ACTAUNIVERSITATIS

UPSALIENSISUPPSALA

2019

Digital Comprehensive Summaries of Uppsala Dissertationsfrom the Faculty of Science and Technology 1822

Genomics of population decline

TOM VAN DER VALK

ISSN 1651-6214ISBN 978-91-513-0684-1urn:nbn:se:uu:diva-384346

Dissertation presented at Uppsala University to be publicly examined in Lindahlsalen,Norbyvägen 18, Uppsala, Friday, 6 September 2019 at 10:00 for the degree of Doctor ofPhilosophy. The examination will be conducted in English. Faculty examiner: Dr AylwynScally (University of Cambridge, Department of genetics).

Abstractvan der Valk, T. 2019. Genomics of population decline. Digital Comprehensive Summariesof Uppsala Dissertations from the Faculty of Science and Technology 1822. 57 pp. Uppsala:Acta Universitatis Upsaliensis. ISBN 978-91-513-0684-1.

With human populations forecasted to grow in the next decades, many mammals face increasinganthropogenic threats. The consequential population declines are a precursor to extinctions, assmall populations are not only more sensitive to stochastic events, but reduction in populationsize is generally also followed by a decrease in genetic diversity, which in turn reduces adaptivepotential and fitness of the population. By using molecular methods I aimed to estimate themagnitude of the genomic consequences as a result of rapid population declines with a focus onthe endangered eastern gorillas. First, I genotyped Grauer’s gorilla (Gorilla beringei graueri)faecal samples, which revealed lower genetic diversity and high differentiation in the peripheralcompared to the central populations, indicating a strong effect of genetic drift and limited geneflow among the small, isolated forest fragments (Chapter 1). Next, by using a target captureapproach I obtained complete mitochondrial genomes from degraded Grauer’s and mountain(Gorilla beringei beringei) gorilla faecal and museum samples (Chapter 2) which showed aloss of mitochondrial diversity within the last century in Grauer’s gorillas, mainly driven by theextinction of peripheral populations (Chapter 3). Genome-wide sequence data from historicalsamples suggests that this loss has also affected the nuclear genome, as modern Grauer’s gorillascarry on average more genetic variants with putatively negative fitness consequences thanhistorically. No significant temporal changes were observed in the closely related mountaingorillas, which might be due to their contrasting demographic history (Chapter 4). I thenswitched study species to the endangered Dryas monkey and find that, despite its possible smallpopulation size, the current Dryas monkey population is genetically diverse with low levels ofinbreeding and as such likely viable in the long-term if appropriate conservation measures aretaken (Chapter 5). Finally, I aimed to estimate the strength of genetic purging across a rangeof mammalian species. This revealed that although genetic purging might be common amongendangered species, it mainly acts on long evolutionary time scales with limited strength duringthe rapid population declines as experienced by many species today (Chapter 6).

Keywords: genetic diversity, minimal-invasive samples, population decline, inbreeding,genetic purging, eastern gorillas, Dryas monkey

Tom van der Valk, Department of Ecology and Genetics, Animal ecology, Norbyvägen 18 D,Uppsala University, SE-752 36 Uppsala, Sweden.

© Tom van der Valk 2019

ISSN 1651-6214ISBN 978-91-513-0684-1urn:nbn:se:uu:diva-384346 (http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-384346)

List of Papers

This thesis is based on the following papers

1. Baas, P., van der Valk T., Vigilant, L., Ngobobo, U., Binyinyi, E., Nishuli R, Caillaud, D. & Guschanski, K. (2018). Population-level assessment of genetic diversity and habitat fragmentation in Critically-Endangered Grauer’s gorillas. American Journal of Physical Anthropology

2. van der Valk, T., Lona Durazo, F., Dalén, L. & Guschanski, K. (2017).

Whole mitochondrial genome capture from faecal samples and museum-preserved specimens. Molecular Ecology Resources

3. van der Valk, T., Sandoval-Castellanos, E., Caillaud, D., Ngobobo, U.,

Binyinyi, E., Nishuli, R., Stoinski, T., Gilissen, E., Sonet, G., Semal, P., Kalthoff, K., Dalén, L. & Guschanski, K. (2018). Significant loss of mi-tochondrial diversity within the last century due to extinction of peripheral populations in eastern gorillas. Scientific Reports

4. van der Valk, T., Díez-del-Molino, D., Marques-Bonet, T., Guschanski,

K. & Dalén, L. (2019). Historical Genomes Reveal the Genomic Conse-quences of Recent Population Decline in Eastern Gorillas. Current Biol-ogy

5. van der Valk, T., Gonda, C., Hart, J., Hart, T., Detwiler, K. & Guschan-

ski, K. (2019). The genome of the endangered dryas monkey provides new insights into the evolutionary history of the vervets. Submitted manuscript

6. van der Valk, T., de Manuel, M., Marques-Bonet, T. & Guschanski, K.

(2019). Genetic purging in mammalian populations. Manuscript

The following papers were written during the course of my doctoral studies but are not part of the present dissertation. 1. van der Meijden, A., Koch, B., van der Valk, T., Vargas-Muñoz, L. J. &

Estrada-Gómez, S. (2017). Target-Specificity in Scorpions; Comparing Lethality of Scorpion Venoms across Arthropods and Vertebrates. Toxins

2. Hooper, R., Brealey, J. C., van der Valk, T., Alberdi, A., Durban, J. W., Fearnbach, H., Robertson K.M., Baird R.W., Bradley Hanson M., Wade P., Gilbert M.T.P., Morin P.A., Wolf J.B.W., Foote A.D. & Guschanski, K. (2018). Host-derived population genomics data provides insights into bacterial and diatom composition of the killer whale skin. Molecular Ecol-ogy

3. van der Valk, T., Vezzi, F., Ormestad, M., Dalén, L. & Guschanski, K.

(2019). Index hopping on the Illumina HiseqX platform and its conse-quences for ancient DNA studies. Molecular Ecology Resources

Contents

1.1| The genetic consequences of population decline in the Anthropocene .... 7 

1.2| Obtaining genetic information from endangered species ......................... 9 

1.3| Research aims......................................................................................... 11 

1.4| The gorillas ............................................................................................ 12 

2.1| Population‐level assessment of genetic diversity and habitat fragmentation in critically endangered Grauer's gorillas (Chapter 1) ......... 17 

2.2| Whole mitochondrial genome capture from faecal samples and museum-preserved specimens (Chapter 2) .................................................. 20 

2.3| Significant loss of mitochondrial diversity within the last century due to extinction of peripheral populations in eastern gorillas (Chapter 3) ....... 24 

2.4| Historical genomes reveal the genomic consequences of recent population decline in eastern gorillas (Chapter 4) ....................................... 28 

2.5| The genome of the endangered Dryas monkey provides new insights into the evolutionary history of vervets (Chapter 5).................................... 31 

2.6| Genetic purging in mammalian populations (Chapter 6) ...................... 35 

3| Conclusions ............................................................................................... 39 

4| Future perspectives.................................................................................... 41 

5| Svensk sammanfattning ............................................................................ 46 

6| Acknowledgments ..................................................................................... 48 

7| Bibliography .............................................................................................. 49 

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1.1| The genetic consequences of population decline in the Anthropocene

Anthropogenic impacts on the Earth’s ecosystems are now so prominent that our current time period is defined by some as a new, human dominated, geo-logical epoch: the Anthropocene (Lewis and Maslin, 2015). Although the magnitude of human-driven species extinctions is debated, even under a con-servative scenario, current extinction rates are far above usual background levels and as such the Anthropocene can be considered the planet’s sixth mass extinction event (Ceballos et al., 2015; Ceballos, Ehrlich and Dirzo, 2017). Decades ago, scientists already warned for the disastrous effects of human pressures on wildlife, arguing for the urgent implementation of strict conser-vation actions (McVay, 1973; Myers, 1990). Nonetheless, many animals face ever increasing threats from urban, industrial and agricultural development in their natural habitats (Ceballos et al., 2015; Ceballos, Ehrlich and Dirzo, 2017). The resulting population declines are a precursor to extinctions, as not only are small populations more sensitive to stochastic events such as disease outbreaks or extreme climatic events, reduction in population size is generally followed by a decrease in genetic diversity (Frankham, 1996). Populations with lower genetic diversity have reduced adaptive potential to changing en-vironment (Lande and Shannon, 1996), often display lower fertility (Reed and Frankham, 2003) and are more prone to infectious diseases (Smith, Sax and Lafferty, 2006). In addition, mating between closely related individuals (in-breeding) is expected to increase when the number of individuals within a population becomes small. This can result in inbreeding depression, the re-duction of fitness because of lower survival, mating success, and/or reproduc-tion in the offspring of related individuals compared to those of unrelated in-dividuals (Hedrick and Kalinowski, 2000). In turn, the negative fitness conse-quences of reduced genetic diversity can accelerate population decline, further increasing inbreeding depression and ultimately resulting in an “extinction vortex” (Fagan and Holmes, 2005).

However, despite broad theoretical and empirical support for the negative genetic consequences of population declines (Keller and Waller, 2002; Charlesworth and Willis, 2009), many animals have survived for thousands of generations at small population size, without apparent strong effects on fit-ness. One suggested explanation for the long-term persistence of these popu-lations is genetic purging; the increased efficiency of purifying selection that

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removes deleterious recessive alleles facilitated by inbreeding (Hedrick, 1994). Whereas in large populations deleterious recessive alleles are most of-ten found at low frequency, such alleles can drift to a higher frequency in small populations. Mating between related individuals subsequently increases the likelihood that recessive deleterious alleles end up in homozygous state, thereby becoming subjected to purifying selection (Charlesworth and Willis, 2009). The interplay between demographic change, selection, drift and in-breeding might thus over time result in the removal of recessive deleterious alleles from small populations, and as such facilitate “adaptation” to small population size. Strong genetic purging has been described in, among others, the Channel Island foxes (Robinson et al., 2018), mountain gorillas (Xue et al., 2015), ibex (Grossen et al., 2019) and Apennine brown bears (Cornetti et al., 2017). However, the deleterious genomic consequences and extend of purging during population declines in the Anthropocene remain largely un-known due to limited empirical data (Díez-del-Molino et al., 2017).

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1.2| Obtaining genetic information from endangered species

Given the wealth of demographic and ecological information that can be de-duced from genetic data it is evident that genomics can play an important role in the protection of biodiversity and conservation research. However, despite some conservation success stories that relied on genetics such as the Florida panther population increase and the detection of illegal harvesting and trade (Manel, Berthier and Luikart, 2002; US Fish and Wildlife services, 2008; Wasser et al., 2018), genomics is not yet widely used in conservation plan-ning. This is partly due to the difficulties of translating genomic data into prac-tical conservation planning and to the fact that solving the most pressing con-servation issues requires immediate political actions rather than genomic data (Fyumagwa et al., 2013; Ripple et al., 2014; Shafer et al., 2015; Britt et al., 2018; Kardos and Shafer, 2018). In addition, an overlooked challenge for the application of genomic tools to ecology and conservation research is the pos-sibility of obtaining DNA for the species of interest. High quality samples (e.g. fresh blood or tissue) are ideal from the analysis standpoint, but in most cases acquiring such samples is not possible as the species of interest are rare, en-dangered, occur in challenging habitats, and invasive sampling is ethically un-desired (Taberlet and Waits, 1998). Current genomic studies of endangered animals are therefore often based on samples obtained from captive individu-als. Such samples can yield a wealth of information about the demographic history of a species (e.g. Locke et al., 2011; Scally et al., 2012), but do not always provide an accurate representation of the wild population. Specific breeding practices (e.g. hybridization between divergent populations) can ob-scure demographic inferences, change the social structure or result in “adap-tations to captivity” (Snyder et al., 1996; Araki, Cooper and Blouin, 2007; Christie et al., 2012). In addition, the exact geographical origins of captive individuals are often unknown, making it challenging to obtain accurate infer-ences about substructure and relationships between populations. In rare cases, high quality genomic data can be obtained from wild-born individuals of en-dangered species, often by sampling during medical treatment, post-mortem or using biopsy darts (Prado-Martinez et al., 2013; Xue et al., 2015; Abascal et al., 2016; Foote et al., 2016; Nater et al., 2017; Tunstall et al., 2018). How-ever, such studies rely on opportunistic sampling, and therefore the study de-sign is usually not optimal (Fünfstück et al., 2015) and sample collection can

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take a long time. For instance, the collection of blood samples from the en-dangered mountain gorillas took several years (Xue et al., 2015). With the nowadays low cost of DNA sequencing, sample availability rather than DNA sequencing has become the main bottleneck for most genomic studies.

The limitations of access to high quality samples were already recognized in the early days of conservation genetics (Taberlet and Bouvet, 1992). As means to overcome this constrain, much work has been done on optimizing the DNA yield and quality obtained from minimal-invasive sample sources such as faeces, hair, saliva, feathers and urine (in addition, museum-preserved specimens might also be considered minimal-invasive as they do not pose ad-ditional pressure for current wild-populations, however, many of these sam-ples are from poached individuals, and at one point in time were thus ex-tremely invasive). The first genetic information from minimal-invasive sam-ples was obtained by Taberlet & Bouvet 1992 and Höss et al. 1992, who used snagged hair and faecal samples from brown bears to amplify and sequence mitochondrial DNA. Shortly after, using similar PCR-based approaches, mi-tochondrial sequences were obtained from a wild chimpanzee population to study their social structure (Martin, Dixson and Wickings, 1992) and only a year later, these targeted PCR amplification methods where extended to nu-clear DNA, allowing the determination of the sex of wild individuals from faecal and hair samples (Taberlet et al., 1993). By now, genetic data from minimal-invasive samples has been used for a wide range of applications which include; the detection of rare species, modelling demographic history, estimating genetic diversity and gene flow, detecting population structure and migration events, uncovering social structure, detecting hybrids, monitoring disease episodes, identifying species diet, and wildlife forensics (Schunck, Kraft and Truyen, 1995; Constable et al., 2001; Palomares et al., 2002; Epps et al., 2005; Proctor et al., 2005; Kendall et al., 2009; Lukoschek et al., 2009; De Barba et al., 2014; Steyer et al., 2016; Balasingham et al., 2018). Despite the wealth of information that can be obtained, using minimal-invasive sam-ples remains challenging as they are characterized by low quantities of host DNA, low DNA quality (the DNA is chemical modified, degraded and dam-aged), and presence of enzyme inhibitors which make standard lab protocols unsuitable (Monteiro et al., 1997; Taberlet, Waits and Luikart, 1999). Espe-cially, the large proportion of non-host DNA complicates analyses from min-imal-invasive samples, as it is inherently difficult to target endogenous DNA in a complex mixture of DNA sources.

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1.3| Research aims

The aim of this thesis was two-fold; (i) Use genetic data from minimal-inva-sive samples to study the ecology and demography of endangered species, fo-cusing on the eastern gorillas and (ii) Increase our understanding of the ge-nomic consequences of population declines and small population size in the Anthropocene.

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1.4| The gorillas

In chapters 1-4 of this thesis I focus on the eastern gorillas. Two gorilla species are recognized, the relatively abundant western gorillas (Gorilla gorilla, with an estimated census population size of ~360.000 individuals) and the much rarer eastern gorillas (Gorilla beringei, ~5.000 individuals) (Gray et al., 2013; Plumptre et al., 2016; Strindberg et al., 2018). The two species are allopatric, genetically distinct from each other, and further classified into two subspecies, respectively, in the west of Central Africa the western lowland (Gorilla gorilla gorilla) and Cross-River gorillas (Gorilla gorilla diehli), and in East Africa the Grauer’s (Gorilla beringei graueri) and mountain gorillas (Gorilla ber-ingei beringei) (Figure 1). All gorilla (sub)species experienced population de-cline for at least the last ~100 thousand years, but this decline has been espe-cially pronounced in the eastern species (Figure 2, Xue et al., 2015). In recent times, anthropogenic pressures and disease outbreaks have further reduced the gorilla populations, so that until very recently all four sub-species were clas-sified as critically endangered (IUCN, 2018).

The most famous and intensively studied are the mountain gorillas, en-demic to the mountain ranges of the Virunga Volcanoes and Bwindi Impene-trable National Park in Uganda, Rwanda and the Democratic Republic of Congo (Harcourt and Fossey, 1981). Thanks to intense conservation efforts, the mountain gorillas, which experienced a population low of possibly less than 250 individuals in the 1980s (Harcourt and Fossey, 1981), have now re-covered to ~1000 individuals, and are no longer considered critically endan-gered (IUCN, 2019). Geographically and genetically close to the mountain gorillas are the lesser known and little studied Grauer’s gorillas, the subspe-cies currently facing great anthropogenic threats from poaching, agricultural development and illegal mining operations (Plumptre et al., 2016). Formerly occupying a much larger geographic range, the Grauer’s gorillas lost up to 90% of their population in the last two decades and are nowadays restricted to fragmented forest patches in the eastern parts of the Democratic Republic of Congo (Plumptre et al., 2016).

Despite the availability of genomic data for all (sub)species, the exact de-mographic history of the gorillas remains unclear. Estimates of the divergence times between western and eastern gorillas range from 100kya to over 1.5Mya, depending on the modelled extent and timing of gene flow (Thalmann et al., 2007; Mailund et al., 2012; Scally et al., 2012; Prado-

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Martinez et al., 2013; Xue et al., 2015). A recent estimate using Bayesian co-alescent modelling inferred a divergence time of ~261 kya (McManus et al., 2015), however such models are sensitive to allele frequency estimates, which can be biased due to high levels of inbreeding in the eastern gorillas and small samples size (2 eastern gorilla genomes were used in McManus et al.). By applying a Hidden Markov-Model aimed at identifying “archaic-like” frag-ments without the availability of genomic data from the “archaic” source pop-ulation (Skov et al., 2018) to all published gorilla genomes I observed that ~10% of the eastern gorilla genomes have diverged from the western species possibly up to ~2 million years ago. The other ~90% of the genome suggests a much more recent divergence of ~200kya ago (Figure 3A). Whole-genome Pairwise Markovian Coalescent Analysis (PSMC) also shows that the demo-graphic history of the two species started to markedly differ around 200kya, but in addition suggests that the demographic history of the two species might have been diverging already much earlier (Figure 2). One possible explanation for this pattern would be an ancient split (~1-2Mya) between the two gorilla species with subsequent strong admixture between the two species in more recent times, a similar scenario to what has previously been proposed (Thalmann et al., 2007; Scally et al., 2012). The divergence between the go-rilla subspecies (western – Cross River and mountain – Grauer’s gorilla) is more recent, estimated at ~10-20ky, with possible gene-flow up to very re-cently between the two western subspecies (Thalmann et al., 2011; Roy et al., 2014), although one study estimates a much older western – Cross River split of ~65kya (McManus et al., 2015).

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Figure 1. Geographic distribution and evolutionary relationships of gorilla taxa. (A) Rough approximation of the current gorilla distribution ranges. Note that alt-hough depicted as continuous habitat, the western and Grauer’s gorillas are mostly found in fragmented forest patches (B) Estimates of gorilla (sub)species divergence times obtained from the literature (McManus et al., 2015; Xue et al., 2015). (C) Genome-wide principal component analysis on 44 gorilla genomes. Data was ob-tained from (Prado-Martinez et al., 2013; Xue et al., 2015; Besenbacher et al., 2019) and mapped to a high quality western lowland gorilla reference (Gordon et al., 2016) using bwa mem on default parameters (Li, 2013). SNPs were subsequently identified and filtered following “GATK best-practices” (Van der Auwera et al., 2013) and prin-cipal components on all bi-allelic autosomal SNPs were calculated using smartpca (Patterson, Price and Reich, 2006).

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Figure 2. Inferred effective population size history for the gorillas using PSMC. High-coverage genomes (range 33X – 38X) for two western, two Grauer’s and two mountain gorillas were mapped against the long-read western gorilla assembly (Gordon et al., 2016). PSMC analysis was then run on all autosomes, excluding sites within highly repetitive regions and those below depth 1/3X and above depth 2X of genome-wide coverage. Trajectories between the western and eastern (Grauer’s + mountain) gorillas start diverging 1-2Mya, with the most prominent change starting ~200Kya (using a generation-time of 19.3 years and a mutation rate of 1.25 * 10-8).

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Figure 3. Support for ancient divergence with recent gene flow between the two gorilla species. For each eastern gorilla genome all nucleotide variants not present in any of the western gorillas were identified in non-overlapping windows of 1000 base pairs. SNP calls were obtained as described in Figure 1C, however this time the genomes were mapped to a human reference (hg19) to avoid possible reference bias from using a western gorilla reference (Günther and Nettelblad, 2018). Next, a Hid-den Markov Model aimed at identifying “archaic-like” genomic fragments based on a high density of private nucleotide variants was applied (Skov et al., 2018). Model priors were set corresponding to the divergence of western-eastern of ~1mya, eastern-“archaic” divergence of ~3 mya, with ~5% of the eastern genome being of archaic component. (A) Shows the divergence time estimates between the eastern gorillas and the putatively “archaic” fraction of the eastern genomes (the external fraction) and the divergence between the western and “non-archaic” eastern gorilla genomes (in-ternal fraction) as obtained from the model posteriors (using a mutation rate of 1.25 * 10-8 and a generation time of 19 years). Each dot represents one individual genome. The “archaic” fraction most likely does not represent a distinct lineage but rather an ancient divergence between western and eastern gorillas (B) Shows the posterior es-timate for the timing of gene-flow between the eastern gorillas and putative “archaic” lineage. (C) By summing over all decoded genomic windows an estimated ~10% of the eastern gorilla genomes show a signal of “archaic” admixture (e.g. ancient di-vergence (~2mya) to the western gorilla). (D) The distribution of fragments identified as “archaic” (e.g. ~2 million years divergence to the western gorillas) along chro-mosome 21. Each row represents a chromosome from a single eastern gorilla indi-vidual.

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2.1| Population‐level assessment of genetic diversity and habitat fragmentation in critically endangered Grauer's gorillas (Chapter 1)

The possibility to amplify nuclear DNA from minimal-invasive samples and subsequent improved understanding of microsatellite mutation processes sparked a revolution in conservation genetics in the 1980s (Taberlet et al., 1996). Microsatellites are tracts of repetitive DNA, in which sequences of one or more base pairs are repeated up to hundreds of times. As microsatellites are usually highly polymorphic, Mendelian inherited, noncoding (and thus likely selectively neutral) and abundant in eukaryote genomes they are an ideal ge-netic marker for conservation genetic studies (Taberlet, Waits and Luikart, 1999). Genotyping microsatellites from minimal-invasive samples allows for accurate identification of individuals and their relationship through time and space without having to catch, handle or even observe the animals and as such have been widely used for studying endangered wildlife, including gorillas (Taberlet et al., 1997; Bradley, Chambers and Vigilant, 2001; Guschanski et al., 2008, 2009; Vigilant and Guschanski, 2009; Arandjelovic et al., 2010; Fünfstück and Vigilant, 2015). Due to the political instability in the eastern Democratic Republic of Congo, little is known about substructure, connectiv-ity and diversity of the critically endangered Grauer’s gorillas that are endemic to this region. We are thus lacking crucial information needed for the effective conservation of this species. In chapter 1, I extracted, amplified and geno-typed microsatellite markers from Grauer’s gorilla faecal samples using pre-viously developed methods (Nsubuga et al., 2004; Vallet et al., 2008; Arandjelovic et al., 2009) with the aim to; (i) compare genetic diversity among eastern gorilla populations; (ii) estimate levels of differentiation among Grau-er's gorilla populations and (iii) test if peripheral and central populations of this species differ from each other in genetic diversity.

Results and discussion Nineteen samples from the high‐altitude sector of the Kahuzi-Biega National Park and thirty‐nine samples from the Nkuba Research and Conservation Area in the Walikale territory were genotyped at 13 microsatelite loci (Figure 4A). These samples represented 32 unique individuals, of which 28 identified from

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at least ten genotyped loci. The newly generated genotypes were then comple-mented with previously published data obtained from three additional Grauer’s gorilla populations (the Itombwe Massif Natural Reserve, Mount Tshiaberimu, and Walikale) and a gorilla group that was previously sampled in the high‐altitude sector of the Kahuzi-Biega National Park (Figure 4A) (Roy et al., 2014). I also included a subset of data from two mountain gorilla populations from the Bwindi Impenetrable National Park (Guschanski et al., 2009) and the Virunga Massif (Bradley et al., 2005) and a western lowland gorilla population from Loango National Park (Gabon) (Arandjelovic et al., 2010) for between-species comparisons.

Structure and principal component analysis on the entire dataset (Pritchard, Stephens and Donnelly, 2000; Jombart, 2008) showed a clear genetic distinc-tion between the gorillas species and subspecies, (Figure 4 A-C), corroborat-ing previous finding (Fünfstück and Vigilant, 2015). A principal component analysis for the dataset containing only Grauer's gorillas revealed genetic dis-tinction between the populations of Kahuzi-Biega National Park, Mount Tshi-aberimu and the other populations (Figure 4D). Estimates of heterozygosity, number of unique alleles and allelic richness were significantly higher in the western lowland gorillas compared to the eastern gorillas. I did not observe significant differences in estimates of genetic diversity between the two east-ern subspecies, the mountain and Grauer's gorillas, however, at population level the Bwindi mountain gorillas had a greater mean number of alleles than the two peripheral Grauer's populations; Itombwe and Mount Tshiaberimu. Within Grauer's gorillas, the centrally located population of Nkuba was genet-ically more diverse than the peripheral populations of Itombwe, Mt. Tshi-aberimu, and Kahuzi-Biega. The relative levels of genetic diversity among gorilla taxa found in this study (highest in western lowland gorillas, followed by Grauer's and finally mountain gorillas) are in line with previous work that used different genetic markers ranging from microsatellites to whole genome sequences (Prado-Martinez et al., 2013; Fünfstück and Vigilant, 2015; Xue et al., 2015). Among eastern gorillas, Grauer's gorillas generally show higher values of genetic diversity than the mountain gorillas, however it is especially the central populations of Walikale and particularly Nkuba that are the most genetically diverse.

Chapter 1 demonstrates that compared to mountain gorillas, which are now recovering thanks to dedicated conservation efforts, appreciable genetic diversity is still present in Grauer's gorillas, but it is not evenly distributed across the species range. Specifically, isolated populations are less genetically diverse than those located in the core of the species range, similar to what has been observed in peripheral populations of western lowland gorillas (Fünfstück and Vigilant, 2015). Conservation efforts often prioritize the ge-netically most diverse populations, however, small peripheral populations can be essential for species survival as immigrants from low‐diversity, isolated populations into larger central ones can still introduce novel variants that help

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maintain genetic diversity (Hogg et al., 2006; Åkesson et al., 2016; Chen et al., 2016). Therefore, small, isolated gorilla populations can have an important conservation value despite lower genetic diversity, and restoration of connec-tivity between them and the species' core range might increase conservation success for this species.

Figure 4. Geographic location and genetic population structure of eastern gorillas. (A) The eastern Bwindi and Virunga populations are mountain gorillas, whereas all other depicted populations are Grauer's gorillas. The Loango population of western lowland gorillas from Gabon is not shown. The location of the pie‐charts represents the approximate sampling location, pie‐chart size corresponds to the number of unique individuals sampled, and the colour of the pie‐chart reflects the proportion of the group's genome membership in one of six genetic clusters as inferred using the software structure. (B) Principal component analysis for the complete dataset, show-ing PC1 and PC2 or (C) PC1 and PC3. (D) Principal component analysis only for the Grauer's gorilla populations.

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2.2| Whole mitochondrial genome capture from faecal samples and museum-preserved specimens (Chapter 2)

Although chapter 1 provides new insights into the genetic diversity and pop-ulation structure of the Grauer’s gorillas, the quantification of genetic diver-sity loss resulting from recent population decline requires comparisons be-tween modern and historical samples that predate the causative events. Alt-hough microsatellites amplification from historical samples can be successful if DNA preservation is exceptionally high (e.g. Thalmann, Wegmann, Spitzner, Arandjelovic, Guschanski, Wegmann, et al., 2011), in most cases the degraded DNA of historical samples makes microsatellite markers inac-cessible for direct amplification. In chapter 2 I therefore focus on mitochon-drial genomes, another widely used marker in population genetic studies be-cause of its fast evolutionary rate, adaptive potential and female‐specific in-heritance (Ruiz-Pesini et al., 2004; Duchêne et al., 2011; Gutiérrez et al., 2014; Hofman et al., 2015; Desalle, Schierwater and Hadrys, 2017). In addi-tion, the high copy number per cell and small genome size makes it suitable for sequencing from low‐quality samples. Obtaining mitochondrial genomes from low-quality samples (e.g. faecal and museum specimens) is non-trivial as the DNA in such samples is highly degraded (short DNA fragments), of low quantity (picograms of host DNA), and usually contaminated with envi-ronmental and bacterial DNA. In chapter 2 I aimed to recover complete mi-tochondrial genomes from highly degraded Grauer’s gorilla faecal and mu-seum samples using methods specifically developed for low-quality samples. DNA from museum specimens (powder obtained from teeth and skin frag-ments) was extracted using a DNA extraction protocol designed for the reten-tion of ultra-short DNA fragments (Dabney, Meyer and Pääbo, 2013). The DNA of the faecal samples was extracted using methods specifically aimed at reducing the amount of inhibiting components in the extract (Nsubuga et al., 2004; Vallet et al., 2008). Faecal and historical samples generally contain a complex mixture of DNA, with only a minority coming from the host species, thus shotgun sequencing of these DNA extracts usually does not yield enough sequence data for the inferences of host genetics. I therefore applied a capture-based approach aimed at enriching the DNA extract for endogenous fragment (Maricic, Whitten and Pääbo, 2010). In this method, “baits” are created from

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a high-quality sample (I used a western lowland gorilla blood extract), which are then used to “fish” out endogenous DNA fragments through hybridization. This method circumvents the need for PCR amplification-based sequence analysis (such as microsatellites or mtDNA hypervariable regions), which of-ten cannot be applied to highly degraded samples, as they require the presence of long DNA molecules (e.g. >100 basepairs). In addition, PCR‐based mito-chondrial studies of great apes have been hampered by the high prevalence of mitochondrial DNA-like sequences in the nucleus (numts) (Thalmann et al., 2004). Targeted capture overcomes this problem, due to the greater number of true mitochondrial fragments compared to nucleus‐encoded numts post-cap-ture (Guschanski et al., 2013). Although previously successful on ancient and historical samples, the target capture methods had not been applied to faecal samples prior to my study. Besides sharing damage characteristics with his-torical samples, faecal samples also contain enzyme inhibitors reducing the efficiency of many laboratory protocols. In addition, biases such as preferen-tial retention of specific fragment sizes, reduced capture efficiency of dam-aged molecules and capture performance in the face of closely related con-taminating sequences have not been systematically evaluated for target cap-ture approaches. The aim of chapter 2 was thus twofold: (i) using gorilla mu-seum specimens, to evaluate how targeted enrichment of host-DNA affects the endogenous content, levels of human contamination, read length distribu-tion and prevalence of DNA damage and (ii) investigate if mitochondrial cap-ture is possible from faecal samples and evaluate its performance compared to museum specimens. In addition, although the faecal samples used in this study were collected from three presumed gorilla social groups, one of the groups was later identified as eastern chimpanzees based on recovered mito-chondrial sequences. This initially unintentional inclusion of chimpanzee samples allowed me to also evaluate (iii) the ability to capture mitochondrial genomes from closely related species using a divergent bait (gorilla) and the effects of sequence divergence between target and bait.

Results and discussion By comparing sequence data from the same libraries pre- and post-capture I show that the applied capture method increased the proportion of target se-quences from 0.13 ± 0.04% reads pre-capture to 29.15 ± 3.23% and 40.5 ± 3.78% after one and two capture rounds, respectively (Figure 5A), an increase of over 300‐fold. Genome coverage post-capture was relatively equal across the entire length of the mitochondrial genome, suggesting no pro-nounced regional capture biases. In contrast to previous findings that reported preferential retention of longer fragments after target capture (Enk, Rouillard and Poinar, 2013; Cruz-Dávalos et al., 2016), I observed no change in median read length, but instead reduced retention of both short and long fragments following capture. Capture was also considerably less efficient for contami-

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nating human fragments than for gorilla fragments overall, however the pro-portion of human mitochondrial reads did increase following capture. This shows that human contamination remains a challenge when working with low‐quality (great ape) samples. Applying the target enrichment method to 51 Grauer's gorilla and five eastern chimpanzee faecal samples, over 90% of the mitochondrial genomes was recovered for 80% and 40% of gorilla and chim-panzee samples, respectively. The proportion of on‐target reads did not differ significantly between faecal and museum gorilla samples, suggesting that the capture approach works efficiently for both sample types. Significantly fewer on‐target reads were observed for the chimpanzee faecal samples. While this could be due to significantly lower pre-capture endogenous content of these samples, it is also possible that capture efficiency decreases with increasing genetic distance between bait and sample. Concordantly, I observed a negative correlation between regional genome divergence and coverage, suggesting that regions with higher divergence to the bait were captured less efficiently (Figure 5B,C). Nevertheless, nearly complete mitochondrial genomes from chimpanzee samples were obtained, showing that the applied target enrich-ment method can be successful despite more than eight million years diver-gence between chimpanzees and gorillas (Langergraber et al., 2012).

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Figure 5. Hybridization capture of mitochondrial DNA fragments from faecal and museum-preserved specimens (A) The proportion of mtDNA reads significantly in-creased following one and two capture rounds (*p‐value = <.05, ***p‐value < 10−10). (B) Relative coverage of chimpanzee samples, calculated as the aver-age coverage in 30 base pair sliding windows divided by the average coverage of the whole mitochondrial genome, plotted against the sequence divergence to the western lowland gorilla. Dotted line shows the fitted linear regression (r = −0.31, p‐value < .0001). (C) Same as (B) for gorilla faecal samples (r = −0.15, p < .0001)

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2.3| Significant loss of mitochondrial diversity within the last century due to extinction of peripheral populations in eastern gorillas (Chapter 3)

All four recognized gorilla taxa experienced continued long-term population decline over the last 100,000 years (Xue et al., 2015, Figure 2). However, this decline was particularly pronounced in the eastern species, which is reflected by the low genetic diversity in eastern compared to western gorillas (Kuhlwilm et al., 2016). Surveys on the ground have estimated possibly up to 90% population decline in Grauer’s gorillas in the last two decades due to habitat loss and poaching, and the current population size is possibly less than 4,000 individuals (Plumptre et al., 2016). In contrast, thanks to major interna-tional conservation efforts, the mountain gorilla population of the Virunga Massif has recovered from a population low of ~250 in the early 1980s, to around 1000 individuals today (Kalpers et al., 2003; Gray et al., 2013, Dian Fossey Gorila Fund 2018). Therefore, eastern gorillas (and in particular the Grauer’s gorillas) represent a case of rapid population decline over the last few generations that happened against the backdrop of long-term small popu-lation size. Demographic analyses of gorillas had so far only considered mod-ern samples and therefore have limited power to resolve how genetic diversity has changed in recent time periods. In chapter 3 I used historical museum and modern faecal samples that span the last 110 years, to provide a direct past-to-present comparison of mitochondrial genetic diversity in eastern gorillas. Mitochondrial genomes are well suited for such a comparison, as they can reflect recent demographic changes (Cassidy et al., 2017). Due to the low ef-fective population size of mtDNA (1/4th of the nuclear genome) and high mu-tation rate, nucleotide variants rapidly become fixed through genetic drift, al-lowing the observation of demographic processes, even when the sampling period encompasses only a few generations (Nyström, Angerbjörn and Dalén, 2006; Xenikoudakis et al., 2015). In chapter 2, I obtained a large set of mito-chondrial genomes and this revealed that many of the historical samples con-tained relatively well preserved DNA, likely due to the young age of these samples (~100 years), the area targeted for DNA extraction (bone powder from the inside of the teeth) and extensive surface contamination (sanding and UV decontamination). The preservation levels for many of these samples

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made it possible to obtain (nearly) complete mitochondrial genomes through Illumina shotgun sequencing of the initial DNA extract. Thus the mountain gorilla historical mitochondrial genomes in chapter 3 were obtained through shotgun sequencing rather than applying the hybridisation capture method of chapter 2. Obtained mitochondrial genomes were combined with previously published data from contemporary gorilla populations (Prado-Martinez et al., 2013; Xue et al., 2015), resulting in a set of over 100 gorilla mitochondrial genomes, which were then used to; (i) quantitatively assess how genetic di-versity has changed over the course of a few generations in the eastern gorillas and (ii) evaluate the relative contribution of decline in population size versus local population extinction to genetic diversity of Grauer’s gorillas.

Results and discussion Comparing the eastern gorilla mitochondrial genomes from modern and his-torical samples, a pronounced loss of genetic diversity within the last century was observed in Grauer’s gorillas. Because the historical sampling contained populations from both within and outside of the current known species distri-bution range, it allowed me to assess the relative contribution of population size reduction compared to population loss due to genetic diversity. This is important, as Grauer’s gorillas have not only experienced reduction in popu-lation size and increased fragmentation throughout their range (Plumptre et al., 2016; Molinario et al., 2017), but also face a general range contraction, accompanied by local population extirpation (Maldonado et al., 2012). Alt-hough genetic diversity within the Grauer’s gorilla core distribution range re-mained relatively stable over the time period spanned by our study (~100 years), overall genetic diversity in this species declined significantly as the result of extinction of populations that are outside the current species range. This significant loss of mitochondrial diversity in Grauer’s gorillas over a short time period is alarming, as it likely also holds for autosomal variation (albeit to a lesser extent due to differences in effective population size). A particularly large number of unique mitochondrial haplotypes in peripheral historical populations was observed and multiple unique haplotypes were ob-served within relatively small geographic regions (Figure 6). These patterns are possibly the result of the long-term historical isolation of peripheral pop-ulations, with limited (female) dispersal, which may have allowed multiple unique variants to drift to high frequency.

In the historical mountain gorilla samples only four different haplotypes were present, showing that mitochondrial diversity was already extremely low in the past. Among the modern samples only two unique haplotypes remained. Such low levels of diversity in the datasets made it impossible to derive any statistically meaningful conclusions about genetic temporal changes in the mountain gorillas.

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Although chapter 1 shows that the peripheral Grauer’s gorillas generally have lower diversity than the core population, chapter 3, reveals that periph-eral gorilla populations are nonetheless keepers of unique genetic variants, highlighting their conservation importance (Lawton, 1993; Vucetich and Waite, 2003). Therefore, conservation actions aimed at preserving peripheral populations, improving habitat connectivity and hence facilitating gene flow, could have a disproportionally positive effect on maintaining overall diversity of Grauer’s gorillas.

Finally, demographic modelling (extended Bayesian Skyline plots) on the mitochondrial genomes, suggest that Grauer’s gorillas went through a period of population growth, most likely between 10,000 and 2,500 years ago, and only recently experienced dramatic population decline. This is concordant with previous inferences about Grauer’s gorilla evolutionary history based on morphological analyses, and coincides with the expansion of forest habitat in central Africa during this time period (Barks et al., 2014; Tocheri et al., 2016).

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Figure 6. Haplotype map and haplotype network showing the geographic and genetic placement of haplotypes for historical and modern samples. Each haplo-type is marked by a unique colour. Dashed line in panels A and C designates the currently estimated distribution range of Grauer’s gorillas. Geographic origin of studied mountain gorilla samples is limited to the Virunga Massif, but is presented larger on the map for clarity. (A) Geographic location of all samples and (B) the corresponding mtDNA haplotype network. (C) Geographic location and (D) the corresponding mtDNA haplotype network of modern samples (coloured) and his-torical samples (shown as outlines). Red outlines designate historical samples from locations outside of the current distribution range, where Grauer’s gorillas are extinct today.

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2.4| Historical genomes reveal the genomic consequences of recent population decline in eastern gorillas (Chapter 4)

Chapter 3 revealed a decline in mitochondrial diversity within the last century in the eastern gorillas, however the functional consequences of this decline remained unknown. In chapter 4 I thus aimed to directly quantify genomic changes within the last century in the two eastern gorilla subspecies by ana-lysing genome-wide sequence data generated from the best-preserved histori-cal gorillas specimens and comparing them to present-day (modern) genomes (Prado-Martinez et al., 2013; Xue et al., 2015). By low-depth shotgun se-quencing of historical gorilla specimens (chapter 2 and 3), the specimens with the highest endogenous content and quantity could be identified and se-lected for deep genome sequencing. For seven Grauer’s and four mountain gorilla samples collected between 1910 and 1962 (median: 1923) adequate coverage (3.1X–10.8X) to infer genomic changes through time was obtained.

Results and discussion Estimates of autosomal heterozygosity in the Grauer’s gorillas suggested a decline in genetic diversity in the last century, with modern individuals con-taining on average 20% fewer heterozygous sites than historical individuals. Lower genetic diversity in modern mountain gorillas was also observed, how-ever the difference compared to the historical individuals was small (3%) and not statistically significant. Additional support for reduced diversity in the modern Grauer’s gorilla population was obtained at population level (meas-ured as the total number of variable sites per population). Next, I aimed to infer the effects of the recent population decline on inbreeding levels by iden-tifying tracts of within-individual chromosomal sequence sharing (ROH). Whereas an average of 35.1% and 33.9% of the historical Grauer’s and moun-tain gorilla genomes, respectively, consisted of ROH above 100 kb, this pro-portion increased to 39.2% in modern Grauer’s and to 36.3% in modern moun-tain gorillas. This change is mainly driven by the proportion of the genome contained in very long ROH (2.5–10 Mb), which increased by 24% in modern Grauer’s gorilla genomes (Figures 7A). Such long tracts are likely to arise from mating between closely related individuals less than a few generations

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ago (Kardos et al., 2018) and as such suggest that mating between related in-dividuals might have increased within the last century. The proportion of the genome contained in long ROH also increased in modern mountain gorillas (+6.9%) however the difference with the historical samples was not statisti-cally significant. To test if the population decline and subsequent increase in inbreeding led to an accumulation of deleterious mutations in eastern gorillas, three complementary approaches to characterize genetic load on genome-wide, gene, and protein level were used. A significant increase in frequency of both missense and loss-of-function (LoF) variants in modern Grauer’s go-rillas compared to the historical individuals was found, consistent with a higher genetic load in the modern population (Figure 7B). In contrast, this analysis suggested that the frequency of missense and LoF variants has re-mained stable in the mountain gorillas during the same time period (Figure 8B). Genes affected by LoF mutations with the highest frequency increase in the modern Grauer’s gorillas were enriched for functions related to immunity and methylation, possibly indicating a decline in pathogen resistance.

Overall the Grauer’s gorillas have been more severely affected by popula-tion decline than mountain gorillas, which could be a result of their contrasting demographic histories. In chapter 3, I suggested that Grauer’s gorillas likely went through a period of population growth and range expansion 2,500–10,000 years ago. This demographic expansion may have led not only to a historically higher genetic diversity in Grauer’s compared to mountain gorillas but also to a higher number of low-frequency (de-novo) deleterious mutations in the Grauer’s gorilla population. As Grauer’s gorillas went through a severe population decline of up to 90% in the last 20 years (Plumptre et al., 2016), these deleterious mutations might have increased in frequency, possibly due to increased drift and inbreeding, thus leading to a more pronounced change in genetic load in Grauer’s compared to mountain gorillas. However, the sam-ple size in this study was limited, and Grauer’s gorilla historical samples were not all obtained from the same locations as the modern samples. Thus, the observed difference between the historical and modern Grauer’s gorillas might also be the result of sample specific features or more ancient substruc-ture (and consequently differences in inbreeding and genetic load between isolated populations) rather than recent temporal changes.

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Figure 7. Genomic consequences of population decline in eastern gorillas (A) Cu-mulative proportion of the genomes contained in ROH below the length displayed on the x axis. Thin lines represent individual genomes, whereas thick lines show the pop-ulation averages. Trajectories of modern and historical genomes start diverging at long ROH (>1 Mb) for Grauer’s gorillas, which are expected to arise primarily form recent inbreeding. (B) Ratio of derived alleles between historical and modern ge-nomes at LoF and missense sites. Error bars depict ±1 SD. This ratio is significantly different from 1 in Grauer’s gorillas.

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2.5| The genome of the endangered Dryas monkey provides new insights into the evolutionary history of vervets (Chapter 5)

In Chapter 5 I switch study species to the dryas monkey (Cercopithecus dryas, Figure 8), a cryptic guenon, previously only known from a single small isolated population (Kokolopori) in the Congo River basin. The recent discov-ery of a second geographically distinct population (Lomani, Figure 9A) has led to the elevation of its conservation status from critically endangered to endangered, however the actual population size, distribution range, behaviour, ecology and evolutionary history of the dryas monkey remains unknown (IUCN, 2019). Despite being classified as a Cercopithecus species due to its resembles to the Diana monkey (Colyn, Gautier-Hion and van den Audenaerde, 1991), a previous study based on mitochondrial genomes placed the dryas monkey together with the vervets (genus: Chlorocebus), supporting suggested grouping based on similarities in cranial and dental morphology (Kuroda, Kano and Muhindo, 1985; Guschanski et al., 2013). Thus, even the phylogenetic placement of the dryas monkey is unclear. With possibly less than 250 remaining adult individuals, the dryas monkey is of high-conserva-tion concern, but it’s challenging habitat, cryptic behaviour and the decade-long unstable political situation in the Democratic Republic of Congo have made it extremely challenging to observe and study this primate in the wild (Hart et al., 2019). In such instances, genomic data can possibly provide a wealth of novel conservation-relevant information, not accessible by other means. The goal of this study was twofold: (i) Reconstruct the evolutionary and demographic history of the dryas monkey in relation to that of the vervets and (ii) asses the long-term genetic viability of this species. To this end, the genome of a single male dryas monkey was sequenced to high coverage (33X) and analysed together with previously published vervet monkey genomes (Svardal et al., 2017).

Results and discussion Multiple independent phylogenomic approaches using whole-genome se-quencing data unambiguously support the same tree topology, showing the dryas monkey as a sister species to all other vervets. The dryas monkey di-verged from the common ancestor of all vervets at least 1 million years ago,

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long before the vervet radiation started ca. 590 thousand years ago (Figure 9B). The Y-chromosome-based phylogeny shows the same topology and di-vergence time estimates as the autosomal trees (Figure 9C). This stands in stark contrast to the inferences based on the mitochondrial genomes, which show the dryas monkey (both the modern dryas monkey sample and the type specimen mitochondrial genome) to be nested within the vervet genus Chlorocebus (Guschanski et al., 2013) (Figure 9D). The incongruence be-tween the nuclear and the mitochondrial phylogeny could be explained by an-cient admixture between the vervets and dryas.

The sabaeus-vervets share significantly fewer derived alleles with the dryas monkey than all other vervets. As derived alleles should be approxi-mately equally frequent in all populations under the scenario of incomplete lineage sorting without additional gene flow (Green et al., 2010), such a pat-tern strongly suggest that indeed alleles were exchanged between the dryas monkey and the vervets after sabaeus-vervets diverged from the other vervets. Using model-based approaches, I obtained additional support for gene flow that occurred 590,000 – 360,000 years ago between the common ancestor of the non-sabaeus vervets and the dryas monkey. Bonobo-chimpanzee admix-ture also occurred during the same time-period and both admixture events most likely involved the crossing of the Congo River (Figure 9A), previously thought to be an impenetrable barrier for mammals (Colyn, 1987; Colyn, Gautier-Hion and Verheyen, 1991; Colyn and Deleporte, 2004; Eriksson et al., 2004; Kennis et al., 2011). In addition, the proposed archaic gene-flow from an unknown great-ape lineage into bonobos also occurred during the same time period (Kuhlwilm et al., 2019). As the timing of these events are highly congruent, the fluvial topology of the Congo River and the geology within the Congo basin might have been more dynamic 300,000-500,000 years ago than previously recognised (Beadle, 1981; Stankiewicz and de Wit, 2006).

Principal Pairwise Markovian Coalescent analysis suggest that 100,000 – 300,000 years ago the dryas monkey population was the largest among all vervets, possibly ranging in the tens of thousands of individuals. This is also reflected by the high genetic diversity of the dryas monkey individual. The dryas monkey did not show signs of excessive recent inbreeding, which would manifest itself in a high fraction of the genome contained in long tracts of homozygosity (> 2.5Mb). In addition, genome-wide measures of genetic load, measured as the ratio between LoF or missense and synonymous mutations, did not show an increased genomic burden of deleterious mutations in the dryas monkey compared to the much more abundant and widely distributed vervets. The demographic history and genome-wide measures of genetic di-versity and genetic load of the dryas monkey thus suggest that the population of this endangered primate might be larger than currently recognised and likely has good chances for long-term survival, if appropriate conservation measures are implemented.

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Figure 8. A rare image of the dryas monkey obtained from camera trapping. ©Daniel Alempijevic.

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Figure 9. Phylogeny of the dryas monkey and the vervets. (A) Distribution ranges of the vervets and dryas monkey. The dryas monkey is currently known from two isolated populations: The Kokolopori-Wamba and the Lomami National Park. The sequenced dryas monkey individual was sampled from the Lomami population as indicated by the asterisk. (B) The autosomal consensus phylogeny of the dryas monkey and the vervets. The tree topology is supported by multiple analyses. Red dotted lines depict previously reported admixture events between the different vervet species (Svardal et al., 2017), with the line width corresponding to the relative strength of admixture. Green arrows show the best-supported timing of admixture between the dryas monkey and the vervets, with arrow heads pointing into the most prominent direction of gene flow. (C) Maximum likelihood Y-chromosome phylogeny, calibrated using the rhesus macaque Y-chromosome as outgroup (not shown). (D) Mitochondrial phylogeny based on de-novo assembled and the previously published dryas monkey type-speci-men mitochondrial genomes, rooted with the rhesus macaque (not shown).

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2.6| Genetic purging in mammalian populations (Chapter 6)

Inbreeding depression, the reduction of fitness because of lower survival, mat-ing, and/or reproduction in the offspring of related individuals compared to unrelated individuals is widely observed among inbred populations (Hedrick and Kalinowski, 2000). This decrease in fitness is caused by increased homo-zygosity at loci with deleterious recessive alleles (Charlesworth and Charlesworth, 1999) and can have severe consequences for the long-term sur-vival of populations (O’Grady et al., 2006). However, despite broad theoreti-cal and empirical support for inbreeding depression (Keller and Waller, 2002; Charlesworth and Willis, 2009), many animals have survived for thousands of generations at small effective population sizes, without apparent strong fitness consequences. A suggested explanation for this long-term persistence is ge-netic purging; the increased efficiency of purifying selection facilitated by in-breeding as a result of increased homozygosity of partially recessive deleteri-ous variants (Hedrick, 1994). The interplay between demographic change, se-lection, drift and inbreeding might thus over time result in the removal of re-cessive deleterious alleles from small populations. Evidence for genetic purging has been found in several species; the channel island foxes (Robinson et al., 2018) , mountain gorillas (Xue et al., 2015), ibex (Grossen et al., 2019), and Apennine brown bears (Cornetti et al., 2017), but it remains largely un-known to what extend purging is a dominant evolutionary force in wild pop-ulations. As animal populations throughout the planet are currently experienc-ing anthropogenically-induced declines at unprecedented speeds (Pimm et al., 2014), inbreeding in wild populations is expected to rise. The resulting genetic consequences might thus be an important contributor to the extinction of al-ready struggling species (Frankham, 1995). Identifying under what circum-stances genetic purging can act and how common it is among endangered pop-ulations could therefore aid in increased efficiency of animal conservation. The aim of chapter 6 was thus to better understand to what extent genetic purging is a common evolutionary force in small populations and under what circumstances it can act by estimating the relative genetic load in a range of mammalian species from genomic data.

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Results and discussion Identifying deleterious alleles (and genetic load) from genomic data is chal-lenging, however evolutionary constraints seem to be a remarkable accurate predictors for the fitness consequences of mutations (Cooper and Shendure, 2011). In the first part of chapter 6 I used previously developed software, together with a newly developed pipeline to calculate the number of rejected substitutions (genomic evolutionary rate profiling; GERP-scores) along a ge-nome alignment. Such “rejected” substitutions would have occurred if the el-ement was selectively neutral, but are not observed because the genomic ele-ment has been under strong evolutionary constrains (Davydov et al., 2010). High GERP-scores reflect sites in the genome that have largely remained iden-tical between a set of genomes, in this chapter comprising all major mamma-lian clades.

The GERP-scores I calculated in this study showed a high correlation with those previously published for the human genome (hg19). In addition, the scores were 4-6 times higher within exonic regions, known to be highly con-served in vertebrates (Lindblad-Toh et al., 2011), than within intronic regions and the vast majority of within-species genetic variation is found at low GERP-scores (indicating that these regions are likely nearly-neutral). These results suggest that the calculate GERP-scores indeed reflect to what extent genomic regions have experienced strong purifying selection throughout their evolutionary history. Using these GERP-scores, genetic load was then esti-mated for 670 individuals, comprising 42 mammalian species by identifying the fraction of derived alleles found within highly conserved genomic regions (Figure 10).

Pronounced differences in genetic load between mammalian species was observed. Mammalian species with relatively few derived alleles at putatively deleterious sites had the highest levels of genome-wide inbreeding, i.e. a high proportion of their genome was in complete autozygosity (e.g. snow leopard, tiger, island fox, wolves, cheetah). In contrast, species with large population sizes and low rates of inbreeding had many putatively deleterious alleles (e.g. house mouse, brown rat, Himalayan rat, European rabbit, vervet monkey, ol-ive baboon, rhesus macaque). However, several species that experienced dra-matic recent population declines (e.g. chimpanzee, orang-utan, lions and Ibe-rian lynx) do not show the same strong signal of genetic purging, despite some being highly inbred (e.g. lions and Iberian Lynx). This suggest that although genetic purging can be a prominent evolutionary force in small populations, the purging of deleterious alleles in wild populations mostly occurs over long evolutionary time-frames, whereas changes in levels of inbreeding (and con-sequent increase of deleterious alleles) occur much faster.

Despite some of the genetically diverse populations (e.g house mouse, brown rat, Himalayan rat, European rabbit, vervet monkey, olive baboon, rhesus macaque) carrying a relatively high fraction of putatively deleterious alleles, the majority of these are at such low frequency that they are rarely

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found in a homozygous state. In contrast, while purging can be imagined for the majority of deleterious alleles in some of the highly inbred populations, some deleterious alleles do reach fixation, which could subsequently lead to strong inbreeding depression. This observation is especially worrying for ge-netically diverse populations facing dramatic population declines (e.g. orang-utan, chimpanzee). As genetically diverse mammals generally seem to carry relatively many deleterious alleles, a high proportion of these could reach fix-ation during rapid population declines before being removed by purging, re-sulting in high inbreeding depression in such populations. This also warns against genetic rescue strategies, where a small number of genetically diverse immigrants is introduced into a small population without reducing the overall levels of inbreeding. In such cases, the introduction of new genetic variants can result in short-term increased population fitness (Hedrick et al., 2014), but subsequent inbreeding will likely result in the fixation of a higher number of deleterious alleles than present in the population before the introduction of novel genetic variation.

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Figure 10. Relative genetic load by species. We estimated genetic load as the average GERP-score of the derived allele. A random scatter is added to the individuals within a species for clarity. Several closely related species (Sumatran and Bornean orangutans, gibbons, vervet monkeys, and eastern and western gorillas) are grouped together for clarity (depicted by the asterisks).

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3| Conclusions

With human populations forecasted to continuously grow in the next decades, reaching 10 billion by the year 2050 (United Nations, 2017), wildlife will face ever increasing anthropogenic pressures. Tools that can improve our under-standing of the genetic consequences of these population declines and aid in increased conservation success are thus urgently needed. In chapter 1 I used microsatellite genotypes obtained from Grauer’s gorilla faecal samples, to show how such methods can provide new insights into the genetic diversity and substructure of challenging to study species. This revealed lower genetic diversity and high differentiation in the peripheral compared to the central populations, indicating a strong effect of genetic drift and limited gene flow among the small, isolated forest fragments. In agreement with previous find-ings, all eastern gorillas displayed significantly lower genetic diversity than the western lowland gorillas. This low genetic diversity might negatively im-pact the fitness and future survival of the eastern gorillas, however genetic diversity is strongly influenced by species’ life history and demography. Spe-cies with long-term low genetic diversity may have developed adaptations to mitigate some of the negative effects and it is thus important to distin-guish long-term from short-term genetic processes. Here museum collec-tions can play an essential role, as they frequently span the critical period of the last few hundred years during which human pressures on natural eco-systems increased. However, historical specimens are of low DNA quality and obtaining genetic data from such samples is non-trivial. In chapter 2 I therefore applied methods developed specifically for obtaining genetic data from low quality samples to faecal and museum specimens to show that com-plete mitochondrial genomes can be obtained from these degraded samples, as long as high-quality DNA is available for bait construction. In chapter 3, using the obtained mitochondrial genomes, I found that Grauer’s gorillas lost mitochondrial diversity within the last century, mainly driven by the extinc-tion of peripheral populations. Mountain gorilla mitochondrial diversity was historically already extremely low, resulting in limited statistical power to quantify temporal changes. Although the Grauer’s gorilla peripheral popula-tions generally showed lower genetic diversity (chapter 1), extinct popula-tions from the edge of the former distribution range contained unique genetic variants. This shows that peripheral populations can be important keepers

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of genetic diversity in species with fragmented habitats. In chapter 4, ge-nome-wide sequence data from relatively well preserved 100-year old mu-seum and high-quality modern samples made it possibly to quantify the func-tional consequences of the observed population declines. Modern Grauer’s gorillas carry on average more genetic variants with putatively negative fitness consequences than historical Grauer’s gorillas. In contrast, the mountain go-rillas did not display the same magnitude of change, which might be a result of their specific demographic history. In chapters 1 to 4 I aimed to show how we can use minimal-invasive and museum samples to asses and quantify the genetic structure and consequences of population declines for challenging to study species, but high-quality samples remain necessary for extensive demo-graphic inferences. In chapter 5, using a tissue sample of a male dryas mon-key, a cryptic and little-known endangered primate, I showed that the dryas monkey is a sister species to the vervets. In addition, I found indications for ancient gene flow between the dryas monkey and vervets, long after their ini-tial divergence. The genomic data also suggest that the current dryas monkey population is genetically “healthy” and as such likely viable in the long-term, if appropriate conservation measures are taken.

The loss of genetic diversity and increase of putatively deleterious alleles in Grauer’s gorillas within the last decades can negatively impact their future survival chances, however some species (including the mountain gorillas), show signs of “adaptation” to small population size, resulting from the purg-ing of deleterious genetic variants. The extent of genetic purging and the evo-lutionary time-scale at which it can take place in wild populations is not yet well understood. In chapter 6 I aimed to improve upon our understanding of genetic purging by estimating the genetic load across a range of mammals with different population sizes and demographic histories. This suggested that genetic purging might be relatively common among endangered species, how-ever it mainly acts on long evolutionary time-scales with limited strength dur-ing the rapid population declines experienced by many species today. I also find that, despite genetic purging, many putatively deleterious alleles still reach fixation in small populations. Thus, although genetic purging might mit-igate some negative fitness consequences of small population size, population decline likely results in reduced fitness overall in most instances.

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4| Future perspectives

Ultimately, I hope this thesis (and future genomics studies) will allow us to better preserve biodiversity in a time where wild populations are faced with ever increasing anthropogenic pressures. However, to do so, major challenges are still remaining. In chapters 1-4, minimal-invasive samples are used to es-timate the geographic and temporal differences in genetic diversity of the east-ern gorillas. However, with the exception of a few well-preserved historical specimens, most of these results are based on a limited set of markers (mi-crosatellites and mitochondrial genomes), as it remains extremely challenging to obtain genome wide data from such samples. For the field of genomics to significantly contribute to practical conservation programs, improvements in data quality obtained from minimal-invasive samples and analytical methods that can be applied to such datasets are needed. In recent years, promising developments, especially in the field of targeted enrichment and capture meth-ods, have been made. Using such methods, de Manuel et al. (2016) succeeded in capturing genome-wide markers and the complete chromosome 21 from chimpanzee faecal samples, allowing for the identification of population struc-ture at fine-scale. Snyder-Mackler et al. (2016), succeeded in enriching ba-boon faecal samples for host-DNA by up to 40-fold, making some of these samples accessible to low coverage (<1X) whole-genome shotgun sequenc-ing. Another promising development is the use of fluorescence-activated cell sorting technologies that can separate “host-like cells” from microbial and plant cells before any DNA is extracted. The DNA can then be obtained from the host-cell enriched fraction and subjected to shotgun sequencing, which has already in a few cases resulted in such high endogenous DNA quantities (>30%) that the samples become accessible for unbiased whole genome se-quencing (Orkin et al., 2018).

The developments in genomics from minimal-invasive samples might eventually also help us to better understand the evolutionary history of the gorillas, which despite being studied for decades, remains mysterious. Esti-mates for the timing of divergence between the two gorilla species vary widely based on the modelled extend and timing of gene-flow (e.g. Scally et al., 2012; Xue et al., 2015). In addition, whole-genome data suggest that both eastern gorilla species (Mountain and Grauer’s) have been at small population size throughout most of their history (Figure 2 and Xue et al., 2015), however field based studies show that whereas mountain gorillas have most likely been at a population size of a few hundred individuals throughout their demographic

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history, Grauer’s gorillas numbered until recently in the tens of thousands (Roy et al., 2014; Plumptre et al., 2016). In chapter 3 I found indications for a marked population size increase in the Grauer’s gorilla ~2.5-10 kya (Figure 11A). Taken together, these observation fit a scenario suggested by (Tocheri et al., 2016): Eastern gorillas were isolated on the Virunga-Bwindi mountain ranges after the split from western lowland gorillas, but when the central Af-rican forest started expanding ~20.000 years ago, some gorillas came down the mountains and expanded rapidly into the new available habitat, becoming what is now known as the Grauer’s gorillas. Such a scenario could also explain why Grauer’s gorillas show a larger fraction of their genome in runs of homo-zygosity between 50-500kb than mountain gorillas do (Figure 8A, chapter 4). The additional bottleneck experienced during the (re)colonisation of the cen-tral African forest would have temporarily increased mating between related individuals, and the impact of this is now visible as runs of homozygosity of intermediate length in the modern Grauer’s gorilla genomes. In addition, the currently available genomic data suggest substructure within the Grauer’s go-rilla’s population (Figure 11B), possibly indicating two separate colonisation events of the Central African forest. However, the current sample sizes are to small to asses such structure in detail.

To resolve these outstanding questions, additional genomic data from un-related wild-born individuals is needed to accurately estimate substructure and allele frequencies of the different gorilla subspecies, which is essential for the development of more accurate demographic models. Although historical sam-ples can be extremely useful, only very few of such samples are available and in most cases they yield too little sequencing data to provide the resolution needed (Figure 11C). It is thus methodological developments of protocols for obtaining genome-wide data from minimal-invasive faecal samples, together with novel methods that can account for genetic lineages not present within the dataset (e.g. Browning et al., 2018; Skov et al., 2018) and/or involve mod-elling rare alleles (which are often excluded from demographic analysis due to their high error rates) that most likely will help solve some of the outstand-ing gorilla mysteries.

Finally, reference bias is known to have an impact on divergence and gene-flow estimates as DNA fragments carrying the reference allele will be more likely to map successfully, or receive higher quality scores. Currently, only a high-quality de-novo assembly for a western gorilla female is available (Gordon et al., 2016). Thus ultimately, fine-scale genomic analysis of the gorillas might require de-novo assemblies for all gorilla subspecies.

In contrast to the gorillas, our understanding of the evolutionary history and ecology of the dryas monkey, a guenon species, is in its infancy. Classified as a Cercopithecus, genomic data shows that the dryas is a sister species to the vervets (Chlorocebus) with strong indications of ancient gene flow between dryas and some of the vervet species after their initial separation. However,

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the guenons are known for the high rate of hybridization, with hybrids re-ported between species that have diverged more than 5 million years ago (Moulin et al., 2008; Jong and Butynski, 2011; Detwiler, 2019). It is thus pos-sible that the dryas monkey carries significant genomic legacy from additional hybridisation events with non-vervet guenons. Upon recently, the dryas mon-key was classified as critically endangered, however the finding of a second population has elevated its status to endangered. The genomic data indicates that the population might be much larger than currently recognised, and recent field observations suggest that the species indeed occupies a wider range. Fu-ture field studies and additional dryas monkey and guenon genomes (possibly from minimal-invasive samples) are needed to improve our understanding of the conservation status, demographic history, gene-flow, phylogenetic classi-fication and population genetic structure of the dryas monkey.

Finally, recent genomic studies and chapter 6 suggest that genetic purging might be more common among small populations than previously recognised (e.g. Xue et al., 2015; Benazzo et al., 2017; Robinson et al., 2018). However, the extend of genetic purging and the temporal scale at which such processes take place remain poorly understood and will require many more dedicated studies. Direct quantification of genetic purging is possible using historical and ancient samples (e.g. Rogers and Slatkin, 2017), however for the vast ma-jority of endangered species such samples are not available. A promising fu-ture route to circumvent this limitation and directly observe genetic purging in wild populations on a fine-scale might be by focussing on species that have been introduced onto small islands (and thus consequently stayed at small population size due to the low carrying capacity) within the last centuries. For many of such species, the approximate date of introduction, and thus diver-gence from the “mainland” population, is known. In addition, it is possible to obtain high quality modern samples, minimising possible biases arising from the use of low-quality samples. One example of such a study system are the vervet monkeys, which occur throughout mainland Africa but have also been introduced on the Caribbean island during the colonial times around 500 years ago (Figure 12A) (Dore, 2017). The proportion of the genome in runs of ho-mozygosity of the Caribbean vervets is almost double that of the mainland population, suggesting strong inbreeding after their introduction (Figure 12B). Interestingly, the number of putatively deleterious mutations in the Caribbean populations seems to have decreased (Figure 12C). The purged deleterious variants are enriched for functions related to chemical stimuli involved in sen-sory perceptions of smell (P < 0.001), possibly indicating rapid adaptations to a new habitat and diet. These changes occurred relatively rapidly (e.g. ~50 generations) suggesting that genetic purging might play a prominent role at even short evolutionary time scale in the vervets. Future studies using island versus mainland comparisons might thus help us to better understand the forces driving genetic purging and the time scales on which it occurs.

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To conclude, exciting new technologies, likely revolutionizing the field of minimal-invasive conservation genomics, are currently in development. Ap-plying these methods and convert outcomes into clear examples of genomic-based conservation success stories are needed to better protect the biodiversity on our planet. Ultimately, efficient species conservation will rely on the inte-gration of political, financial, social and scientific approaches, in which I fore-see a prominent role for genomics.

Figure 11. (A) Extended Bayesian skyline plots for Grauer’s gorillas based on complete mitochondrial genomes. Time is presented on the x-axis, the effective fe-male population size, assuming a generation time of 19 years, is shown on the y-axis. Black line shows the estimate of the mean and the coloured area corresponds to the 95% probability density interval. (B) Eastern gorilla whole genome autoso-mal principal component plot, using historical samples (4-8X coverage) and mod-ern genomes (>20X coverage). Principal component analysis suggests substruc-ture in the Grauer’s gorilla subspecies that is present in historical and modern populations. (C) Projected PC analysis of high quality modern (>20X) and low-quality (<0.01X) historical samples. Pseudo-haploid sequences for each historical individual were obtained by randomly selecting a single high-quality base call (Base-Quality ≥30, MapQuality ≥30) at each site covered by at least 1 read, excluding sites within repetitive regions (as identified from the repeatmask tracts) to minimize false bases from spurious mappings. Next, a reference set of high-quality polymorphisms was made from all bi-allelic sites in the modern genomes. The low-coverage samples were than projected onto the pre-calculated PC space using smartpca (Patterson et al. 2006). Historical samples are coloured according to the geographic origin de-picted on their associated museum label. For the majority of historical samples, the species can be identified despite extremely low depth data (note also a museum mis-labelling of one mountain gorilla, here identified as a western gorilla), however fine scale substructure requires much higher coverage (see panel B), which is challenging to obtain for most historical samples.

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Figure 12. Indications for genetic purging in vervets on the Caribbean islands. (A) Distribution range of the vervets. Black dots represent the geographical origin of whole-genome samples obtained from (Svardal et al., 2017). The insert shows ge-nome-wide principal component analysis on all bi-allelic autosomal SNPs of 148 ver-vet genomes. The Caribbean vervets are most closely related to the populations from Gambia and Ghana, known to be a former slave-trading hotspot. (B) Fraction of the genome in ROH nearly doubled in the island populations compared to the Ghana-Gambia mainland population within ~50 generations. (D) Variant effect predictor (McLaren et al., 2016) was used to classify genetic variants into Loss-of-Function, missense and synonymous mutations. The frequency of all such types decreased in the island populations, suggesting that on average the vervets on the Caribbean islands carry fewer deleterious mutations than those on mainland Africa.

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5| Svensk sammanfattning

Då människans populationer förväntas att ständigt växa under de kommande årtiondena och nå 10 miljarder år 2050 (Förenta staterna, 2017) så kommer vilda djur att möta allt större antropogena påtryckningar. Det är därför bråds-kande med verktyg som kan förbättra vår förståelse vad dessa populations-minskningar har för genetisk påverkan samt ge stöd till ökad framgång i be-varandet av dessa djur. I kapitel 1 använde jag mikrosatellit-genotyper er-hållna från avföringsprover från Grauers gorillor för att visa hur denna metod kan ge nya insikter om genetisk diversitet samt populationsstrukturer av svår-studerade arter. Detta visade en lägre genetisk mångfald och en hög differen-tiering i periferin jämfört med de centrala populationerna. Detta indikerar en stark effekt av genetisk drift och begränsat genflöde bland de små isolerade skogsfragmenten. I överensstämmelse med tidigare fynd uppvisade alla öst-liga gorillor signifikant lägre genetisk mångfald än de västliga låglandsgoril-lorna. Denna låga genetiska mångfald kan negativt påverka östliga gorillans livskraft och framtida överlevnad, dock kan den genetiska mångfalden vara ett resultat av artens livshistoria och demografi. Arter med långvarig låg ge-netisk mångfald kan ha utvecklat anpassningar för att mildra några av de ne-gativa effekterna och det är därför viktigt att skilja mellan långvariga och kort-variga genetiska processer. Här kan museisamlingar spela en avgörande roll, eftersom de ofta sträcker sig över den kritiska perioden av de senaste hundra åren då människans påtryckningar på naturens ekosystem ökat. Historiska ex-emplar har dock låg DNA-kvalitet och det är inte trivialt att erhålla genetiska data från sådana prover. I kapitel 2 tillämpade jag därför metoder som speci-fikt utvecklats för att erhålla genetisk data från prover av låg kvalitet, så som avförnings- och museiprover för att visa att fullständiga mitokondriegenom kan erhållas från dessa nedbrutna prover, så länge som högkvalitativt DNA är tillgängligt för beteskonstruktion. I kapitel 3 fann jag med hjälp av de erhållna mitokondriegenomen att Grauers gorillor har förlorat mitokondriell mångfald under det senaste århundradet, främst på grund av utrotning av perifera popu-lationer. Bergsgorillans mitokondriella mångfald var historiskt redan extremt låg, vilket resulterade i begränsad statistisk kraft för att kvantifiera föränd-ringar över tid. Även om Grauers gorillans perifera populationer generellt vi-sade lägre genetisk mångfald (kapitel 1) innehöll utdöda populationer från ut-

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kanten av det tidigare utbredningsområdet unika genetiska varianter. Detta vi-sar att perifera populationer kan vara viktiga hållare av genetisk mångfald för arter med fragmenterade habitat. I kapitel 4 gjorde genomomfattande sekvens-data från relativt välbevarade 100-åriga museiprover och moderna högkvali-tetsprover det möjligt att kvantifiera de funktionella konsekvenserna av de ob-serverade populationsminskningarna. Moderna Grauers gorillor har i genom-snitt mer genetiska varianter med antaget negativa effekter på deras hälsa än historiska Grauers gorillor. Däremot visade bergsgorillorna inte samma för-ändringsform, vilket kan vara ett resultat av deras specifika demografiska historia. I kapitel 1 till 4 försökte jag visa hur vi kan använda minimalt inva-siva prover och museiprover för att fastställa och kvantifiera den genetiska strukturen och följderna av populationsminskningarna för svårstuderade arter, men högkvalitativa prover är fortfarande nödvändiga för att kunna dra omfat-tande demografiska slutsatser. I kapitel 5 visade jag att dryasmarkattan, en skygg och relativt okänd hotad primat, är en systerart till gröna markattan Chlorocebus pygerythrus, med hjälp av ett vävnadsprov av en dryasmarkatte-hane. Dessutom fann jag indikationer på ett historiskt genflöde mellan dryas-markattan och Chlorocebus pygerythrus, långt efter deras initiala separation. Genomiska data tyder också på att den nuvarande dryasmarkattepopulationen är genetiskt "hälsosam" och därav sannolikt livskraftig på lång sikt, om lämp-liga bevarandeåtgärder vidtas. Förlusten av genetisk mångfald och ökning av troligen skadliga alleler hos Grauers gorillor under de senaste decennierna kan negativt påverka deras framtida överlevnadschanser, men vissa arter (inklu-sive bergsgorillorna) visar tecken på "anpassning" till liten populationsstorlek som resultat från utrensning av skadliga genetiska varianter. Graden av gene-tisk utrensning och den evolutionära tidsskala där den kan ske i vilda populat-ioner är ännu inte väl förstådd. I kapitel 6 syftade jag till att förbättra vår för-ståelse av genetisk utrensning genom att uppskatta den genetiska belastningen över ett antal olika däggdjur med olika populationsstorlekar och demografiska historier. Detta föreslog att genetisk utrensning kan vara relativt vanligt bland hotade arter, dock sker det främst över långa evolutionära tidsskalor och har begränsad kapacitet under den snabba populationsminskningen som många arter utsätts för idag. Jag finner också att många antaget skadliga alleler fort-farande når fixering i små populationer trots genetisk utrensning. Således, även om genetisk utrensning kan mildra några av små populationsstorlekars negativa hälsoeffekter så leder populationsminskning sannolikt till en gene-rellt minskad livskraft i de flesta fall.

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6| Acknowledgments

I hope that by the time you read this I have thanked you in person for all the help, support and joy you brought me during the past years. I feel very fortu-nate to have been surrounded by so many supportive and inspiring people throughout my PhD studies. This thesis has been a shared effort of many peo-ple, however I would like to specifically acknowledge Katerina Guschanski. Thank you for letting me be your first PhD-student. Thank you for all the in-spiring scientific and personal discussions. Thank you for your openness to new ideas, guiding me when needed and letting me fly free when needed. Thank you for being critical and supportive. Thank you for all the fun and happiness. And finally, thank you for being such an amazing role model. I realize I have been extremely lucky to have you guiding me through the past years. There hasn’t been a single day I regretted starting my PhD with you.

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7| Bibliography

Abascal, F. et al. (2016) ‘Extreme genomic erosion after recurrent demographic bottlenecks in the highly endangered Iberian lynx.’, Genome biology, 17(1), p. 251. doi: 10.1186/s13059-016-1090-1.

Åkesson, M. et al. (2016) ‘Genetic rescue in a severely inbred wolf population’, Molecular Ecology, 25(19), pp. 4745–4756. doi: 10.1111/mec.13797.

Araki, H., Cooper, B. and Blouin, M. S. (2007) ‘Genetic effects of captive breeding cause a rapid, cumulative fitness decline in the wild.’, Science (New York, N.Y.). American Association for the Advancement of Science, 318(5847), pp. 100–3. doi: 10.1126/science.1145621.

Arandjelovic, M. et al. (2009) ‘Two-step multiplex polymerase chain reaction improves the speed and accuracy of genotyping using DNA from noninvasive and museum samples’, Molecular Ecology Resources, 9(1), pp. 28–36. doi: 10.1111/j.1755-0998.2008.02387.x.

Arandjelovic, M. et al. (2010) ‘Effective non-invasive genetic monitoring of multiple wild western gorilla groups’, Biological Conservation. Elsevier, 143(7), pp. 1780–1791. doi: 10.1016/J.BIOCON.2010.04.030.

Van der Auwera, G. A. et al. (2013) ‘From FastQ Data to High-Confidence Variant Calls: The Genome Analysis Toolkit Best Practices Pipeline’, in Current Protocols in Bioinformatics. Hoboken, NJ, USA: John Wiley & Sons, Inc., pp. 11.10.1-11.10.33. doi: 10.1002/0471250953.bi1110s43.

Balasingham, K. D. et al. (2018) ‘Environmental DNA detection of rare and invasive fish species in two Great Lakes tributaries’, Molecular Ecology. Wiley/Blackwell (10.1111), 27(1), pp. 112–127. doi: 10.1111/mec.14395.

De Barba, M. et al. (2014) ‘DNA metabarcoding multiplexing and validation of data accuracy for diet assessment: application to omnivorous diet’, Molecular Ecology Resources, 14(2), pp. 306–323. doi: 10.1111/1755-0998.12188.

Barks, S. K. et al. (2014) ‘Variable temporoinsular cortex neuroanatomy in primates suggests a bottleneck effect in eastern gorillas’, Journal of Comparative Neurology, 522(4), pp. 844–860. doi: 10.1002/cne.23448.

Beadle, L. (1981) The inland waters of tropical Africa: an introduction to tropical limnology. 2nd editio. London/New York.

Benazzo, A. et al. (2017) ‘Survival and divergence in a small group: The extraordinary genomic history of the endangered Apennine brown bear stragglers’, Proceedings of the National Academy of Sciences, 114(45), pp. E9589–E9597. doi: 10.1073/pnas.1707279114.

Besenbacher, S. et al. (2019) ‘Direct estimation of mutations in great apes reconciles phylogenetic dating’, Nature Ecology & Evolution. Nature Publishing Group, 3(2), pp. 286–292. doi: 10.1038/s41559-018-0778-x.

Bradley, B. J. et al. (2005) ‘Mountain gorilla tug-of-war: Silverbacks have limited control over reproduction in multimale groups’, Proceedings of the National Academy of Sciences, 102(26), pp. 9418–9423. doi: 10.1073/pnas.0502019102.

50

Bradley, B. J., Chambers, K. E. and Vigilant, L. (2001) ‘Accurate DNA-based sex identification of apes using non-invasive samples’, Conservation Genetics, 2, pp. 179–181.

Britt, M. et al. (2018) ‘The importance of non-academic coauthors in bridging the conservation genetics gap’, Biological Conservation. Elsevier, 218, pp. 118–123. doi: 10.1016/J.BIOCON.2017.12.019.

Browning, S. R. et al. (2018) ‘Analysis of Human Sequence Data Reveals Two Pulses of Archaic Denisovan Admixture Two waves of Denisovan admixture detected in East Asians Analysis of Human Sequence Data Reveals Two Pulses of Archaic Denisovan Admixture’, Cell. Elsevier Inc, 173, pp. 53–61. doi: 10.1016/j.cell.2018.02.031.

Cassidy, L. M. et al. (2017) ‘Capturing goats: documenting two hundred years of mitochondrial DNA diversity among goat populations from Britain and Ireland’, Biology Letters, 13(3), p. 20160876. doi: 10.1098/rsbl.2016.0876.

Ceballos, G. et al. (2015) ‘Accelerated modern human-induced species losses: Entering the sixth mass extinction’, Science Advances, 1(5), pp. e1400253–e1400253. doi: 10.1126/sciadv.1400253.

Ceballos, G., Ehrlich, P. R. and Dirzo, R. (2017) ‘Biological annihilation via the ongoing sixth mass extinction signaled by vertebrate population losses and declines’, Proceedings of the National Academy of Sciences. National Academy of Sciences, 114(30), p. 201704949. doi: 10.1073/pnas.1704949114.

Charlesworth, B. and Charlesworth, D. (1999) ‘The genetic basis of inbreeding depression.’, Genetical research, 74(3), pp. 329–40.

Charlesworth, D. and Willis, J. H. (2009) ‘The genetics of inbreeding depression’, Nature Reviews Genetics. Nature Publishing Group, 10(11), pp. 783–796. doi: 10.1038/nrg2664.

Chen, N. et al. (2016) ‘Genomic Consequences of Population Decline in the Endangered Florida Scrub-Jay’, Current Biology. R Foundation for Statistical Computing, 26(21), pp. 2974–2979. doi: 10.1016/j.cub.2016.08.062.

Christie, M. R. et al. (2012) ‘Genetic adaptation to captivity can occur in a single generation.’, Proceedings of the National Academy of Sciences of the United States of America. National Academy of Sciences, 109(1), pp. 238–42. doi: 10.1073/pnas.1111073109.

Colyn, Gautier-Hion, A. and van den Audenaerde, T. (1991) ‘Cercopithecus dryas Schwarz 1932 and C. salongo Thys van den Audenaerde 1977 are the same species with an age-related coat pattern’, Folia Primatologica. Karger Publishers, 56(3), pp. 167–170. doi: 10.1159/000156543.

Colyn, M. (1987) ‘Les primates des forêts ombrophiles de la cuvette du Zaïre: interprétations zoogéographiques des modèles de distribution’, Revue De Zoologie Africaine, 101, pp. 183–196.

Colyn, M. and Deleporte, P. (2004) ‘Biogeographic Analysis of Central African Forest Guenons’, in The Guenons: Diversity and Adaptation in African Monkeys. Boston: Kluwer Academic Publishers, pp. 61–78. doi: 10.1007/0-306-48417-X_6.

Colyn, M., Gautier-Hion, A. and Verheyen, W. (1991) ‘A Re-Appraisal of Palaeoenvironmental History in Central Africa: Evidence for a Major Fluvial Refuge in the Zaire Basin’, Journal of Biogeography, 18(4), p. 403. doi: 10.2307/2845482.

Constable, J. L. et al. (2001) ‘Noninvasive paternity assignment in Gombe chimpanzees.’, Molecular ecology, 10(5), pp. 1279–300.

51

Cooper, G. M. and Shendure, J. (2011) ‘Needles in stacks of needles: finding disease-causal variants in a wealth of genomic data’, Nature Reviews Genetics, 12(9), pp. 628–640. doi: 10.1038/nrg3046.

Cornetti, L. et al. (2017) ‘Survival and divergence in a small group: The extraordinary genomic history of the endangered Apennine brown bear stragglers’, Proceedings of the National Academy of Sciences, 114(45), pp. E9589–E9597. doi: 10.1073/pnas.1707279114.

Cruz-Dávalos, D. I. et al. (2016) ‘Experimental conditions improving in-solution target enrichment for ancient DNA’, Molecular Ecology Resources. doi: 10.1111/1755-0998.12595.

Dabney, J., Meyer, M. and Pääbo, S. (2013) ‘Ancient DNA damage.’, Cold Spring Harbor perspectives in biology. Cold Spring Harbor Laboratory Press, 5(7), p. a012567. doi: 10.1101/cshperspect.a012567.

Davydov, E. V et al. (2010) ‘Identifying a High Fraction of the Human Genome to be under Selective Constraint Using GERP++’, PLoS Comput Biol, 6(12), p. 1001025. doi: 10.1371/journal.pcbi.1001025.

Desalle, R., Schierwater, B. and Hadrys, H. (2017) ‘MtDNA: The small workhorse of evolutionary studies.’, Frontiers in bioscience (Landmark edition), 22(January), pp. 873–887.

Detwiler, K. M. (2019) ‘Mitochondrial DNA Analyses of Cercopithecus Monkeys Reveal a Localized Hybrid Origin for C. mitis doggetti in Gombe National Park, Tanzania’, International Journal of Primatology. Springer US, 40(1), pp. 28–52. doi: 10.1007/s10764-018-0029-7.

Díez-del-Molino, D. et al. (2017) ‘Quantifying Temporal Genomic Erosion in Endangered Species’, Trends in Ecology and Evolution, 27 December.

Dore, K. M. (2017) ‘Vervets in the Caribbean’, in The International Encyclopedia of Primatology. Hoboken, NJ, USA: John Wiley & Sons, Inc., pp. 1–3. doi: 10.1002/9781119179313.wbprim0358.

Duchêne, S. et al. (2011) ‘Mitogenome Phylogenetics: The Impact of Using Single Regions and Partitioning Schemes on Topology, Substitution Rate and Divergence Time Estimation’, PLoS ONE. Edited by S.-O. Kolokotronis. Cambridge, 6(11), p. e27138. doi: 10.1371/journal.pone.0027138.

Enk, J., Rouillard, J.-M. and Poinar, H. (2013) ‘Quantitative PCR as a predictor of aligned ancient DNA read counts following targeted enrichment.’, BioTechniques, 55(6), pp. 300–9. doi: 10.2144/000114114.

Epps, C. W. et al. (2005) ‘Highways block gene flow and cause a rapid decline in genetic diversity of desert bighorn sheep’, Ecology Letters. Wiley/Blackwell (10.1111), 8(10), pp. 1029–1038. doi: 10.1111/j.1461-0248.2005.00804.x.

Eriksson, J. et al. (2004) ‘Rivers influence the population genetic structure of bonobos (Pan paniscus)’, Molecular Ecology, 13(11), pp. 3425–3435. doi: 10.1111/j.1365-294X.2004.02332.x.

Fagan, W. F. and Holmes, E. E. (2005) ‘Quantifying the extinction vortex’, Ecology Letters, 0(0), p. 051109031307004. doi: 10.1111/j.1461-0248.2005.00845.x.

Foote, A. D. et al. (2016) ‘Genome-culture coevolution promotes rapid divergence of killer whale ecotypes’, Nature Communications. Nature Publishing Group, 7, p. 11693. doi: 10.1038/ncomms11693.

Frankham, R. (1995) ‘Inbreeding and Extinction: A Threshold Effect’, Conservation Biology. John Wiley & Sons, Ltd (10.1111), 9(4), pp. 792–799. doi: 10.1046/j.1523-1739.1995.09040792.x.

Frankham, R. (1996) ‘Relationship of Genetic Variation to Population Size in Wildlife’, Conservation Biology. Blackwell Science Inc, 10(6), pp. 1500–1508. doi: 10.1046/j.1523-1739.1996.10061500.x.

52

Fünfstück, T. et al. (2015) ‘The sampling scheme matters: Pan troglodytes troglodytes and P. t . schweinfurthii are characterized by clinal genetic variation rather than a strong subspecies break’, American Journal of Physical Anthropology. Wiley-Blackwell, 156(2), pp. 181–191. doi: 10.1002/ajpa.22638.

Fünfstück, T. and Vigilant, L. (2015) ‘The geographic distribution of genetic diversity within gorillas’, American Journal of Primatology, 77(9), pp. 974–985. doi: 10.1002/ajp.22427.

Fyumagwa, R. et al. (2013) ‘Roads as a threat to the serengeti ecosystem’, Conservation Biology. Wiley/Blackwell (10.1111), 27(5), pp. 1122–1125. doi: 10.1111/cobi.12116.

Gordon, D. et al. (2016) ‘Long-read sequence assembly of the gorilla genome’, Science. American Association for the Advancement of Science, 352(6281), pp. aae0344–aae0344. doi: 10.1126/science.aae0344.

Gray, M. et al. (2013) ‘Genetic census reveals increased but uneven growth of a critically endangered mountain gorilla population’, Biological Conservation, 158, pp. 230–238. doi: 10.1016/j.biocon.2012.09.018.

Green, R. E. et al. (2010) ‘A draft sequence of the Neandertal genome.’, Science (New York, N.Y.), 328(5979), pp. 710–722. doi: 10.1126/science.1188021.

Grossen, C. et al. (2019) ‘Accumulation and purging of deleterious mutations through severe bottlenecks in ibex’, bioRxiv. Cold Spring Harbor Laboratory, p. 605147. doi: 10.1101/605147.

Günther, T. and Nettelblad, C. (2018) ‘The presence and impact of reference bias on population genomic studies of prehistoric human populations’. doi: 10.1101/487983.

Guschanski, K. et al. (2008) ‘Females Shape the Genetic Structure of a Gorilla Population’, Current Biology, 18(22), pp. 1809–1814. doi: 10.1016/j.cub.2008.10.031.

Guschanski, K. et al. (2009) ‘Counting elusive animals: Comparing field and genetic census of the entire mountain gorilla population of Bwindi Impenetrable National Park, Uganda’, Biological Conservation, 142(2), pp. 290–300. doi: 10.1016/j.biocon.2008.10.024.

Guschanski, K. et al. (2013) ‘Next-generation museomics disentangles one of the largest primate radiations’, Systematic Biology, 62(4), pp. 539–554. doi: 10.1093/sysbio/syt018.

Gutiérrez, E. E. et al. (2014) ‘Phylogeography of Marmosa robinsoni : insights into the biogeography of dry forests in northern South America’, Journal of Mammalogy. Oxford University Press, 95(6), pp. 1175–1188. doi: 10.1644/14-MAMM-A-069.

Harcourt, A. H. and Fossey, D. (1981) ‘The Virunga gorillas: decline of an “island” population’, African Journal of Ecology. Blackwell Publishing Ltd, 19(1–2), pp. 83–97. doi: 10.1111/j.1365-2028.1981.tb00654.x.

Hart, J. A. et al. (2019) ‘Cercopithecus dryas. The IUCN Red List of Threatened Species’.

Hedrick, P. W. (1994) ‘Purging inbreeding depression and the probability of extinction: full-sib mating’, Heredity. Nature Publishing Group, 73(4), pp. 363–372. doi: 10.1038/hdy.1994.183.

Hedrick, P. W. et al. (2014) ‘Genetic rescue in Isle Royale wolves: genetic analysis and the collapse of the population’, Conservation Genetics. Springer Netherlands, 15(5), pp. 1111–1121. doi: 10.1007/s10592-014-0604-1.

Hedrick, P. W. and Kalinowski, S. T. (2000) ‘Inbreeding Depression in Conservation Biology’, Annual Review of Ecology and Systematics. Annual Reviews 4139 El

53

Camino Way, P.O. Box 10139, Palo Alto, CA 94303-0139, USA, 31(1), pp. 139–162. doi: 10.1146/annurev.ecolsys.31.1.139.

Hofman, C. A. et al. (2015) ‘Mitochondrial Genomes Suggest Rapid Evolution of Dwarf California Channel Islands Foxes ( Urocyon littoralis)’, PLoS ONE. Edited by R. Shao. Rowman Altamira, p. e0118240. doi: 10.1371/journal.pone.0118240.

Hogg, J. T. et al. (2006) ‘Genetic rescue of an insular population of large mammals’, Proceedings of the Royal Society B: Biological Sciences, 273(1593), pp. 1491–1499. doi: 10.1098/rspb.2006.3477.

Höss, M. et al. (1992) ‘Excrement analysis by PCR’, Nature. Nature Publishing Group, 359(6392), pp. 199–199. doi: 10.1038/359199a0.

IUCN (2019) The IUCN Red List of Threatened Species. Version 2019.1. Jombart, T. (2008) ‘adegenet: a R package for the multivariate analysis of genetic

markers’, Bioinformatics, 24(11), pp. 1403–1405. doi: 10.1093/bioinformatics/btn129.

Jong, Y. A. de and Butynski, T. M. (2011) ‘Three Sykes’s Monkey Cercopithecus mitis × Vervet Monkey Chlorocebus pygerythrus Hybrids in Kenya’, Primate Conservation. Conservation International, 25(1), pp. 43–56. doi: 10.1896/052.025.0109.

Kalpers, J. et al. (2003) ‘Gorillas in the crossfire: population dynamics of the Virunga mountain gorillas over the past three decades’, Oryx, 37(03), pp. 326–337. doi: 10.1017/S0030605303000589.

Kardos, M. et al. (2018) ‘Genomic consequences of intensive inbreeding in an isolated wolf population’, Nature Ecology & Evolution. Nature Publishing Group, 2(1), pp. 124–131. doi: 10.1038/s41559-017-0375-4.

Kardos, M. and Shafer, A. B. A. (2018) ‘The Peril of Gene-Targeted Conservation’, Trends in Ecology & Evolution. Elsevier Current Trends. doi: 10.1016/J.TREE.2018.08.011.

Keller, L. F. and Waller, D. M. (2002) ‘Inbreeding effects in wild populations’, Trends in Ecology and Evolution, pp. 230–241. doi: 10.1016/S0169-5347(02)02489-8.

Kendall, K. C. et al. (2009) ‘Demography and Genetic Structure of a Recovering Grizzly Bear Population’, Journal of Wildlife Management. The Wildlife Society , 73(1), pp. 3–17. doi: 10.2193/2008-330.

Kennis, J. et al. (2011) ‘The impact of the Congo River and its tributaries on the rodent genus Praomys: Speciation origin or range expansion limit?’, Zoological Journal of the Linnean Society. Oxford University Press, 163(3), pp. 983–1002. doi: 10.1111/j.1096-3642.2011.00733.x.

Kuhlwilm, M. et al. (2016) ‘Evolution and demography of the great apes’, Current Opinion in Genetics & Development, 41, pp. 124–129. doi: 10.1016/j.gde.2016.09.005.

Kuhlwilm, M. et al. (2019) ‘Ancient admixture from an extinct ape lineage into bonobos’, Nature Ecology & Evolution. doi: 10.1038/s41559-019-0881-7.

Kuroda, S., Kano, T. and Muhindo, K. (1985) ‘Further information on the new monkey species,Cercopithecus salongo Thys van den Audenaerde, 1977’, Primates. Springer-Verlag, 26(3), pp. 325–333. doi: 10.1007/BF02382406.

Lande, R. and Shannon, S. (1996) ‘The Role of Genetic Variation in Adaptation and Population Persistence in a Changing Environment’, Evolution, 50(1), p. 434. doi: 10.2307/2410812.

Langergraber, K. E. et al. (2012) ‘Generation times in wild chimpanzees and gorillas suggest earlier divergence times in great ape and human evolution’, Proceedings of the National Academy of Sciences. National Academy of Sciences, 109(39), pp. 15716–15721. doi: 10.1073/pnas.1211740109.

54

Lawton, J. H. (1993) ‘Range, population abundance and conservation’, Trends in Ecology and Evolution. Elsevier Current Trends, 8(11), pp. 409–413. doi: 10.1016/0169-5347(93)90043-O.

Lewis, S. L. and Maslin, M. A. (2015) ‘Defining the Anthropocene’, Nature. Nature Research, 519(7542), pp. 171–180. doi: 10.1038/nature14258.

Li, H. (2013) ‘Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM’. doi: arXiv:1303.3997.

Lindblad-Toh, K. et al. (2011) ‘A high-resolution map of human evolutionary constraint using 29 mammals’, Nature, 478(7370), pp. 476–482. doi: 10.1038/nature10530.

Locke, D. P. et al. (2011) ‘Comparative and demographic analysis of orang-utan genomes.’, Nature, 469(7331), pp. 529–533. doi: 10.1038/nature09687.

Lukoschek, V. et al. (2009) ‘High proportion of protected minke whales sold on Japanese markets is due to illegal, unreported or unregulated exploitation’, Animal Conservation, 12(5), pp. 385–395. doi: 10.1111/j.1469-1795.2009.00302.x.

Mailund, T. et al. (2012) ‘A New Isolation with Migration Model along Complete Genomes Infers Very Different Divergence Processes among Closely Related Great Ape Species’, PLoS Genetics. Edited by H. S. Malik. Public Library of Science, 8(12), p. e1003125. doi: 10.1371/journal.pgen.1003125.

Maldonado, O. et al. (2012) Grauer’s Gorillas and Chimpanzees in Eastern Democratic Republic of Congo (Kahuzi-Biega, Maiko, Tayna and Itombwe Landscape): Conservation Action Plan 2012–2022. doi: ISBN: 978-2-8317-1535-3.

Manel, S., Berthier, P. and Luikart, G. (2002) ‘Detecting Wildlife Poaching: Identifying the Origin of Individuals with Bayesian Assignment Tests and Multilocus Genotypes’, Conservation Biology. Wiley/Blackwell (10.1111), 16(3), pp. 650–659. doi: 10.1046/j.1523-1739.2002.00576.x.

de Manuel, M. et al. (2016) ‘Chimpanzee genomic diversity reveals ancient admixture with bonobos’, Science, 354(6311).

Maricic, T., Whitten, M. and Pääbo, S. (2010) ‘Multiplexed DNA Sequence Capture of Mitochondrial Genomes Using PCR Products’, PLoS ONE. Edited by R. C. Fleischer. Public Library of Science, 5(11), p. e14004. doi: 10.1371/journal.pone.0014004.

Martin, R. D. (Robert D. ., Dixson, A. F. and Wickings, E. J. (1992) Paternity in primates : genetic tests and theories : implications of human DNA fingerprinting : 2nd Schultz-Biegert Symposium, Kartause Ittingen, Switzerland, September 16-20, 1991. Karger.

McLaren, W. et al. (2016) ‘The Ensembl Variant Effect Predictor’, Genome Biology. BioMed Central, 17(1), p. 122. doi: 10.1186/s13059-016-0974-4.

McManus, K. F. et al. (2015) ‘Inference of Gorilla Demographic and Selective History from Whole-Genome Sequence Data’, Molecular Biology and Evolution. Cambridge University Press, Cambridge, 32(3), pp. 600–612. doi: 10.1093/molbev/msu394.

McVay, S. (1973) ‘Stalking the Arctic whale.’, American scientist, 61(1), pp. 24–37. Molinario, G. et al. (2017) ‘Quantification of land cover and land use within the rural

complex of the Democratic Republic of Congo’, Environmental Research Letters. IOP Publishing, 12(10), p. 104001. doi: 10.1088/1748-9326/aa8680.

Monteiro, L. et al. (1997) ‘Complex polysaccharides as PCR inhibitors in feces’, Am Soc Microbiol.

Moulin, S. et al. (2008) ‘Phylogenomics of African guenons’, Chromosome Research, 16(5), pp. 783–799. doi: 10.1007/s10577-008-1226-6.

55

Myers, N. (1990) ‘The biodiversity challenge: expanded hot-spots analysis.’, The Environmentalist, 10(4), pp. 243–56.

Nater, A. et al. (2017) ‘Morphometric, Behavioral, and Genomic Evidence for a New Orangutan Species.’, Current biology : CB. Elsevier, 27(22), pp. 3487-3498.e10. doi: 10.1016/j.cub.2017.09.047.

Nsubuga, A. M. et al. (2004) ‘Factors affecting the amount of genomic DNA extracted from ape faeces and the identification of an improved sample storage method’, Molecular Ecology, 13(7), pp. 2089–2094.

Nyström, V., Angerbjörn, A. and Dalén, L. (2006) ‘Genetic consequences of a demographic bottleneck in the Scandinavian arctic fox’, Oikos. Blackwell Publishing Ltd, 114(1), pp. 84–94. doi: 10.1111/j.2006.0030-1299.14701.x.

O’Grady, J. J. et al. (2006) ‘Realistic levels of inbreeding depression strongly affect extinction risk in wild populations’, Biological Conservation, 133(1), pp. 42–51. doi: 10.1016/j.biocon.2006.05.016.

Orkin, J. D. et al. (2018) ‘Unbiased whole genomes from mammalian feces using fluorescence-activated cell sorting’, bioRxiv. Cold Spring Harbor Laboratory, p. 366112. doi: 10.1101/366112.

Palomares, F. et al. (2002) ‘Faecal genetic analysis to determine the presence and distribution of elusive carnivores: design and feasibility for the Iberian lynx.’, Molecular ecology, 11(10), pp. 2171–82.

Patterson, N., Price, A. L. and Reich, D. (2006) ‘Population Structure and Eigenanalysis’, PLoS Genetics. Public Library of Science, 2(12), p. e190. doi: 10.1371/journal.pgen.0020190.

Pimm, S. L. et al. (2014) ‘The biodiversity of species and their rates of extinction, distribution, and protection’, Science, pp. 1246752–1246752. doi: 10.1126/science.1246752.

Plumptre, A. J. et al. (2016) ‘Catastrophic Decline of World’s Largest Primate: 80% Loss of Grauer’s Gorilla (Gorilla beringei graueri) Population Justifies Critically Endangered Status’, PLOS ONE. Edited by A. Margalida. IUCN/SSC Primate Specialist Group, Ministry of Environment, Nature Conservation & Tourism, Institut Congolais pour la Conservation de la Nature & Jane Goodall Institute, 11(10), p. e0162697. doi: 10.1371/journal.pone.0162697.

Prado-Martinez, J. et al. (2013) ‘Great ape genetic diversity and population history’, Nature. Nature Research, 499(7459), pp. 471–475. doi: 10.1038/nature12228.

Pritchard, J. K., Stephens, M. and Donnelly, P. (2000) ‘Inference of Population Structure Using Multilocus Genotype Data’.

Proctor, M. F. et al. (2005) ‘Genetic analysis reveals demographic fragmentation of grizzly bears yielding vulnerably small populations’, Proceedings of the Royal Society B: Biological Sciences, 272(1579), pp. 2409–2416. doi: 10.1098/rspb.2005.3246.

Reed, D. H. and Frankham, R. (2003) ‘Correlation between fitness and genetic diversity’, Conservation Biology. Blackwell Science, Inc., 17(1), pp. 230–237. doi: 10.1046/j.1523-1739.2003.01236.x.

Ripple, W. J. et al. (2014) ‘Status and Ecological Effects of the World’s Largest Carnivores’, Science, 343(6167), pp. 1241484–1241484. doi: 10.1126/science.1241484.

Robinson, J. A. et al. (2018) ‘Purging of Strongly Deleterious Mutations Explains Long-Term Persistence and Absence of Inbreeding Depression in Island Foxes’, Current Biology, 28(21), pp. 3487-3494.e4. doi: 10.1016/j.cub.2018.08.066.

Rogers, R. L. and Slatkin, M. (2017) ‘Excess of genomic defects in a woolly mammoth on Wrangel island’, PLOS Genetics. Edited by G. S. Barsh. Public Library of Science, 13(3), p. e1006601. doi: 10.1371/journal.pgen.1006601.

56

Roy, J. et al. (2014) ‘Recent divergences and size decreases of eastern gorilla populations’, Biology Letters, 10(11), pp. 20140811–20140811. doi: 10.1098/rsbl.2014.0811.

Ruiz-Pesini, E. et al. (2004) ‘Effects of Purifying and Adaptive Selection on Regional Variation in Human mtDNA’, Science, 303(5655).

Scally, A. et al. (2012) ‘Insights into hominid evolution from the gorilla genome sequence’, Nature, 483(7388), pp. 169–175. doi: 10.1038/nature10842.

Schunck, B., Kraft, W. and Truyen, U. (1995) ‘A simple touch-down polymerase chain reaction for the detection of canine parvovirus and feline panleukopenia virus in feces.’, Journal of virological methods, 55(3), pp. 427–33.

Shafer, A. B. A. et al. (2015) ‘Genomics and the challenging translation into conservation practice’, Trends in Ecology and Evolution. Elsevier Current Trends, pp. 78–87. doi: 10.1016/j.tree.2014.11.009.

Skov, L. et al. (2018) ‘Detecting archaic introgression using an unadmixed outgroup’, PLOS Genetics. Edited by F. Racimo. Public Library of Science, 14(9), p. e1007641. doi: 10.1371/journal.pgen.1007641.

Smith, K. F., Sax, D. F. and Lafferty, K. D. (2006) ‘Evidence for the role of infectious disease in species extinction and endangerment’, Conservation Biology, pp. 1349–1357. doi: 10.1111/j.1523-1739.2006.00524.x.

Snyder-Mackler, N. et al. (2016) ‘Efficient Genome-Wide Sequencing and Low-Coverage Pedigree Analysis from Noninvasively Collected Samples’, Genetics, 203(2).

Snyder, N. F. R. et al. (1996) ‘Limitations of Captive Breeding in Endangered Species Recovery’, Conservation Biology. Wiley/Blackwell (10.1111), 10(2), pp. 338–348. doi: 10.1046/j.1523-1739.1996.10020338.x.

Stankiewicz, J. and de Wit, M. J. (2006) ‘A proposed drainage evolution model for Central Africa—Did the Congo flow east?’, Journal of African Earth Sciences. Pergamon, 44(1), pp. 75–84. doi: 10.1016/J.JAFREARSCI.2005.11.008.

Steyer, K. et al. (2016) ‘Large-scale genetic census of an elusive carnivore, the European wildcat (Felis s. silvestris)’, Conservation Genetics. Springer Netherlands, 17(5), pp. 1183–1199. doi: 10.1007/s10592-016-0853-2.

Strindberg, S. et al. (2018) ‘Guns, germs, and trees determine density and distribution of gorillas and chimpanzees in Western Equatorial Africa’, Science Advances. American Association for the Advancement of Science, 4(4), p. eaar2964. doi: 10.1126/sciadv.aar2964.

Svardal, H. et al. (2017) ‘Ancient hybridization and strong adaptation to viruses across African vervet monkey populations’, Nature Genetics. Nature Publishing Group, 49(12), pp. 1705–1713. doi: 10.1038/ng.3980.

Taberlet and Bouvet (1992) ‘Génétique de l’Ours brun des Pyrenees (Ursus arctos): Premiers résultats’, Comptes Rendus de l’Académie Des Sciences, 314, pp. 15–21.

Taberlet, P. et al. (1993) ‘Sexing free-ranging brown bears Ursus arctos using hairs found in the field.’, Molecular ecology, 2(6), pp. 399–403.

Taberlet, P. et al. (1996) ‘Reliable genotyping of samples with very low DNA quantities using PCR.’, Nucleic acids research. Oxford University Press, 24(16), pp. 3189–94.

Taberlet, P. et al. (1997) ‘Noninvasive genetic tracking of the endangered Pyrenean brown bear population.’, Molecular ecology, 6(9), pp. 869–76.

Taberlet, P. and Waits, L. P. (1998) ‘Non-invasive genetic sampling.’, Trends in ecology & evolution. Elsevier, 13(1), pp. 26–7. doi: 10.1016/S0169-5347(97)01276-7.

57

Taberlet, Waits and Luikart (1999) ‘Noninvasive genetic sampling: look before you leap.’, Trends in ecology & evolution, 14(8), pp. 323–327.

Thalmann, O. et al. (2004) ‘Unreliable mtDNA data due to nuclear insertions: A cautionary tale from analysis of humans and other great apes’, Molecular Ecology, 13(2), pp. 321–335. doi: 10.1046/j.1365-294X.2003.02070.x.

Thalmann, O. et al. (2011) ‘Historical sampling reveals dramatic demographic changes in western gorilla populations’, BMC Evolutionary Biology, 11(1), p. 85. doi: 10.1186/1471-2148-11-85.

Thalmann, O. H. et al. (2007) ‘The complex evolutionary history of gorillas: Insights from genomic data’, Molecular Biology and Evolution, 24(1), pp. 146–158. doi: 10.1093/molbev/msl160.

Tocheri, M. W. et al. (2016) ‘The evolutionary origin and population history of the grauer gorilla’, American Journal of Physical Anthropology, pp. S4–S18. doi: 10.1002/ajpa.22900.

Tunstall, T. et al. (2018) ‘Evaluating recovery potential of the northern white rhinoceros from cryopreserved somatic cells.’, Genome research. Cold Spring Harbor Laboratory Press, 28(6), pp. 780–788. doi: 10.1101/gr.227603.117.

United Nations (2017) World Population Prospects: The 2017 Revision | Multimedia Library - United Nations Department of Economic and Social Affairs.

US Fish and Wildlife services (2008) Florida Panther Recovery Plan (Puma concolor coryi), Third Revision.

Vallet, D. et al. (2008) ‘A new 2CTAB/PCI method improves DNA amplification success from faeces of Mediterranean (Barbary macaques) and tropical (lowland gorillas) primates’, Conservation Genetics. Springer Netherlands, 9(3), pp. 677–680. doi: 10.1007/s10592-007-9361-8.

Vigilant, L. and Guschanski, K. (2009) ‘Using genetics to understand the dynamics of wild primate populations’, Primates, 50(2), pp. 105–120. doi: 10.1007/s10329-008-0124-z.

Vucetich, J. A. and Waite, T. A. (2003) ‘Spatial patterns of demography and genetic processes across the species’ range: Null hypotheses for landscape conservation genetics’, Conservation Genetics. Kluwer Academic Publishers, 4(5), pp. 639–645. doi: 10.1023/A:1025671831349.

Wasser, S. K. et al. (2018) ‘Combating transnational organized crime by linking multiple large ivory seizures to the same dealer’, Science Advances. American Association for the Advancement of Science, 4(9), p. eaat0625. doi: 10.1126/sciadv.aat0625.

Xenikoudakis, G. et al. (2015) ‘Consequences of a demographic bottleneck on genetic structure and variation in the Scandinavian brown bear’, Molecular Ecology, 24(13), pp. 3441–3454. doi: 10.1111/mec.13239.

Xue, Y. et al. (2015) ‘Mountain gorilla genomes reveal the impact of long-term population decline and inbreeding.’, Science (New York, N.Y.). NIH Public Access, 348(6231), pp. 242–5. doi: 10.1126/science.aaa3952.

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