Inference of gorilla demographic and selective history from whole-genome sequence data

Modulating vertebrate physiology by genomic fine-tuning of GPCR functions

G protein-coupled receptors (GPCRs) play a crucial role as membrane receptors, facilitating the communication of eukaryotic species with their environment and regulating cellular and organ interactions. Consequently, GPCRs hold immense potential in contributing to adaptation to ecological niches and responding to environmental shifts. Comparative analyses of vertebrate genomes reveal patterns of GPCR gene loss, expansion, and signatures of selection. Integrating these genomic data with insights from functional analyses of gene variants enables the interpretation of genotype-phenotype correlations. This review underscores the involvement of GPCRs in adaptive processes, presenting numerous examples of how alterations in GPCR functionality influence vertebrate physiology or, conversely, how environmental changes impact GPCR functions. The findings demonstrate that modifications in GPCR function contribute to adapting to aquatic, arid, and nocturnal habitats, influencing camouflage strategies, and specializing in particular dietary preferences. Furthermore, the adaptability of GPCR functions provides an effective mechanism in facilitating past, recent, or ongoing adaptations in animal domestication and human evolution and should be considered in therapeutic strategies and drug development.

A whole-genome scan for evidence of recent positive and balancing selection in aye-ayes (Daubentonia madagascariensis) utilizing a well-fit evolutionary baseline model

The aye-aye (Daubentonia madagascariensis) is one of the 25 most endangered primate species in the world, maintaining amongst the lowest genetic diversity of any primate measured to date. Characterizing patterns of genetic variation within aye-aye populations, and the relative influences of neutral and selective processes in shaping that variation, is thus important for future conservation efforts. In this study, we performed the first whole-genome scans for recent positive and balancing selection in the species, utilizing high-coverage population genomic data from newly sequenced individuals. We generated null thresholds for our genomic scans by creating an evolutionarily appropriate baseline model that incorporates the demographic history of this aye-aye population, and identified a small number of candidate genes. Most notably, a suite of genes involved in olfaction - a key trait in these nocturnal primates - were identified as experiencing long-term balancing selection. We also conducted analyses to quantify the expected statistical power to detect positive and balancing selection in this population using site frequency spectrum-based inference methods, once accounting for the potentially confounding contributions of population history, recombination and mutation rate variation, and purifying and background selection. This work, presenting the first high-quality, genome-wide polymorphism data across the functional regions of the aye-aye genome, thus provides important insights into the landscape of episodic selective forces in this highly endangered species.

Complete sequencing of ape genomes

We present haplotype-resolved reference genomes and comparative analyses of six ape species, namely: chimpanzee, bonobo, gorilla, Bornean orangutan, Sumatran orangutan, and siamang. We achieve chromosome-level contiguity with unparalleled sequence accuracy (<1 error in 500,000 base pairs), completely sequencing 215 gapless chromosomes telomere-to-telomere. We resolve challenging regions, such as the major histocompatibility complex and immunoglobulin loci, providing more in-depth evolutionary insights. Comparative analyses, including human, allow us to investigate the evolution and diversity of regions previously uncharacterized or incompletely studied without bias from mapping to the human reference. This includes newly minted gene families within lineage-specific segmental duplications, centromeric DNA, acrocentric chromosomes, and subterminal heterochromatin. This resource should serve as a definitive baseline for all future evolutionary studies of humans and our closest living ape relatives.

Biases in ARG-Based Inference of Historical Population Size in Populations Experiencing Selection

Inferring the demographic history of populations provides fundamental insights into species dynamics and is essential for developing a null model to accurately study selective processes. However, background selection and selective sweeps can produce genomic signatures at linked sites that mimic or mask signals associated with historical population size change. While the theoretical biases introduced by the linked effects of selection have been well established, it is unclear whether ancestral recombination graph (ARG)-based approaches to demographic inference in typical empirical analyses are susceptible to misinference due to these effects. To address this, we developed highly realistic forward simulations of human and Drosophila melanogaster populations, including empirically estimated variability of gene density, mutation rates, recombination rates, purifying, and positive selection, across different historical demographic scenarios, to broadly assess the impact of selection on demographic inference using a genealogy-based approach. Our results indicate that the linked effects of selection minimally impact demographic inference for human populations, although it could cause misinference in populations with similar genome architecture and population parameters experiencing more frequent recurrent sweeps. We found that accurate demographic inference of D. melanogaster populations by ARG-based methods is compromised by the presence of pervasive background selection alone, leading to spurious inferences of recent population expansion, which may be further worsened by recurrent sweeps, depending on the proportion and strength of beneficial mutations. Caution and additional testing with species-specific simulations are needed when inferring population history with non-human populations using ARG-based approaches to avoid misinference due to the linked effects of selection.

Ghosts of extinct apes: genomic insights into African hominid evolution

We are accustomed to regular announcements of new hominin fossils. There are now some 6000 hominin fossils, and up to 31 species. However, where are the announcements of African ape fossils? The answer is that there are almost none. Our knowledge of African ape evolution is based entirely on genomic analyses, which show that extant diversity is very young. This contrasts with the extensive and deep diversity of hominins known from fossils. Does this difference point to low and late diversification of ape lineages, or high rates of extinction? The comparative evolutionary dynamics of African hominids are central to interpreting living ape adaptations, as well as understanding the patterns of hominin evolution and the nature of the last common ancestor.

Ghost admixture in eastern gorillas

Archaic admixture has had a substantial impact on human evolution with multiple events across different clades, including from extinct hominins such as Neanderthals and Denisovans into modern humans. In great apes, archaic admixture has been identified in chimpanzees and bonobos but the possibility of such events has not been explored in other species. Here, we address this question using high-coverage whole-genome sequences from all four extant gorilla subspecies, including six newly sequenced eastern gorillas from previously unsampled geographic regions. Using approximate Bayesian computation with neural networks to model the demographic history of gorillas, we find a signature of admixture from an archaic 'ghost' lineage into the common ancestor of eastern gorillas but not western gorillas. We infer that up to 3% of the genome of these individuals is introgressed from an archaic lineage that diverged more than 3 million years ago from the common ancestor of all extant gorillas. This introgression event took place before the split of mountain and eastern lowland gorillas, probably more than 40 thousand years ago and may have influenced perception of bitter taste in eastern gorillas. When comparing the introgression landscapes of gorillas, humans and bonobos, we find a consistent depletion of introgressed fragments on the X chromosome across these species. However, depletion in protein-coding content is not detectable in eastern gorillas, possibly as a consequence of stronger genetic drift in this species.

Past Connectivity but Recent Inbreeding in Cross River Gorillas Determined Using Whole Genomes from Single Hairs

The critically endangered western gorillas (Gorilla gorilla) are divided into two subspecies: the western lowland (G. g. gorilla) and the Cross River (G. g. diehli) gorilla. Given the difficulty in sampling wild great ape populations and the small estimated size of the Cross River gorilla population, only one whole genome of a Cross River gorilla has been sequenced to date, hindering the study of this subspecies at the population level. In this study, we expand the number of whole genomes available for wild western gorillas, generating 41 new genomes (25 belonging to Cross River gorillas) using single shed hairs collected from gorilla nests. By combining these genomes with publicly available wild gorilla genomes, we confirm that Cross River gorillas form three population clusters. We also found little variation in genome-wide heterozygosity among them. Our analyses reveal long runs of homozygosity (>10 Mb), indicating recent inbreeding in Cross River gorillas. This is similar to that seen in mountain gorillas but with a much more recent bottleneck. We also detect past gene flow between two Cross River sites, Afi Mountain Wildlife Sanctuary and the Mbe Mountains. Furthermore, we observe past allele sharing between Cross River gorillas and the northern western lowland gorilla sites, as well as with the eastern gorilla species. This is the first study using single shed hairs from a wild species for whole genome sequencing to date. Taken together, our results highlight the importance of implementing conservation measures to increase connectivity among Cross River gorilla sites.

Ecology, Not Host Phylogeny, Shapes the Oral Microbiome in Closely Related Species

Host-associated microbiomes are essential for a multitude of biological processes. Placed at the contact zone between external and internal environments, the little-studied oral microbiome has important roles in host physiology and health. Here, we investigate the roles of host evolutionary relationships and ecology in shaping the oral microbiome in three closely related gorilla subspecies (mountain, Grauer's, and western lowland gorillas) using shotgun metagenomics of 46 museum-preserved dental calculus samples. We find that the oral microbiomes of mountain gorillas are functionally and taxonomically distinct from the other two subspecies, despite close evolutionary relationships and geographic proximity with Grauer's gorillas. Grauer's gorillas show intermediate bacterial taxonomic and functional, and dietary profiles. Altitudinal differences in gorilla subspecies ranges appear to explain these patterns, suggesting a close connection between dental calculus microbiomes and the environment, likely mediated through diet. This is further supported by the presence of gorilla subspecies-specific phyllosphere/rhizosphere taxa in the oral microbiome. Mountain gorillas show a high abundance of nitrate-reducing oral taxa, which may promote adaptation to a high-altitude lifestyle by modulating blood pressure. Our results suggest that ecology, rather than evolutionary relationships and geographic distribution, shape the oral microbiome in these closely related species.

African Suid Genomes Provide Insights into the Local Adaptation to Diverse African Environments

African wild suids consist of several endemic species that represent ancient members of the family Suidae and have colonized diverse habitats on the African continent. However, limited genomic resources for African wild suids hinder our understanding of their evolution and genetic diversity. In this study, we assembled high-quality genomes of a common warthog (Phacochoerus africanus), a red river hog (Potamochoerus porcus), as well as an East Asian Diannan small-ear pig (Sus scrofa). Phylogenetic analysis showed that common warthog and red river hog diverged from their common ancestor around the Miocene/Pliocene boundary, putatively predating their entry into Africa. We detected species-specific selective signals associated with sensory perception and interferon signaling pathways in common warthog and red river hog, respectively, which contributed to their local adaptation to savannah and tropical rainforest environments, respectively. The structural variation and evolving signals in genes involved in T-cell immunity, viral infection, and lymphoid development were identified in their ancestral lineage. Our results provide new insights into the evolutionary histories and divergent genetic adaptations of African suids.

The complex Y-chromosomal history of gorillas

Studies of the evolutionary relationships among gorilla populations using autosomal and mitochondrial sequences suggest that male-mediated gene flow may have been important in the past, but data on the Y-chromosomal relationships among the gorilla subspecies are limited. Here, we genotyped blood and noninvasively collected fecal samples from 12 captives and 257 wild male gorillas of known origin representing all four subspecies (Gorilla gorilla gorilla, G. g. diehli, G. beringei beringei, and G. b. graueri) at 10 Y-linked microsatellite loci resulting in 102 unique Y-haplotypes for 224 individuals. We found that western lowland gorilla (G. g. gorilla) haplotypes were consistently more diverse than any other subspecies for all measures of diversity and comprised several genetically distinct groups. However, these did not correspond to geographical proximity and some closely related haplotypes were found several hundred kilometers apart. Similarly, our broad sampling of eastern gorillas revealed that mountain (G. b. beringei) and Grauer's (G. b. graueri) gorilla Y-chromosomal haplotypes did not form distinct clusters. These observations suggest structure in the ancestral population with subsequent mixing of differentiated haplotypes by male dispersal for western lowland gorillas, and postisolation migration or incomplete lineage sorting due to short divergence times for eastern gorillas.

Population Genomics in the Great Apes

The great apes play an important role as model organisms. They are our closest living relatives, allowing us to identify the genetic basis of phenotypic traits that we think of as characteristically human. However, the most significant asset of great apes as model organisms is that they share with humans most of their genetic makeup. This means that we can extend our vast knowledge of the human genome, its genes, and the associated phenotypes to these species. Comparative genomic studies of humans and apes thus reveal how very similar genomes react when exposed to different population genetic regimes. In this way, each species represents a natural experiment, where a genome highly similar to the human one, is differently exposed to the evolutionary forces of demography, population structure, selection, recombination, and admixture/hybridization. The initial sequencing of reference genomes for chimpanzee, orangutan, gorilla, the bonobo, each provided new insights and a second generation of sequencing projects has provided diversity data for all the great apes. In this chapter, we will outline some of the findings that population genomic analysis of great apes has provided, and how comparative studies have helped us understand how the fundamental forces in evolution have contributed to shaping the genomes and the genetic diversity of the great apes.

Divergent Selection and Primary Gene Flow Shape Incipient Speciation of a Riparian Tree on Hawaii Island

A long-standing goal of evolutionary biology is to understand the mechanisms underlying the formation of species. Of particular interest is whether or not speciation can occur in the presence of gene flow and without a period of physical isolation. Here, we investigated this process within Hawaiian Metrosideros, a hypervariable and highly dispersible woody species complex that dominates the Hawaiian Islands in continuous stands. Specifically, we investigated the origin of Metrosideros polymorpha var. newellii (newellii), a riparian ecotype endemic to Hawaii Island that is purportedly derived from the archipelago-wide M. polymorpha var. glaberrima (glaberrima). Disruptive selection across a sharp forest-riparian ecotone contributes to the isolation of these varieties and is a likely driver of newellii's origin. We examined genome-wide variation of 42 trees from Hawaii Island and older islands. Results revealed a split between glaberrima and newellii within the past 0.3-1.2 My. Admixture was extensive between lineages within Hawaii Island and between islands, but introgression from populations on older islands (i.e., secondary gene flow) did not appear to contribute to the emergence of newellii. In contrast, recurrent gene flow (i.e., primary gene flow) between glaberrima and newellii contributed to the formation of genomic islands of elevated absolute and relative divergence. These regions were enriched for genes with regulatory functions as well as for signals of positive selection, especially in newellii, consistent with divergent selection underlying their formation. In sum, our results support riparian newellii as a rare case of incipient ecological speciation with primary gene flow in trees.

Detecting Positive Selection in Populations Using Genetic Data

High-throughput genomic sequencing allows to disentangle the evolutionary forces acting in populations. Among evolutionary forces, positive selection has received a lot of attention because it is related to the adaptation of populations in their environments, both biotic and abiotic. Positive selection, also known as Darwinian selection, occurs when an allele is favored by natural selection. The frequency of the favored allele increases in the population and, due to genetic hitchhiking, neighboring linked variation diminishes, creating so-called selective sweeps. Such a process leaves traces in genomes that can be detected in a future time point. Detecting traces of positive selection in genomes is achieved by searching for signatures introduced by selective sweeps, such as regions of reduced variation, a specific shift of the site frequency spectrum, and particular linkage disequilibrium (LD) patterns in the region. A variety of approaches can be used for detecting selective sweeps, ranging from simple implementations that compute summary statistics to more advanced statistical approaches, e.g., Bayesian approaches, maximum-likelihood-based methods, and machine learning methods. In this chapter, we discuss selective sweep detection methodologies on the basis of their capacity to analyze whole genomes or just subgenomic regions, and on the specific polymorphism patterns they exploit as selective sweep signatures. We also summarize the results of comparisons among five open-source software releases (SweeD, SweepFinder, SweepFinder2, OmegaPlus, and RAiSD) regarding sensitivity, specificity, and execution times. Furthermore, we test and discuss machine learning methods and present a thorough performance analysis. In equilibrium neutral models or mild bottlenecks, most methods are able to detect selective sweeps accurately. Methods and tools that rely on linkage disequilibrium (LD) rather than single SNPs exhibit higher true positive rates than the site frequency spectrum (SFS)-based methods under the model of a single sweep or recurrent hitchhiking. However, their false positive rate is elevated when a misspecified demographic model is used to build the distribution of the statistic under the null hypothesis. Both LD and SFS-based approaches suffer from decreased accuracy on localizing the true target of selection in bottleneck scenarios. Furthermore, we present an extensive analysis of the effects of gene flow on selective sweep detection, a problem that has been understudied in selective sweep literature.

Comparison of the Full Distribution of Fitness Effects of New Amino Acid Mutations Across Great Apes

The distribution of fitness effects (DFE) is central to many questions in evolutionary biology. However, little is known about the differences in DFE between closely related species. We use >9000 coding genes orthologous one-to-one across great apes, gibbons, and macaques to assess the stability of the DFE across great apes. We use the unfolded site frequency spectrum of polymorphic mutations (n = 8 haploid chromosomes per population) to estimate the DFE. We find that the shape of the deleterious DFE is strikingly similar across great apes. We confirm that effective population size (Ne ) is a strong predictor of the strength of negative selection, consistent with the nearly neutral theory. However, we also find that the strength of negative selection varies more than expected given the differences in Ne between species. Across species, mean fitness effects of new deleterious mutations covaries with Ne , consistent with positive epistasis among deleterious mutations. We find that the strength of negative selection for the smallest populations, bonobos and western chimpanzees, is higher than expected given their Ne This may result from a more efficient purging of strongly deleterious recessive variants in these populations. Forward simulations confirm that these findings are not artifacts of the way we are inferring Ne and DFE parameters. All findings are replicated using only GC-conservative mutations, thereby confirming that GC-biased gene conversion is not affecting our conclusions.

Application of the geographic population structure (GPS) algorithm for biogeographical analyses of wild and captive gorillas

Background

The utilization of high resolution genome data has important implications for the phylogeographical evaluation of non-human species. Biogeographical analyses can yield detailed understanding of their population biology and facilitate the geo-localization of individuals to promote their efficacious management, particularly when bred in captivity. The Geographic Population Structure (GPS) algorithm is an admixture based tool for inference of biogeographical affinities and has been employed for the geo-localization of various human populations worldwide. Here, we applied the GPS tool for biogeographical analyses and localization of the ancestral origins of wild and captive gorilla genomes, of unknown geographic source, available in the Great Ape Genome Project (GAGP), employing Gorillas with known ancestral origin as the reference data.

Results

Our findings suggest that GPS was successful in recapitulating the population history and estimating the geographic origins of all gorilla genomes queried and localized the wild gorillas with unknown geographical origin < 150 km of National Parks/Wildlife Reserves within the political boundaries of countries, considered as prominent modern-day abode for gorillas in the wild. Further, the GPS localization of most captive-born gorillas was congruent with their previously presumed ancestral homes.

Conclusions

Currently there is limited knowledge of the ancestral origins of most North American captive gorillas, and our study highlights the usefulness of GPS for inferring ancestry of captive gorillas. Determination of the native geographical source of captive gorillas can provide valuable information to guide breeding programs and ensure their appropriate management at the population level. Finally, our findings shine light on the broader applicability of GPS for protecting the genetic integrity of other endangered non-human species, where controlled breeding is a vital component of their conservation.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2568-5) contains supplementary material, which is available to authorized users.

Recurrent Loss-of-Function Mutations Reveal Costs to OAS1 Antiviral Activity in Primates

Immune responses counteract infections but also cause collateral damage to hosts. Oligoadenylate synthetase 1 (OAS1) binds double-stranded RNA from invading viruses and produces 2'-5' linked oligoadenylate (2-5A) to activate ribonuclease L (RNase L), which cleaves RNA to inhibit virus replication. OAS1 can also undergo autoactivation by host RNAs, a potential trade-off to antiviral activity. We investigated functional variation in primate OAS1 as a model for how immune pathways evolve to mitigate costs and observed a surprising frequency of loss-of-function variation. In gorillas, we identified a polymorphism that severely decreases catalytic function, mirroring a common variant in humans that impairs 2-5A synthesis through alternative splicing. OAS1 loss-of-function variation is also common in monkeys, including complete loss of 2-5A synthesis in tamarins. The frequency of loss-of-function alleles suggests that costs associated with OAS1 activation can be so detrimental to host fitness that pathogen-protective effects are repeatedly forfeited.

Whole-Genome Sequencing of Three Native Cattle Breeds Originating From the Northernmost Cattle Farming Regions

Northern Fennoscandia and the Sakha Republic in the Russian Federation represent the northernmost regions on Earth where cattle farming has been traditionally practiced. In this study, we performed whole-genome sequencing to genetically characterize three rare native breeds Eastern Finncattle, Western Finncattle and Yakutian cattle adapted to these northern Eurasian regions. We examined the demographic history, genetic diversity and unfolded loci under natural or artificial selection. On average, we achieved 13.01-fold genome coverage after mapping the sequencing reads on the bovine reference genome (UMD 3.1) and detected a total of 17.45 million single nucleotide polymorphisms (SNPs) and 1.95 million insertions-deletions (indels). We observed that the ancestral species (Bos primigenius) of Eurasian taurine cattle experienced two notable prehistorical declines in effective population size associated with dramatic climate changes. The modern Yakutian cattle exhibited a higher level of within-population variation in terms of number of SNPs and nucleotide diversity than the contemporary European taurine breeds. This result is in contrast to the results of marker-based cattle breed diversity studies, indicating assortment bias in previous analyses. Our results suggest that the effective population size of the ancestral Asiatic taurine cattle may have been higher than that of the European cattle. Alternatively, our findings could indicate the hybrid origins of the Yakutian cattle ancestries and possibly the lack of intensive artificial selection. We identified a number of genomic regions under selection that may have contributed to the adaptation to the northern and subarctic environments, including genes involved in disease resistance, sensory perception, cold adaptation and growth. By characterizing the native breeds, we were able to obtain new information on cattle genomes and on the value of the adapted breeds for the conservation of cattle genetic resources.

Genomes reveal marked differences in the adaptive evolution between orangutan species

BACKGROUND

Integrating demography and adaptive evolution is pivotal to understanding the evolutionary history and conservation of great apes. However, little is known about the adaptive evolution of our closest relatives, in particular if and to what extent adaptions to environmental differences have occurred. Here, we used whole-genome sequencing data from critically endangered orangutans from North Sumatra (Pongo abelii) and Borneo (P. pygmaeus) to investigate adaptive responses of each species to environmental differences during the Pleistocene.

RESULTS

Taking into account the markedly disparate demographic histories of each species after their split ~ 1 Ma ago, we show that persistent environmental differences on each island had a strong impact on the adaptive evolution of the genus Pongo. Across a range of tests for positive selection, we find a consistent pattern of between-island and species differences. In the more productive Sumatran environment, the most notable signals of positive selection involve genes linked to brain and neuronal development, learning, and glucose metabolism. On Borneo, however, positive selection comprised genes involved in lipid metabolism, as well as cardiac and muscle activities.

CONCLUSIONS

We find strikingly different sets of genes appearing to have evolved under strong positive selection in each species. In Sumatran orangutans, selection patterns were congruent with well-documented cognitive and behavioral differences between the species, such as a larger and more complex cultural repertoire and higher degrees of sociality. However, in Bornean orangutans, selective responses to fluctuating environmental conditions appear to have produced physiological adaptations to generally lower and temporally more unpredictable food supplies.

Using Genomic Data to Infer Historic Population Dynamics of Nonmodel Organisms

Genome sequence data are now being routinely obtained from many nonmodel organisms. These data contain a wealth of information about the demographic history of the populations from which they originate. Many sophisticated statistical inference procedures have been developed to infer the demographic history of populations from this type of genomic data. In this review, we discuss the different statistical methods available for inference of demography, providing an overview of the underlying theory and logic behind each approach. We also discuss the types of data required and the pros and cons of each method. We then discuss how these methods have been applied to a variety of nonmodel organisms. We conclude by presenting some recommendations for researchers looking to use genomic data to infer demographic history.

Background selection and biased gene conversion affect more than 95% of the human genome and bias demographic inferences

Disentangling the effect on genomic diversity of natural selection from that of demography is notoriously difficult, but necessary to properly reconstruct the history of species. Here, we use high-quality human genomic data to show that purifying selection at linked sites (i.e. background selection, BGS) and GC-biased gene conversion (gBGC) together affect as much as 95% of the variants of our genome. We find that the magnitude and relative importance of BGS and gBGC are largely determined by variation in recombination rate and base composition. Importantly, synonymous sites and non-transcribed regions are also affected, albeit to different degrees. Their use for demographic inference can lead to strong biases. However, by conditioning on genomic regions with recombination rates above 1.5 cM/Mb and mutation types (C↔G, A↔T), we identify a set of SNPs that is mostly unaffected by BGS or gBGC, and that avoids these biases in the reconstruction of human history.

Insights into Platypus Population Structure and History from Whole-Genome Sequencing

The platypus is an egg-laying mammal which, alongside the echidna, occupies a unique place in the mammalian phylogenetic tree. Despite widespread interest in its unusual biology, little is known about its population structure or recent evolutionary history. To provide new insights into the dispersal and demographic history of this iconic species, we sequenced the genomes of 57 platypuses from across the whole species range in eastern mainland Australia and Tasmania. Using a highly improved reference genome, we called over 6.7 M SNPs, providing an informative genetic data set for population analyses. Our results show very strong population structure in the platypus, with our sampling locations corresponding to discrete groupings between which there is no evidence for recent gene flow. Genome-wide data allowed us to establish that 28 of the 57 sampled individuals had at least a third-degree relative among other samples from the same river, often taken at different times. Taking advantage of a sampled family quartet, we estimated the de novo mutation rate in the platypus at 7.0 × 10-9/bp/generation (95% CI 4.1 × 10-9-1.2 × 10-8/bp/generation). We estimated effective population sizes of ancestral populations and haplotype sharing between current groupings, and found evidence for bottlenecks and long-term population decline in multiple regions, and early divergence between populations in different regions. This study demonstrates the power of whole-genome sequencing for studying natural populations of an evolutionarily important species.

Discovery of gorilla MHC-C expressing C1 ligand for KIR

In comparison to humans and chimpanzees, gorillas show low diversity at MHC class I genes (Gogo), as reflected by an overall reduced level of allelic variation as well as the absence of a functionally important sequence motif that interacts with killer cell immunoglobulin-like receptors (KIR). Here, we use recently generated large-scale genomic sequence data for a reassessment of allelic diversity at Gogo-C, the gorilla orthologue of HLA-C. Through the combination of long-range amplifications and long-read sequencing technology, we obtained, among the 35 gorillas reanalyzed, three novel full-length genomic sequences including a coding region sequence that has not been previously described. The newly identified Gogo-C*03:01 allele has a divergent recombinant structure that sets it apart from other Gogo-C alleles. Domain-by-domain phylogenetic analysis shows that Gogo-C*03:01 has segments in common with Gogo-B*07, the additional B-like gene that is present on some gorilla MHC haplotypes. Identified in ~ 50% of the gorillas analyzed, the Gogo-C*03:01 allele exclusively encodes the C1 epitope among Gogo-C allotypes, indicating its important function in controlling natural killer cell (NK cell) responses via KIR. We further explored the hypothesis whether gorillas experienced a selective sweep which may have resulted in a general reduction of the gorilla MHC class I repertoire. Our results provide little support for a selective sweep but rather suggest that the overall low Gogo class I diversity can be best explained by drastic demographic changes gorillas experienced in the ancient and recent past.

Signatures of positive selection and local adaptation to urbanization in white-footed mice (Peromyscus leucopus)

Urbanization significantly alters natural ecosystems and has accelerated globally. Urban wildlife populations are often highly fragmented by human infrastructure, and isolated populations may adapt in response to local urban pressures. However, relatively few studies have identified genomic signatures of adaptation in urban animals. We used a landscape genomic approach to examine signatures of selection in urban populations of white-footed mice (Peromyscus leucopus) in New York City. We analysed 154,770 SNPs identified from transcriptome data from 48 P. leucopus individuals from three urban and three rural populations and used outlier tests to identify evidence of urban adaptation. We accounted for demography by simulating a neutral SNP data set under an inferred demographic history as a null model for outlier analysis. We also tested whether candidate genes were associated with environmental variables related to urbanization. In total, we detected 381 outlier loci and after stringent filtering, identified and annotated 19 candidate loci. Many of the candidate genes were involved in metabolic processes and have well-established roles in metabolizing lipids and carbohydrates. Our results indicate that white-footed mice in New York City are adapting at the biomolecular level to local selective pressures in urban habitats. Annotation of outlier loci suggests selection is acting on metabolic pathways in urban populations, likely related to novel diets in cities that differ from diets in less disturbed areas.

A survey of methods and tools to detect recent and strong positive selection

Positive selection occurs when an allele is favored by natural selection. The frequency of the favored allele increases in the population and due to genetic hitchhiking the neighboring linked variation diminishes, creating so-called selective sweeps. Detecting traces of positive selection in genomes is achieved by searching for signatures introduced by selective sweeps, such as regions of reduced variation, a specific shift of the site frequency spectrum, and particular LD patterns in the region. A variety of methods and tools can be used for detecting sweeps, ranging from simple implementations that compute summary statistics such as Tajima's D, to more advanced statistical approaches that use combinations of statistics, maximum likelihood, machine learning etc. In this survey, we present and discuss summary statistics and software tools, and classify them based on the selective sweep signature they detect, i.e., SFS-based vs. LD-based, as well as their capacity to analyze whole genomes or just subgenomic regions. Additionally, we summarize the results of comparisons among four open-source software releases (SweeD, SweepFinder, SweepFinder2, and OmegaPlus) regarding sensitivity, specificity, and execution times. In equilibrium neutral models or mild bottlenecks, both SFS- and LD-based methods are able to detect selective sweeps accurately. Methods and tools that rely on LD exhibit higher true positive rates than SFS-based ones under the model of a single sweep or recurrent hitchhiking. However, their false positive rate is elevated when a misspecified demographic model is used to represent the null hypothesis. When the correct (or similar to the correct) demographic model is used instead, the false positive rates are considerably reduced. The accuracy of detecting the true target of selection is decreased in bottleneck scenarios. In terms of execution time, LD-based methods are typically faster than SFS-based methods, due to the nature of required arithmetic.

Inference of the Distribution of Selection Coefficients for New Nonsynonymous Mutations Using Large Samples

The distribution of fitness effects (DFE) has considerable importance in population genetics. To date, estimates of the DFE come from studies using a small number of individuals. Thus, estimates of the proportion of moderately to strongly deleterious new mutations may be unreliable because such variants are unlikely to be segregating in the data. Additionally, the true functional form of the DFE is unknown, and estimates of the DFE differ significantly between studies. Here we present a flexible and computationally tractable method, called Fit∂a∂i, to estimate the DFE of new mutations using the site frequency spectrum from a large number of individuals. We apply our approach to the frequency spectrum of 1300 Europeans from the Exome Sequencing Project ESP6400 data set, 1298 Danes from the LuCamp data set, and 432 Europeans from the 1000 Genomes Project to estimate the DFE of deleterious nonsynonymous mutations. We infer significantly fewer (0.38-0.84 fold) strongly deleterious mutations with selection coefficient |s| > 0.01 and more (1.24-1.43 fold) weakly deleterious mutations with selection coefficient |s| < 0.001 compared to previous estimates. Furthermore, a DFE that is a mixture distribution of a point mass at neutrality plus a gamma distribution fits better than a gamma distribution in two of the three data sets. Our results suggest that nearly neutral forces play a larger role in human evolution than previously thought.

Natural Selection in the Great Apes

Natural selection is crucial for the adaptation of populations to their environments. Here, we present the first global study of natural selection in the Hominidae (humans and great apes) based on genome-wide information from population samples representing all extant species (including most subspecies). Combining several neutrality tests we create a multi-species map of signatures of natural selection covering all major types of natural selection. We find that the estimated efficiency of both purifying and positive selection varies between species and is significantly correlated with their long-term effective population size. Thus, even the modest differences in population size among the closely related Hominidae lineages have resulted in differences in their ability to remove deleterious alleles and to adapt to changing environments. Most signatures of balancing and positive selection are species-specific, with signatures of balancing selection more often being shared among species. We also identify loci with evidence of positive selection across several lineages. Notably, we detect signatures of positive selection in several genes related to brain function, anatomy, diet and immune processes. Our results contribute to a better understanding of human evolution by putting the evidence of natural selection in humans within its larger evolutionary context. The global map of natural selection in our closest living relatives is available as an interactive browser at http://tinyurl.com/nf8qmzh.

Evolutionary History, Selective Sweeps, and Deleterious Variation in the Dog

The dog is our oldest domesticate and has experienced a wide variety of demographic histories, including a bottleneck associated with domestication and individual bottlenecks associated with the formation of modern breeds. Admixture with gray wolves, and among dog breeds and populations, has also occurred throughout its history. Likewise, the intensity and focus of selection have varied, from an initial focus on traits enhancing cohabitation with humans, to more directed selection on specific phenotypic characteristics and behaviors. In this review, we summarize and synthesize genetic findings from genome-wide and complete genome studies that document the genomic consequences of demography and selection, including the effects on adaptive and deleterious variation. Consistent with the evolutionary history of the dog, signals of natural and artificial selection are evident in the dog genome. However, conclusions from studies of positive selection are fraught with the problem of false positives given that demographic history is often not taken into account.

Long-read sequence assembly of the gorilla genome

Accurate sequence and assembly of genomes is a critical first step for studies of genetic variation. We generated a high-quality assembly of the gorilla genome using single-molecule, real-time sequence technology and a string graph de novo assembly algorithm. The new assembly improves contiguity by two to three orders of magnitude with respect to previously released assemblies, recovering 87% of missing reference exons and incomplete gene models. Although regions of large, high-identity segmental duplications remain largely unresolved, this comprehensive assembly provides new biological insight into genetic diversity, structural variation, gene loss, and representation of repeat structures within the gorilla genome. The approach provides a path forward for the routine assembly of mammalian genomes at a level approaching that of the current quality of the human genome.

The Time Scale of Recombination Rate Evolution in Great Apes

We present three linkage-disequilibrium (LD)-based recombination maps generated using whole-genome sequence data from 10 Nigerian chimpanzees, 13 bonobos, and 15 western gorillas, collected as part of the Great Ape Genome Project (Prado-Martinez J, et al. 2013. Great ape genetic diversity and population history. Nature 499:471-475). We also identified species-specific recombination hotspots in each group using a modified LDhot framework, which greatly improves statistical power to detect hotspots at varying strengths. We show that fewer hotspots are shared among chimpanzee subspecies than within human populations, further narrowing the time scale of complete hotspot turnover. Further, using species-specific PRDM9 sequences to predict potential binding sites (PBS), we show higher predicted PRDM9 binding in recombination hotspots as compared to matched cold spot regions in multiple great ape species, including at least one chimpanzee subspecies. We found that correlations between broad-scale recombination rates decline more rapidly than nucleotide divergence between species. We also compared the skew of recombination rates at centromeres and telomeres between species and show a skew from chromosome means extending as far as 10-15 Mb from chromosome ends. Further, we examined broad-scale recombination rate changes near a translocation in gorillas and found minimal differences as compared to other great ape species perhaps because the coordinates relative to the chromosome ends were unaffected. Finally, on the basis of multiple linear regression analysis, we found that various correlates of recombination rate persist throughout the African great apes including repeats, diversity, and divergence. Our study is the first to analyze within- and between-species genome-wide recombination rate variation in several close relatives.

Great ape Y Chromosome and mitochondrial DNA phylogenies reflect subspecies structure and patterns of mating and dispersal

The distribution of genetic diversity in great ape species is likely to have been affected by patterns of dispersal and mating. This has previously been investigated by sequencing autosomal and mitochondrial DNA (mtDNA), but large-scale sequence analysis of the male-specific region of the Y Chromosome (MSY) has not yet been undertaken. Here, we use the human MSY reference sequence as a basis for sequence capture and read mapping in 19 great ape males, combining the data with sequences extracted from the published whole genomes of 24 additional males to yield a total sample of 19 chimpanzees, four bonobos, 14 gorillas, and six orangutans, in which interpretable MSY sequence ranges from 2.61 to 3.80 Mb. This analysis reveals thousands of novel MSY variants and defines unbiased phylogenies. We compare these with mtDNA-based trees in the same individuals, estimating time-to-most-recent common ancestor (TMRCA) for key nodes in both cases. The two loci show high topological concordance and are consistent with accepted (sub)species definitions, but time depths differ enormously between loci and (sub)species, likely reflecting different dispersal and mating patterns. Gorillas and chimpanzees/bonobos present generally low and high MSY diversity, respectively, reflecting polygyny versus multimale–multifemale mating. However, particularly marked differences exist among chimpanzee subspecies: The western chimpanzee MSY phylogeny has a TMRCA of only 13.2 (10.8–15.8) thousand years, but that for central chimpanzees exceeds 1 million years. Cross-species comparison within a single MSY phylogeny emphasizes the low human diversity, and reveals species-specific branch length variation that may reflect differences in long-term generation times.

The conservation genetics juggling act: integrating genetics and ecology, science and policy

The field of conservation genetics, when properly implemented, is a constant juggling act integrating molecular genetics, ecology, and demography with applied aspects concerning managing declining species or implementing conservation laws and policies. This young field has grown substantially since the 1980s following the development of polymerase chain reaction and now into the genomics era. Our laboratory has ‘grown up’ with the field, having worked on these issues for over three decades. Our multidisciplinary approach entails understanding the behavior and ecology of species as well as the underlying processes that contribute to genetic viability. Taking this holistic approach provides a comprehensive understanding of factors that influence species persistence and evolutionary potential while considering annual challenges that occur throughout their life cycle. As a federal laboratory, we are often addressing the needs of the U.S. Fish and Wildlife Service in their efforts to list, de‐list, or recover species. Nevertheless, there remains an overall communication gap between research geneticists and biologists who are charged with implementing their results. Therefore, we outline the need for a National Center for Small Population Biology to ameliorate this problem and provide organizations charged with making status decisions firmer ground from which to make their critical decisions.

Characterization of MHC class II B polymorphism in multiple populations of wild gorillas using non-invasive samples and next-generation sequencing

Genes encoded by the major histocompatibility complex (MHC) are crucial for the recognition and presentation of antigens to the immune system. In contrast to their closest relatives, chimpanzees and humans, much less is known about variation in gorillas at these loci. This study explored the exon 2 variation of -DPB1, -DQB1, and -DRB genes in 46 gorillas from four populations while simultaneously evaluating the feasibility of using fecal samples for high-throughput MHC genotyping. By applying strict similarity- and frequency-based analysis, we found, despite our modest sample size, a total of 18 alleles that have not been described previously, thereby illustrating the potential for efficient and highly accurate MHC genotyping from non-invasive DNA samples. We emphasize the importance of controlling for multiple potential sources of error when applying this massively parallel short-read sequencing technology to PCR products generated from low concentration DNA extracts. We observed pronounced differences in MHC variation between species, subspecies and populations that are consistent with both the ancient and recent demographic histories experienced by gorillas.

Demographic inference using genetic data from a single individual: Separating population size variation from population structure

The rapid development of sequencing technologies represents new opportunities for population genetics research. It is expected that genomic data will increase our ability to reconstruct the history of populations. While this increase in genetic information will likely help biologists and anthropologists to reconstruct the demographic history of populations, it also represents new challenges. Recent work has shown that structured populations generate signals of population size change. As a consequence it is often difficult to determine whether demographic events such as expansions or contractions (bottlenecks) inferred from genetic data are real or due to the fact that populations are structured in nature. Given that few inferential methods allow us to account for that structure, and that genomic data will necessarily increase the precision of parameter estimates, it is important to develop new approaches. In the present study we analyze two demographic models. The first is a model of instantaneous population size change whereas the second is the classical symmetric island model. We (i) re-derive the distribution of coalescence times under the two models for a sample of size two, (ii) use a maximum likelihood approach to estimate the parameters of these models (iii) validate this estimation procedure under a wide array of parameter combinations, (iv) implement and validate a model rejection procedure by using a Kolmogorov-Smirnov test, and a model choice procedure based on the AIC, and (v) derive the explicit distribution for the number of differences between two non-recombining sequences. Altogether we show that it is possible to estimate parameters under several models and perform efficient model choice using genetic data from a single diploid individual.