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Chimpanzees, humans' closest relatives, are in danger of extinction. Aside from direct human impacts such as hunting and habitat destruction, a key threat is transmissible disease. As humans continue to encroach upon their habitats, which shrink in size and grow in density, the risk of inter-population and cross-species viral transmission increases, a point dramatically made in the reverse with the global HIV/AIDS pandemic. Inhabiting central Africa, the four subspecies of chimpanzees differ in demographic history and geographical range, and are likely differentially adapted to their particular local environments. To quantitatively explore s genetic adaptation, we investigated the genic enrichment for SNPs highly differentiated between chimpanzee subspecies. Previous analyses of such patterns in human populations exhibited limited evidence of adaptation. In contrast, chimpanzees show evidence of recent positive selection, with differences among subspecies. Specifically, we observe strong evidence of recent selection in eastern chimpanzees, with highly differentiated SNPs being uniquely enriched in genic sites in a way that is expected under recent adaptation but not under neutral evolution or background selection. These sites are enriched for genes involved in immune responses to pathogens, and for genes inferred to differentiate the immune response to infection by simian immunodeficiency virus (SIV) in natural vs. non-natural host species. Conversely, central chimpanzees exhibit an enrichment of signatures of positive selection only at cytokine receptors, due to selective sweeps in CCR3, CCR9 and CXCR6 –paralogs of CCR5 and CXCR4, the two major receptors utilized by HIV to enter human cells. Thus, our results suggest that positive selection has contributed to the genetic and phenotypic differentiation of chimpanzee subspecies, and that viruses likely play a predominate role in this differentiation, with SIV being a likely selective agent. Interestingly, our results suggest that SIV has elicited distinctive adaptive responses in these two chimpanzee subspecies. Author summary: Viruses are a major factor driving recent and ongoing natural selection in mammalian genomes. Studying the effects such selection has had on chimpanzee genomes can provide valuable insights into how pathogens are affecting an endangered primate species. As there are many notable examples of cross-species transmission between primates and humans—including the HIV/AIDS pandemic—these studies can also illuminate mechanisms of adaption to pathogens of medical and economic importance. By investigating patterns of genetic differentiation amongst the four chimpanzee sub-species, we show that genetic differences among some subspecies are due to recent genetic adaptation. The genetic variants selected uniquely in eastern chimpanzees fall disproportionally within genes that differentiate the immune response to infection by simian immunodeficiency virus (SIV) in natural vs. non-natural host species. Thus, we infer that SIV has likely elicited adaptive responses in chimpanzees, building upon a growing body of work suggesting that SIV elicits ongoing selection in African primates. [ABSTRACT FROM AUTHOR]

Pathogenic Salmonella strains that cause gastroenteritis are able to colonize and replicate within the intestines of multiple host species. In general, these strains have retained an ability to form the rdar morphotype, a resistant biofilm physiology hypothesized to be important for Salmonella transmission. In contrast, Salmonella strains that are host-adapted or even host-restricted like Salmonella enterica serovar Typhi, tend to cause systemic infections and have lost the ability to form the rdar morphotype. Here, we investigated the rdar morphotype and CsgD-regulated biofilm formation in two non-typhoidal Salmonella (NTS) strains that caused invasive disease in Malawian children, S. Typhimurium D23580 and S. Enteritidis D7795, and compared them to a panel of NTS strains associated with gastroenteritis, as well as S. Typhi strains. Sequence comparisons combined with luciferase reporter technology identified key SNPs in the promoter region of csgD that either shut off biofilm formation completely (D7795) or reduced transcription of this key biofilm regulator (D23580). Phylogenetic analysis showed that these SNPs are conserved throughout the African clades of invasive isolates, dating as far back as 80 years ago. S. Typhi isolates were negative for the rdar morphotype due to truncation of eight amino acids from the C-terminus of CsgD. We present new evidence in support of parallel evolution between lineages of nontyphoidal Salmonella associated with invasive disease in Africa and the archetypal host-restricted invasive serovar; S. Typhi. We hypothesize that the African invasive isolates are becoming human-adapted and ‘niche specialized’ with less reliance on environmental survival, as compared to gastroenteritis-causing isolates. [ABSTRACT FROM AUTHOR]

Within-population genetic diversity is greatest within Africa, while between-population genetic diversity is directly proportional to geographic distance. The most divergent contemporary human populations include the click-speaking forager peoples of southern Africa, broadly defined as Khoesan. Both intra- (Bantu expansion) and inter-continental migration (European-driven colonization) have resulted in complex patterns of admixture between ancient geographically isolated Khoesan and more recently diverged populations. Using gender-specific analysis and almost 1 million autosomal markers, we determine the significance of estimated ancestral contributions that have shaped five contemporary southern African populations in a cohort of 103 individuals. Limited by lack of available data for homogenous Khoesan representation, we identify the Ju/'hoan (n = 19) as a distinct early diverging human lineage with little to no significant non- Khoesan contribution. In contrast to the Ju/'hoan, we identify ancient signatures of Khoesan and Bantu unions resulting in significant Khoesan- and Bantu-derived contributions to the Southern Bantu amaXhosa (n = 15) and Khoesan !Xun (n = 14), respectively. Our data further suggests that contemporary !Xun represent distinct Khoesan prehistories. Khoesan assimilation with European settlement at the most southern tip of Africa resulted in significant ancestral Khoesan contributions to the Coloured (n = 25) and Baster (n = 30) populations. The latter populations were further impacted by 170 years of East Indian slave trade and intra-continental migrations resulting in a complex pattern of genetic variation (admixture). The populations of southern Africa provide a unique opportunity to investigate the genomic variability from some of the oldest human lineages to the implications of complex admixture patterns including ancient and recently diverged human lineages. [ABSTRACT FROM AUTHOR]

Demographic models built from genetic data play important roles in illuminating prehistorical events and serving as null models in genome scans for selection. We introduce an inference method based on the joint frequency spectrum of genetic variants within and between populations. For candidate models we numerically compute the expected spectrum using a diffusion approximation to the one-locus, two-allele Wright-Fisher process, involving up to three simultaneous populations. Our approach is a composite likelihood scheme, since linkage between neutral loci alters the variance but not the expectation of the frequency spectrum. We thus use bootstraps incorporating linkage to estimate uncertainties for parameters and significance values for hypothesis tests. Our method can also incorporate selection on single sites, predicting the joint distribution of selected alleles among populations experiencing a bevy of evolutionary forces, including expansions, contractions, migrations, and admixture. We model human expansion out of Africa and the settlement of the New World, using 5 Mb of noncoding DNA resequenced in 68 individuals from 4 populations (YRI, CHB, CEU, and MXL) by the Environmental Genome Project. We infer divergence between West African and Eurasian populations 140 thousand years ago (95% confidence interval: 40-270 kya). This is earlier than other genetic studies, in part because we incorporate migration. We estimate the European (CEU) and East Asian (CHB) divergence time to be 23 kya (95% c.i.: 17-43 kya), long after archeological evidence places modern humans in Europe. Finally, we estimate divergence between East Asians (CHB) and Mexican-Americans (MXL) of 22 kya (95% c.i.: 16.3-26.9 kya), and our analysis yields no evidence for subsequent migration. Furthermore, combining our demographic model with a previously estimated distribution of selective effects among newly arising amino acid mutations accurately predicts the frequency spectrum of nonsynonymous variants across three continental populations (YRI, CHB, CEU). [ABSTRACT FROM AUTHOR]

Various observations argue for a role of adaptation in recent human evolution, including results from genome-wide studies and analyses of selection signals at candidate genes. Here, we use genome-wide SNP data from the HapMap and CEPHHuman Genome Diversity Panel samples to study the geographic distributions of putatively selected alleles at a range of geographic scales. We find that the average allele frequency divergence is highly predictive of the most extreme FST values across the whole genome. On a broad scale, the geographic distribution of putatively selected alleles almost invariably conforms to population clusters identified using randomly chosen genetic markers. Given this structure, there are surprisingly few fixed or nearly fixed differences between human populations. Among the nearly fixed differences that do exist, nearly all are due to fixation events that occurred outside of Africa, and most appear in East Asia. These patterns suggest that selection is often weak enough that neutral processes-especially population history, migration, and drift- exert powerful influences over the fate and geographic distribution of selected alleles. [ABSTRACT FROM AUTHOR]

The transition from hunting and gathering to farming involved a major cultural innovation that has spread rapidly over most of the globe in the last ten millennia. In sub-Saharan Africa, hunter-gatherers have begun to shift toward an agriculture-based lifestyle over the last 5,000 years. Only a few populations still base their mode of subsistence on hunting and gathering. The Pygmies are considered to be the largest group of mobile hunter-gatherers of Africa. They dwell in equatorial rainforests and are characterized by their short mean stature. However, little is known about the chronology of the demographic events-size changes, population splits, and gene flow-ultimately giving rise to contemporary Pygmy (Western and Eastern) groups and neighboring agricultural populations. We studied the branching history of Pygmy hunter-gatherers and agricultural populations from Africa and estimated separation times and gene flow between these populations. We resequenced 24 independent noncoding regions across the genome, corresponding to a total of ,33 kb per individual, in 236 samples from seven Pygmy and five agricultural populations dispersed over the African continent. We used simulation-based inference to identify the historical model best fitting our data. The model identified included the early divergence of the ancestors of Pygmy hunter-gatherers and farming populations ,60,000 years ago, followed by a split of the Pygmies' ancestors into the Western and Eastern Pygmy groups ,20,000 years ago. Our findings increase knowledge of the history of the peopling of the African continent in a region lacking archaeological data. An appreciation of the demographic and adaptive history of African populations with different modes of subsistence should improve our understanding of the influence of human lifestyles on genome diversity. [ABSTRACT FROM AUTHOR]

Estimating fine-scale recombination maps of Drosophila from population genomic data is a challenging problem, in particular because of the high background recombination rate. In this paper, a new computational method is developed to address this challenge. Through an extensive simulation study, it is demonstrated that the method allows more accurate inference, and exhibits greater robustness to the effects of natural selection and noise, compared to a well-used previous method developed for studying fine-scale recombination rate variation in the human genome. As an application, a genome-wide analysis of genetic variation data is performed for two Drosophila melanogaster populations, one from North America (Raleigh, USA) and the other from Africa (Gikongoro, Rwanda). It is shown that fine-scale recombination rate variation is widespread throughout the D. melanogaster genome, across all chromosomes and in both populations. At the fine-scale, a conservative, systematic search for evidence of recombination hotspots suggests the existence of a handful of putative hotspots each with at least a tenfold increase in intensity over the background rate. A wavelet analysis is carried out to compare the estimated recombination maps in the two populations and to quantify the extent to which recombination rates are conserved. In general, similarity is observed at very broad scales, but substantial differences are seen at fine scales. The average recombination rate of the X chromosome appears to be higher than that of the autosomes in both populations, and this pattern is much more pronounced in the African population than the North American population. The correlation between various genomic features-including recombination rates, diversity, divergence, GC content, gene content, and sequence quality-is examined using the wavelet analysis, and it is shown that the most notable difference between D. melanogaster and humans is in the correlation between recombination and diversity., Competing Interests: The authors have declared that no competing interests exist.

We consider the statistical analysis of population structure using genetic data. We show how the two most widely used approaches to modeling population structure, admixture-based models and principal components analysis (PCA), can be viewed within a single unifying framework of matrix factorization. Specifically, they can both be interpreted as approximating an observed genotype matrix by a product of two lower-rank matrices, but with different constraints or prior distributions on these lower-rank matrices. This opens the door to a large range of possible approaches to analyzing population structure, by considering other constraints or priors. In this paper, we introduce one such novel approach, based on sparse factor analysis (SFA). We investigate the effects of the different types of constraint in several real and simulated data sets. We find that SFA produces similar results to admixture-based models when the samples are descended from a few well-differentiated ancestral populations and can recapitulate the results of PCA when the population structure is more "continuous," as in isolation-by-distance models., Competing Interests: The authors have declared that no competing interests exist.