Most great ape genetic variation remains uncharacterized; however,\ud its study is critical for understanding population history, recombination,\ud selection and susceptibility to disease.Herewe sequence\ud to high coverage a total of 79 wild- and captive-born individuals\ud representing all six great ape species and seven subspecies and report\ud 88.8 million single nucleotide polymorphisms. Our analysis provides\ud support for genetically distinct populations within each species,\ud signals of gene flow, and the split of common chimpanzees\ud into two distinct groups: Nigeria–Cameroon/western and central/\ud eastern populations.We find extensive inbreeding in almost all wild\ud populations, with eastern gorillas being the most extreme. Inferred\ud effective population sizes have varied radically over timein different\ud lineages and this appears to have a profound effect on the genetic\ud diversity at, or close to, genes in almost all species. We discover and\ud assign 1,982 loss-of-function variants throughout the human and\ud great ape lineages, determining that the rate of gene loss has not\ud been different in the human branch compared to other internal\ud branches in the great ape phylogeny. This comprehensive catalogue\ud of great ape genomediversity provides a framework for understanding\ud evolution and a resource for more effective management of wild\ud and captive great ape populations

Mountain gorillas are an endangered great ape subspecies and a prominent focus for conservation, yet we know little about their genomic diversity and evolutionary past. We sequenced whole genomes from multiple wild individuals and compared the genomes of all four Gorilla subspecies. We found that the two eastern subspecies have experienced a prolonged population decline over the past 100,000 years, resulting in very low genetic diversity and an increased overall burden of deleterious variation. A further recent decline in the mountain gorilla population has led to extensive inbreeding, such that individuals are typically homozygous at 34% of their sequence, leading to the purging of severely deleterious recessive mutations from the population. We discuss the causes of their decline and the consequences for their future survival.

Our closest living relatives, chimpanzees and bonobos, have a complex demographic history. We have analyzed the high-coverage whole genomes of 75 wild-born chimpanzees and bonobos from ten countries in Africa. We find that chimpanzee population sub-structure makes genetic information a good predictor of geographic origin at country and regional scales. Most strikingly, multiple lines of evidence suggest that gene flow occurred from bonobos into the ancestors of central and eastern chimpanzees between 200 and 550 thousand years ago (Kya), probably with subsequent spread into Nigeria-Cameroon chimpanzees. Together with another possibly more recent contact (after 200 Kya), bonobos contributed less than 1% to the central chimpanzee genomes. Admixture thus appears to have been widespread during hominid evolution.

The ruminants are one of the most successful mammalian lineages, exhibiting morphological and habitat diversity and containing several key livestock species. To better understand their evolution, we generated and analyzed de novo assembled genomes of 44 ruminant species, representing all six Ruminantia families. We used these genomes to create a time-calibrated phylogeny to resolve topological controversies, overcoming the challenges of incomplete lineage sorting. Population dynamic analyses show that population declines commenced between 100,000 and 50,000 years ago, which is concomitant with expansion in human populations. We also reveal genes and regulatory elements that possibly contribute to the evolution of the digestive system, cranial appendages, immune system, metabolism, body size, cursorial locomotion, and dentition of the ruminants.

Many coalescent-based methods aiming to infer the demographic history of populations assume a single, isolated and panmictic population (i.e. a Wright-Fisher model). While this assumption may be reasonable under many conditions, several recent studies have shown that the results can be misleading when it is violated. Among the most widely applied demographic inference methods are Bayesian skyline plots (BSPs), which are used across a range of biological fields. Violations of the panmixia assumption are to be expected in many biological systems, but the consequences for skyline plot inferences have so far not been addressed and quantified. We simulated DNA sequence data under a variety of scenarios involving structured populations with variable levels of gene flow and analysed them using BSPs as implemented in the software package BEAST. Results revealed that BSPs can show false signals of population decline under biologically plausible combinations of population structure and sampling strategy, suggesting that the interpretation of several previous studies may need to be re-evaluated. We found that a balanced sampling strategy whereby samples are distributed on several populations provides the best scheme for inferring demographic change over a typical time scale. Analyses of data from a structured African buffalo population demonstrate how BSP results can be strengthened by simulations. We recommend that sample selection should be carefully considered in relation to population structure previous to BSP analyses, and that alternative scenarios should be evaluated when interpreting signals of population size change.