Population genomic analysis reveals a rich speciation and demographic history of orang-utans (Pongo pygmaeus and Pongo abelii)

Evolutionary consequences of domestication on the selective effects of new amino acid changing mutations in canids

The domestication of wild canids led to dogs no longer living in the wild but instead residing alongside humans. Extreme changes in behavior and diet associated with domestication may have led to the relaxation of the selective pressure on traits that may be less important in the domesticated context. Thus, here we hypothesize that strongly deleterious mutations may have become less deleterious in domesticated populations. We test this hypothesis by estimating the distribution of fitness effects (DFE) for new amino acid changing mutations using whole-genome sequence data from 24 gray wolves and 61 breed dogs. We find that the DFE is strikingly similar across canids, with 26-28% of new amino acid changing mutations being neutral/nearly neutral (|s| < 1e-5), and 41-48% under strong purifying selection (|s| > 1e-2). Our results are robust to different model assumptions suggesting that the DFE is stable across short evolutionary timescales, even in the face of putative drastic changes in the selective pressure caused by artificial selection during domestication and breed formation. On par with previous works describing DFE evolution, our data indicate that the DFE of amino acid changing mutations depends more strongly on genome structure and organismal characteristics, and less so on shifting selective pressures or environmental factors. Given the constant DFE and previous data showing that genetic variants that differentiate wolf and dog populations are enriched in regulatory elements, we speculate that domestication may have had a larger impact on regulatory variation than on amino acid changing mutations.

Using Computational Simulations to Model Deleterious Variation and Genetic Load in Natural Populations

AbstractDeleterious genetic variation is abundant in wild populations, and understanding the ecological and conservation implications of such variation is an area of active research. Genomic methods are increasingly used to quantify the impacts of deleterious variation in natural populations; however, these approaches remain limited by an inability to accurately predict the selective and dominance effects of mutations. Computational simulations of deleterious variation offer a complementary tool that can help overcome these limitations, although such approaches have yet to be widely employed. In this perspective article, we aim to encourage ecological and conservation genomics researchers to adopt greater use of computational simulations to aid in deepening our understanding of deleterious variation in natural populations. We first provide an overview of the components of a simulation of deleterious variation, describing the key parameters involved in such models. Next, we discuss several approaches for validating simulation models. Finally, we compare and validate several recently proposed deleterious mutation models, demonstrating that models based on estimates of selection parameters from experimental systems are biased toward highly deleterious mutations. We describe a new model that is supported by multiple orthogonal lines of evidence and provide example scripts for implementing this model (https://github.com/ckyriazis/simulations_review).

Quantifying the fraction of new mutations that are recessive lethal

The presence and impact of recessive lethal mutations have been widely documented in diploid outcrossing species. However, precise estimates of the proportion of new mutations that are recessive lethal remain limited. Here, we evaluate the performance of Fit∂a∂i, a commonly used method for inferring the distribution of fitness effects (DFE), in the presence of lethal mutations. Using simulations, we demonstrate that in both additive and recessive cases, inference of the deleterious nonlethal portion of the DFE is minimally affected by a small proportion (<10%) of lethal mutations. Additionally, we demonstrate that while Fit∂a∂i cannot estimate the fraction of recessive lethal mutations, Fit∂a∂i can accurately infer the fraction of additive lethal mutations. Finally, as an alternative approach to estimate the proportion of mutations that are recessive lethal, we employ models of mutation-selection-drift balance using existing genomic parameters and estimates of segregating recessive lethals for humans and Drosophila melanogaster. In both species, the segregating recessive lethal load can be explained by a very small fraction (<1%) of new nonsynonymous mutations being recessive lethal. Our results refute recent assertions of a much higher proportion of mutations being recessive lethal (4%-5%), while highlighting the need for additional information on the joint distribution of selection and dominance coefficients.

Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations

Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic datasets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed framework stdpopsim seeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version of stdpopsim focused on establishing this framework using six well-characterized model species (Adrion et al., 2020). Here, we report on major improvements made in the new release of stdpopsim (version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than threefold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed the best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements to stdpopsim aim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone.

Nine out of ten samples were mistakenly switched by The Orang-utan Genome Consortium

The Sumatran orang-utan (Pongo abelii) reference genome was first published in 2011, in conjunction with ten re-sequenced genomes from unrelated wild-caught individuals. Together, these published data have been utilized in almost all great ape genomic studies, plus in much broader comparative genomic research. Here, we report that the original sequencing Consortium inadvertently switched nine of the ten samples and/or resulting re-sequenced genomes, erroneously attributing eight of these to the wrong source individuals. Among them is a genome from the recently identified Tapanuli (P. tapanuliensis) species: thus, this genome was sequenced and published a full six years prior to the species’ description. Sex was wrongly assigned to five known individuals; the numbers in one sample identifier were swapped; and the identifier for another sample most closely resembles that of a sample from another individual entirely. These errors have been reproduced in countless subsequent manuscripts, with noted implications for studies reliant on data from known individuals.

On the prospect of achieving accurate joint estimation of selection with population history

As both natural selection and population history can affect genome-wide patterns of variation, disentangling the contributions of each has remained as a major challenge in population genetics. We here discuss historical and recent progress towards this goal-highlighting theoretical and computational challenges that remain to be addressed, as well as inherent difficulties in dealing with model complexity and model violations-and offer thoughts on potentially fruitful next steps.

Short Tandem Repeats as a High-Resolution Marker for Capturing Recent Orangutan Population Evolution

The genus Pongo is ideal to study population genetics adaptation, given its remarkable phenotypic divergence and the highly contrasting environmental conditions it’s been exposed to. Studying its genetic variation bears the promise to reveal a motion picture of these great apes’ evolutionary and adaptive history, and also helps us expand our knowledge of the patterns of adaptation and evolution. In this work, we advance the understanding of the genetic variation among wild orangutans through a genome-wide study of short tandem repeats (STRs). Their elevated mutation rate makes STRs ideal markers for the study of recent evolution within a given population. Current technological and algorithmic advances have rendered their sequencing and discovery more accurate, therefore their potential can be finally leveraged in population genetics studies. To study patterns of population variation within the wild orangutan population, we genotyped the short tandem repeats in a population of 21 individuals spanning four Sumatran and Bornean (sub-) species and eight Southeast Asian regions. We studied the impact of sequencing depth on our ability to genotype STRs and found that the STR copy number changes function as a powerful marker, correctly capturing the demographic history of these populations, even the divergences as recent as 10 Kya. Moreover, gene ontology enrichments for genes close to STR variants are aligned with local adaptations in the two islands. Coupled with more advanced STR-compatible population models, and selection tests, genomic studies based on STRs will be able to reduce the gap caused by the missing heritability for species with recent adaptations.

Inferring genome-wide correlations of mutation fitness effects between populations

The effect of a mutation on fitness may differ between populations depending on environmental and genetic context, but little is known about the factors that underlie such differences. To quantify genome-wide correlations in mutation fitness effects, we developed a novel concept called a joint distribution of fitness effects (DFE) between populations. We then proposed a new statistic w to measure the DFE correlation between populations. Using simulation, we showed that inferring the DFE correlation from the joint allele frequency spectrum is statistically precise and robust. Using population genomic data, we inferred DFE correlations of populations in humans, Drosophila melanogaster, and wild tomatoes. In these species, we found that the overall correlation of the joint DFE was inversely related to genetic differentiation. In humans and D. melanogaster, deleterious mutations had a lower DFE correlation than tolerated mutations, indicating a complex joint DFE. Altogether, the DFE correlation can be reliably inferred, and it offers extensive insight into the genetics of population divergence.

Adaptation, ancestral variation and gene flow in a 'Sky Island' Drosophila species

Over time, populations of species can expand, contract, fragment and become isolated, creating subpopulations that must adapt to local conditions. Understanding how species maintain variation after divergence as well as adapt to these changes in the face of gene flow is of great interest, especially as the current climate crisis has caused range shifts and frequent migrations for many species. Here, we characterize how a mycophageous fly species, Drosophila innubila, came to inhabit and adapt to its current range which includes mountain forests in south-western USA separated by large expanses of desert. Using population genomic data from more than 300 wild-caught individuals, we examine four populations to determine their population history in these mountain forests, looking for signatures of local adaptation. In this first extensive study, establishing D. innubila as a key genomic "Sky Island" model, we find D. innubila spread northwards during the previous glaciation period (30-100 KYA) and have recently expanded even further (0.2-2 KYA). D. innubila shows little evidence of population structure, consistent with a recent establishment and genetic variation maintained since before geographic stratification. We also find some signatures of recent selective sweeps in chorion proteins and population differentiation in antifungal immune genes suggesting differences in the environments to which flies are adapting. However, we find little support for long-term recurrent selection in these genes. In contrast, we find evidence of long-term recurrent positive selection in immune pathways such as the Toll signalling system and the Toll-regulated antimicrobial peptides.

Two to Tango: Co-evolution of Hominid Natural Killer Cell Receptors and MHC

Natural killer (NK) cells have diverse roles in hominid immunity and reproduction. Modulating these functions are the interactions between major histocompatibility complex (MHC) class I molecules that are ligands for two NK cell surface receptor types. Diverse killer cell immunoglobulin-like receptors (KIR) bind specific motifs encoded within the polymorphic MHC class I cell surface glycoproteins, while, in more conserved interactions, CD94:NKG2A receptors recognize MHC-E with bound peptides derived from MHC class I leader sequences. The hominid lineage presents a choreographed co-evolution of KIR with their MHC class I ligands. MHC-A, -B, and -C are present in all great apes with species-specific haplotypic variation in gene content. The Bw4 epitope recognized by lineage II KIR is restricted to MHC-B but also present on some gorilla and human MHC-A. Common to great apes, but rare in humans, are MHC-B possessing a C1 epitope recognized by lineage III KIR. MHC-C arose from duplication of MHC-B and is fixed in all great apes except orangutan, where it exists on approximately 50% of haplotypes and all allotypes are C1-bearing. Recent study showed that gorillas possess yet another intermediate MHC organization compared to humans. Like orangutans, but unlike the Pan-Homo species, duplication of MHC-B occurred. However, MHC-C is fixed, and the MHC-C C2 epitope (absent in orangutans) emerges. The evolution of MHC-C drove expansion of its cognate lineage III KIR. Recently, position −21 of the MHC-B leader sequence has been shown to be critical in determining NK cell educational outcome. In humans, methionine (−21M) results in CD94:NKG2A-focused education whereas threonine (−21T) produces KIR-focused education. This is another dynamic position among hominids. Orangutans have exclusively −21M, consistent with their intermediate stage in lineage III KIR-focused evolution. Gorillas have both −21M and −21T, like humans, but they are unequally encoded by their duplicated B genes. Chimpanzees have near-fixed −21T, indicative of KIR-focused NK education. Harmonious with this observation, chimpanzee KIR exhibit strong binding and, compared to humans, smaller differences between binding levels of activating and inhibitory KIR. Consistent between these MHC-NK cell receptor systems over the course of hominid evolution is the evolution of polymorphism favoring the more novel and dynamic KIR system.

ABLE: blockwise site frequency spectra for inferring complex population histories and recombination

We introduce ABLE (Approximate Blockwise Likelihood Estimation), a novel simulation-based composite likelihood method that uses the blockwise site frequency spectrum to jointly infer past demography and recombination. ABLE is explicitly designed for a wide variety of data from unphased diploid genomes to genome-wide multi-locus data (for example, RADSeq) and can also accommodate arbitrarily large samples. We use simulations to demonstrate the accuracy of this method to infer complex histories of divergence and gene flow and reanalyze whole genome data from two species of orangutan. ABLE is available for download at https://github.com/champost/ABLE.

The Y chromosomes of the great apes

The great apes (orangutans, gorillas, chimpanzees, bonobos and humans) descended from a common ancestor around 13 million years ago, and since then their sex chromosomes have followed very different evolutionary paths. While great-ape X chromosomes are highly conserved, their Y chromosomes, reflecting the general lability and degeneration of this male-specific part of the genome since its early mammalian origin, have evolved rapidly both between and within species. Understanding great-ape Y chromosome structure, gene content and diversity would provide a valuable evolutionary context for the human Y, and would also illuminate sex-biased behaviours, and the effects of the evolutionary pressures exerted by different mating strategies on this male-specific part of the genome. High-quality Y-chromosome sequences are available for human and chimpanzee (and low-quality for gorilla). The chromosomes differ in size, sequence organisation and content, and while retaining a relatively stable set of ancestral single-copy genes, show considerable variation in content and copy number of ampliconic multi-copy genes. Studies of Y-chromosome diversity in other great apes are relatively undeveloped compared to those in humans, but have nevertheless provided insights into speciation, dispersal, and mating patterns. Future studies, including data from larger sample sizes of wild-born and geographically well-defined individuals, and full Y-chromosome sequences from bonobos, gorillas and orangutans, promise to further our understanding of population histories, male-biased behaviours, mutation processes, and the functions of Y-chromosomal genes.

Two Orangutan Species Have Evolved Different KIR Alleles and Haplotypes

The immune and reproductive functions of human NK cells are regulated by interactions of the C1 and C2 epitopes of HLA-C with C1-specific and C2-specific lineage III killer cell Ig-like receptors (KIR). This rapidly evolving and diverse system of ligands and receptors is restricted to humans and great apes. In this context, the orangutan has particular relevance because it represents an evolutionary intermediate, one having the C1 epitope and corresponding KIR but lacking the C2 epitope. Through a combination of direct sequencing, KIR genotyping, and data mining from the Great Ape Genome Project, we characterized the KIR alleles and haplotypes for panels of 10 Bornean orangutans and 19 Sumatran orangutans. The orangutan KIR haplotypes have between 5 and 10 KIR genes. The seven orangutan lineage III KIR genes all locate to the centromeric region of the KIR locus, whereas their human counterparts also populate the telomeric region. One lineage III KIR gene is Bornean specific, one is Sumatran specific, and five are shared. Of 12 KIR gene-content haplotypes, 5 are Bornean specific, 5 are Sumatran specific, and 2 are shared. The haplotypes have different combinations of genes encoding activating and inhibitory C1 receptors that can be of higher or lower affinity. All haplotypes encode an inhibitory C1 receptor, but only some haplotypes encode an activating C1 receptor. Of 130 KIR alleles, 55 are Bornean specific, 65 are Sumatran specific, and 10 are shared.

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.

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.

Accelerated diversification of nonhuman primate malarias in Southeast Asia: adaptive radiation or geographic speciation?

Although parasitic organisms are found worldwide, the relative importance of host specificity and geographic isolation for parasite speciation has been explored in only a few systems. Here, we study Plasmodium parasites known to infect Asian nonhuman primates, a monophyletic group that includes the lineage leading to the human parasite Plasmodium vivax and several species used as laboratory models in malaria research. We analyze the available data together with new samples from three sympatric primate species from Borneo: The Bornean orangutan and the long-tailed and the pig-tailed macaques. We find several species of malaria parasites, including three putatively new species in this biodiversity hotspot. Among those newly discovered lineages, we report two sympatric parasites in orangutans. We find no differences in the sets of malaria species infecting each macaque species indicating that these species show no host specificity. Finally, phylogenetic analysis of these data suggests that the malaria parasites infecting Southeast Asian macaques and their relatives are speciating three to four times more rapidly than those with other mammalian hosts such as lemurs and African apes. We estimate that these events took place in approximately a 3-4-Ma period. Based on the genetic and phenotypic diversity of the macaque malarias, we hypothesize that the diversification of this group of parasites has been facilitated by the diversity, geographic distributions, and demographic histories of their primate hosts.