress_
8h
stress_24h
st ress
_96h
st ress
_168h
stress_
504h
log
ratio
Control stressed
4h 8h 24h 98h 168h 504h 4h 8h 24h 98h 168h 504h
Leve
lofe
xpre
ssio
n
Cytochrome c oxydaseGlyceraldehyde-3-phosphate dehydrogenaseCreatine kinase BComplement c3-1Haptoglobine
haptoglobine
-0,15
-0,1
-0,05
0
0,05
0,1
0,15
0,2
0,25
0,3
cont rol_8
h
contro
l_24h
cont r
ol_96h
contro
l_168
h
contro
l_504h
st res
s_8h
s tress
_24h
s tress_
96h
st ress_
168h
s tress_
504h
microarray
PCR Candidate genes forchronic stressindicators
List of genes involved in stress response: Biological functions
Protein turnoverFerritineHaptoglobineProteasome maturation farctor UMP1Ubiquitine specific peptidaseUbiquitine conjugating enzyme
MetabolismeCyt c oxydaseNADH dehydrogenaseNADH-ubiquinone oxidoreductase B17NADH-ubiquinone oxidoreductase B16NADH-ubiquinone oxidoreductase 1Acyl-CoA binding proteinCreatine kinaseSuccinate CoA ligaseFructose 1,6 biphosphateGalactikinaseEnolase
Signal transductionCalmodulineKH domain containingCentaurin-beta 2AnnexineC-SCR-tyrosine kinaseG proteinCentaurinePalmitoyl protein thioesterase
SteroidogenesisSulfotransferase 2BApolipoprotein Eb precursor
Gene expression60S ribosomal L3560S ribosomal L1360S ribosomal L39Histone
Pituitary PeptideGrowth hormonePOMC ASomatolactine
Oxygene transportHemoglonine alpha 1Hemoglonine alpha 4Hemoglonine beta 1Hemoglonine beta 4
Cellular structureClaudin 8CytokeratinFibronectineMyosineCalpaineCollagen alpha 1Collagen alpha 2Collagenase 3Collagenase 4EpendyminDecorinTalin 2
ImmunologyCd209 antigenCCAAT/enhancer binding protein betaCd9 antigenComplement c3 alpha chainComplement c4 precursorComplement c5 precursorGranulins precursorClass 1 histocompatibility antigenClass 2 histocompatibility antigenHLA class 2 histocompatibility antigenH-2 class 2 histocompatibility antigen
OsmoregulationNa/K ATP ase
DetoxificationCyt P450 1A1Cyt P450 1A3
ABIC 2008 Cork Ireland
New genetic markers: SNP (Single Nucleotide Polymorphism)
in stress/disease-sensitive genes:(i) Cheaper and as efficient as microsatellites markers.(ii) SNP are associated with genes physiological functions
linked to traits (stress or disease resistance).(iii) SNP can be used for parental assignement.
Ex. Identification of SNP in candidate genes for stressand disease resistance in trout O.mykiss
The aim was to obtain up to 140 candidate genes with SNPpolymorphism to do genotyping with SNplex method ( multiplex of48 locus)
Difficulties: At the end, once eliminated duplicated loci andmonomorphic ones only 30% of genes are useful for our study.
Despites these difficulties , first Snplex analysis allowed us togenotype 44 locus on the 1200 individuals of the QTL families plus thetwo families of the genetic map. Use of this tool for QTL identification.
Polymorphismanalysis onQTL familiesfor 2 locus
Homozygotes A2
Homozygotes A2
Homozygotes A2
Homozygotes A2
HeterozygotesA1A2
HeterozygotesA1A2
(F. Krieg, E. quilletINRA Jouy)
Trout QTL design
F0
F1
Individus markedFor genotyping
phenotyping Plasma cortisollevels after
confinment stress
Plasma sodium levels after24h salinity stress (30 ‰)
160 individus
F2 5 families (200 fishes each)
parental DNAInformation
1512189717141381011215134162720252620
20
40
60
80
100
120
140
160
LR HR
2 strains of rainbow troutSelected for cortisolresponsiveness toconfinement stress (F2families).Pottinger and Carrick,1999.
Pathogen exposure stress
Pla
sma
cort
iso
llev
el
0.830.740.650.760.72R
S197164221206202Sodium 2
S200173209195185Sodium 1
CommentsX17X14X8X4X3Cross
Results
• For each individual from the 5 families (~900 fish), 2 salinity testswere carried out at 2 weeks interval.
• Statistical analysis of individual plasma Na+ were analysis withineach family.
A significant difference between family was observedThis difference is obtained for the 2 salinity tests.
This indicate the existence of a family effect whichmay be of generic origin: a possible QTL for resistance to salinity.
• Genotyping and phenotyping analysis:
Statistical analysis of plasma Na+ levels in individual fish issued from cross 3and 8 (the most informative families) in relation with genetic markers 1, 2 or 3located on chromosome 14.
A significant difference is observed in individuals having allel 2 (for marker1) or allel 1 (marker 3) .
210.2Paternal Grand Parent2
228.2Maternal Grand Parent1Mk3X8
201.1Maternal Grand Parent2
206.1Paternal Grand Parent1Mk2
209.4Paternal Grand Parent2
199.1Maternal Grand Parent1Mk1X3
Sod2originealleleMarkerCross
Conclusion: Presence of 2 QTL (located on chr. 14) which influenceresistance to salinity stress exposure.
1) New molecular biomarkers for chronic stresssituations: To be validated in aquaculture context (welfare). Increase our knwoledge on physiological roles of these biomarkers.
2) Characterization of the QTL for resistance to salinitystress using candidate functional genes as markers(SNP): In progress. To increase density of the genetic markers in the locus and ourknowledge on the genes involved these traits.
To improve phenotypic analysis using gene expression information(ex. biomarkers for salinity stress)
To use of these new genetic and phenotypic makers for testing newselective breeding programs in aquaculture species.
ConclusionWhat did we get? What perspectives?
ABIC 2008 Cork Ireland
AQUAFIRST Project:INRA-SCRIBE, Rennes, France.Yvan Le BrasJérome MontfortGrégory GuernecIsabelle LeguenSandrine MativetGuenièvre Le Borgne
Acknowledgements
INRA Laboratory of Fish Genetic:Edwige QuilletFrancine KriegNERC CEH, university of Lancaster, UKTom Pottinger
AQUAGENOME Project:Partners:INRA-SCRIBE, Rennes (France), coordination.IMR, Bergen (Norway) CCMAR, Faro (Portugal)Genesis Faraday, Scotland, UK University of Götegorg (Sweden)SYSAAF, Rennes (France) University of Stirling (UK)HCMR, Heraklion, Greece. CSIC, Vigo, SpainVNIRO, Moscow, Russia.+ Aquagenome Associated Partner Network (A2PN)
ABIC 2008 Cork Ireland