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

Uncovering the genetic and evolutionary basis of local adaptation is a major focus of evolutionary biology. The recent development of cost-effective methods for obtaining high-quality genome-scale data makes it possible to identify some of the loci responsible for adaptive differences among populations. Two basic approaches for identifying putatively locally adaptive loci have been developed and are broadly used: one that identifies loci with unusually high genetic differentiation among populations (differentiation outlier methods) and one that searches for correlations between local population allele frequencies and local environments (genetic-environment association methods). Here, we review the promises and challenges of these genome scan methods, including correcting for the confounding influence of a species’ demographic history, biases caused by missing aspects of the genome, matching scales of environmental data with population structure, and other statistical considerations. In each case, we make suggestions for best practices for maximizing the accuracy and efficiency of genome scans to detect the underlying genetic basis of local adaptation. With attention to their current limitations, genome scan methods can be an important tool in finding the genetic basis of adaptive evolutionary change.

Efforts to identify the genetic basis of human adaptations from polymorphism data have sought footprints of “classic selective sweeps”. Yet it remains unknown whether this form of natural selection was common in our evolution. We examined the evidence for classic sweeps in resequencing data from 179 human genomes. As expected under a recurrent sweep model, diversity levels decrease near exons and conserved non-coding regions. In contrast to expectation, however, the trough in diversity around human-specific amino acid substitutions is no more pronounced than around synonymous substitutions. Moreover, relative to the genome background, amino acid and putative regulatory sites are not significantly enriched for alleles that are highly differentiated between populations. These findings indicate that classic sweeps were not a dominant mode of adaptation over the past ~250,000 years.

Identifying regions of the human genome that have been targets of positive selection will provide important insights into recent human evolutionary history and may facilitate the search for complex disease genes. However, the confounding effects of population demographic history and selection on patterns of genetic variation complicate inferences of selection when a small number of loci are studied. To this end, identifying outlier loci from empirical genome-wide distributions of genetic variation is a promising strategy to detect targets of selection. Here, we evaluate the power and efficiency of a simple outlier approach and describe a genome-wide scan for positive selection using a dense catalog of 1.58 million SNPs that were genotyped in three human populations. In total, we analyzed 14,589 genes, 385 of which possess patterns of genetic variation consistent with the hypothesis of positive selection. Furthermore, several extended genomic regions were found, spanning >500 kb, that contained multiple contiguous candidate selection genes. More generally, these data provide important practical insights into the limits of outlier approaches in genome-wide scans for selection, provide strong candidate selection genes to study in greater detail, and may have important implications for disease related research.

High-throughput DNA sequencing technologies have revolutionized genomic analysis, including the de novo assembly of whole genomes. Nevertheless, assembly of complex genomes remains challenging, in part due to the presence of dispersed repeats which introduce ambiguity during genome reconstruction. Transposable elements (TEs) can be particularly problematic, especially for TE families exhibiting high sequence identity, high copy number, or complex genomic arrangements. While TEs strongly affect genome function and evolution, most current de novo assembly approaches cannot resolve long, identical, and abundant families of TEs. Here, we applied a novel Illumina technology called TruSeq synthetic long-reads, which are generated through highly-parallel library preparation and local assembly of short read data and which achieve lengths of 1.5–18.5 Kbp with an extremely low error rate (0.03% per base). To test the utility of this technology, we sequenced and assembled the genome of the model organism Drosophila melanogaster (reference genome strain y; cn, bw, sp) achieving an N50 contig size of 69.7 Kbp and covering 96.9% of the euchromatic chromosome arms of the current reference genome. TruSeq synthetic long-read technology enables placement of individual TE copies in their proper genomic locations as well as accurate reconstruction of TE sequences. We entirely recovered and accurately placed 4,229 (77.8%) of the 5,434 annotated transposable elements with perfect identity to the current reference genome. As TEs are ubiquitous features of genomes of many species, TruSeq synthetic long-reads, and likely other methods that generate long-reads, offer a powerful approach to improve de novo assemblies of whole genomes.