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Human populations have been shaped by catastrophes that may have left long-lasting signatures in their genomes. One notable example is the second plague pandemic that entered Europe in ca. 1,347 CE and repeatedly returned for over 300 years, with typical village and town mortality estimated at 10%–40%.1 It is assumed that this high mortality affected the gene pools of these populations. First, local population crashes reduced genetic diversity. Second, a change in frequency is expected for sequence variants that may have affected survival or susceptibility to the etiologic agent (Yersinia pestis).2 Third, mass mortality might alter the local gene pools through its impact on subsequent migration patterns. We explored these factors using the Norwegian city of Trondheim as a model, by sequencing 54 genomes spanning three time periods: (1) prior to the plague striking Trondheim in 1,349 CE, (2) the 17th–19th century, and (3) the present. We find that the pandemic period shaped the gene pool by reducing long distance immigration, in particular from the British Isles, and inducing a bottleneck that reduced genetic diversity. Although we also observe an excess of large FST values at multiple loci in the genome, these are shaped by reference biases introduced by mapping our relatively low genome coverage degraded DNA to the reference genome. This implies that attempts to detect selection using ancient DNA (aDNA) datasets that vary by read length and depth of sequencing coverage may be particularly challenging until methods have been developed to account for the impact of differential reference bias on test statistics.

Human populations have been shaped by catastrophes that may have left long-lasting signatures in their genomes. One notable example is the second plague pandemic that entered Europe in ca. 1,347 CE and repeatedly returned for over 300 years, with typical village and town mortality estimated at 10%–40%.1 It is assumed that this high mortality affected the gene pools of these populations. First, local population crashes reduced genetic diversity. Second, a change in frequency is expected for sequence variants that may have affected survival or susceptibility to the etiologic agent (Yersinia pestis).2 Third, mass mortality might alter the local gene pools through its impact on subsequent migration patterns. We explored these factors using the Norwegian city of Trondheim as a model, by sequencing 54 genomes spanning three time periods: (1) prior to the plague striking Trondheim in 1,349 CE, (2) the 17th–19th century, and (3) the present. We find that the pandemic period shaped the gene pool by reducing long distance immigration, in particular from the British Isles, and inducing a bottleneck that reduced genetic diversity. Although we also observe an excess of large FST values at multiple loci in the genome, these are shaped by reference biases introduced by mapping our relatively low genome coverage degraded DNA to the reference genome. This implies that attempts to detect selection using ancient DNA (aDNA) datasets that vary by read length and depth of sequencing coverage may be particularly challenging until methods have been developed to account for the impact of differential reference bias on test statistics.

Archaeological research documents major technological shifts among people who have lived in the southern tip of South America (South Patagonia) during the last thirteen millennia, including the development of marine-based economies and changes in tools and raw materials. It has been proposed that movements of people spreading culture and technology propelled some of these shifts, but these hypotheses have not been tested with ancient DNA. Here we report genome-wide data from 20 ancient individuals, and co-analyze it with previously reported data. We reveal that immigration does not explain the appearance of marine adaptations in South Patagonia. We describe partial genetic continuity since ~6600 BP and two later gene flows correlated with technological changes: one between 4700–2000 BP that affected primarily marine-based groups, and a later one impacting all <2000 BP groups. From ~2200–1200 BP, mixture among neighbors resulted in a cline correlated to geographic ordering along the coast.

Loss of function (LoF) genetic variants are predicted to disrupt gene function, and are therefore expected to substantially reduce individual’s viability. Knowing the genetic burden of LoF variants in endangered species is of interest for a better understanding of the effects of declining population sizes on species viability. In this study, we have estimated the number of LoF polymorphic variants in six great ape populations, based on whole-genome sequencing data in 79 individuals. Our results show that although the number of functional variants per individual is conditioned by the effective population size, the number of variants with a drastic phenotypic effect is very similar across species. We hypothesize that for those variants with high selection coefficients, differences in effective population size are not important enough to affect the efficiency of natural selection to remove them. We also describe that mostly CpG LoF mutations are shared across species, and an accumulation of LoF variants at olfactory receptor genes in agreement with its pseudogenization in humans and other primate species.

© 2015 Macmillan Publishers Limited. Human leukocyte antigen-G (HLA-G) has well-recognized immunosuppressive properties modulating the activity of many immune system cells, and polymorphisms observed at the HLA-G 5′ upstream regulatory region (5′URR) may influence gene transcriptional regulation. In this study, we characterized the sequence variation and haplotype structure of the HLA-G 5′URR in worldwide populations to investigate the evolutionary history of the HLA-G promoter and shed some light into the mechanisms that may underlie HLA-G expression control. A 1.4-kb region, encompassing the known HLA-G regulatory elements, was sequenced in three African populations from Senegal, Benin and Congo, and data were combined with those available in the literature, resulting in a total of 1411 individuals from 21 worldwide populations. High levels of nucleotide and haplotype diversities, excess of intermediate-frequency variants and reduced population differentiation were observed at this locus when compared with the background genomic variation. These features support a strong molecular signature of balancing selection at HLA-G 5′URR, probably as a result of the competing needs to maintain both a maternal-fetal immune tolerance and an efficient host immune response to invading pathogens during human evolution. An extended analysis of a 300-kb region surrounding HLA-G revealed that this region is not involved in a hitchhiking effect and may be the direct target of selection.

East Africa is a strategic region to study human genetic diversity due to the presence of ethnically, linguistically, and geographically diverse populations. Here, we provide new insight into the genetic history of populations living in the Sudanese region of East Africa by analysing nine ethnic groups belonging to three African linguistic families: Niger-Kordofanian, Nilo-Saharan and Afro-Asiatic. A total of 500 individuals were genotyped for 200,000 single-nucleotide polymorphisms. Principal component analysis, clustering analysis using ADMIXTURE, FST statistics, and the three-population test were used to investigate the underlying genetic structure and ancestry of the different ethno-linguistic groups. Our analyses revealed a genetic component for Sudanese Nilo-Saharan speaking groups (Darfurians and part of Nuba populations) related to Nilotes of South Sudan, but not to other Sudanese populations or other sub-Saharan populations. Populations inhabiting the North of the region showed close genetic affinities with North Africa, with a component that could be remnant of North Africans before the migrations of Arabs from Arabia. In addition, we found very low genetic distances between populations in genes important for anti-malarial and anti-bacterial host defence, suggesting similar selective pressures on these genes and stressing the importance of considering functional pathways to understand the evolutionary history of populations.

East Africa is a strategic region to study human genetic diversity due to the presence of ethnically, linguistically, and geographically diverse populations. Here, we provide new insight into the genetic history of populations living in the Sudanese region of East Africa by analysing nine ethnic groups belonging to three African linguistic families: Niger-Kordofanian, Nilo-Saharan and Afro-Asiatic. A total of 500 individuals were genotyped for 200,000 single-nucleotide polymorphisms. Principal component analysis, clustering analysis using ADMIXTURE, FST statistics, and the three*population test were used to investigate the underlying genetic structure and ancestry of the different ethnolinguistic groups. Our analyses revealed a genetic component for Sudanese Nilo*Saharan speaking groups (Darfurians and part of Nuba populations) related to Nilotes of South Sudan, but not to other Sudanese populations or other sub*Saharan populations. Populations inhabiting the North of the region showed close genetic affinities with North Africa, with a component that could be remnant of North Africans before the migrations of Arabs from Arabia. In addition, we found very low genetic distances between populations in genes important for anti*malarial and anti-bacterial host defence, suggesting similar selective pressures on these genes and stressing the importance of considering functional pathways to understand the evolutionary history of populations.

Genes vary in their likelihood to undergo adaptive evolution. The genomic factors that determine adaptability, however, remain poorly understood. Genes function in the context of molecular networks, with some occupying more important positions than others and thus being likely to be under stronger selective pressures. However, how positive selection distributes across the different parts of molecular networks is still not fully understood. Here, we inferred positive selection using comparative genomics and population genetics approaches through the comparison of 10 mammalian and 270 human genomes, respectively. In agreement with previous results, we found that genes with lower network centralities are more likely to evolve under positive selection (as inferred from divergence data). Surprisingly, polymorphism data yield results in the opposite direction than divergence data: Genes with higher centralities are more likely to have been targeted by recent positive selection during recent human evolution. Our results indicate that the relationship between centrality and the impact of adaptive evolution highly depends on the mode of positive selection and/or the evolutionary time-scale.

[Motivation] Detecting positive selection in genomic regions is a recurrent topic in natural population genetic studies. However, there is little consistency among the regions detected in several genome-wide scans using different tests and/or populations. Furthermore, few methods address the challenge of classifying selective events according to specific features such as age, intensity or state (completeness)., [Results] We have developed a machine-learning classification framework that exploits the combined ability of some selection tests to uncover different polymorphism features expected under the hard sweep model, while controlling for population-specific demography. As a result, we achieve high sensitivity toward hard selective sweeps while adding insights about their completeness (whether a selected variant is fixed or not) and age of onset. Our method also determines the relevance of the individual methods implemented so far to detect positive selection under specific selective scenarios. We calibrated and applied the method to three reference human populations from The 1000 Genome Project to generate a genome-wide classification map of hard selective sweeps. This study improves detection of selective sweep by overcoming the classical selection versus no-selection classification strategy, and offers an explanation to the lack of consistency observed among selection tests when applied to real data. Very few signals were observed in the African population studied, while our method presents higher sensitivity in this population demography.

[Background] Population differentiation has proved to be effective for identifying loci under geographically localized positive selection, and has the potential to identify loci subject to balancing selection. We have previously investigated the pattern of genetic differentiation among human populations at 36.8 million genomic variants to identify sites in the genome showing high frequency differences. Here, we extend this dataset to include additional variants, survey sites with low levels of differentiation, and evaluate the extent to which highly differentiated sites are likely to result from selective or other processes., [Results] We demonstrate that while sites with low differentiation represent sampling effects rather than balancing selection, sites showing extremely high population differentiation are enriched for positive selection events and that one half may be the result of classic selective sweeps. Among these, we rediscover known examples, where we actually identify the established functional SNP, and discover novel examples including the genes ABCA12, CALD1 and ZNF804, which we speculate may be linked to adaptations in skin, calcium metabolism and defense, respectively., [Conclusions] We identify known and many novel candidate regions for geographically restricted positive selection, and suggest several directions for further research. © 2014 Colonna et al.

Indian demographic history includes special features such as founder effects, interpopulation segregation, complex social structure with a caste system and elevated frequency of consanguineous marriages. It also presents a higher frequency for some rare mendelian disorders and in the last two decades increased prevalence of some complex disorders. Despite the fact that India represents about one-sixth of the human population, deep genetic studies from this terrain have been scarce. In this study, we analyzed high-density genotyping and whole-exome sequencing data of a North and a South Indian population. Indian populations show higher differentiation levels than those reported between populations of other continents. In this work, we have analyzed its consequences, by specifically assessing the transferability of genetic markers from or to Indian populations. We show that there is limited genetic marker portability from available genetic resources such as HapMap or the 1,000 Genomes Project to Indian populations, which also present an excess of private rare variants. Conversely, tagSNPs show a high level of portability between the two Indian populations, in contrast to the common belief that North and South Indian populations are genetically very different. By estimating kinship from mates and consanguinity in our data from trios, we also describe different patterns of assortative mating and inbreeding in the two populations, in agreement with distinct mating preferences and social structures. In addition, this analysis has allowed us to describe genomic regions under recent adaptive selection, indicating differential adaptive histories for North and South Indian populations. Our findings highlight the importance of considering demography for design and analysis of genetic studies, as well as the need for extending human genetic variation catalogs to new populations and particularly to those with particular demographic histories.

The HLA-G (human leukocyte antigen-G) molecule plays a pivotal role in immune tolerance by inhibiting different cell subsets involved in both innate and adaptive immunity. Besides its primary function in maintaining the maternal–fetal tolerance, HLA-G has been involved in a wide range of pathological conditions where it can be either favorable or detrimental to the patient, depending on the nature of the pathology. Although several studies have demonstrated the utmost importance of the 3′ untranslated region (3′UTR) in the HLA-G expression profile, limited data exist on the sequence variability of this gene region in human populations. In this study, we characterized the genetic diversity and haplotype structure of the HLA-G 3′UTR by resequencing 444 individuals from three sub-Saharan African populations and retrieving data from the 1000 Genomes project and the literature. A total of 1936 individuals representing 21 worldwide populations were combined and jointly analyzed. Our data revealed a high level of nucleotide diversity, an excess of intermediate frequency variants and an extremely low population differentiation, strongly supporting a history of balancing selection at this locus. The 14-bp insertion/deletion polymorphism was further pointed out as the likely target of selection, emphasizing its potential role in the post-transcriptional regulation of HLA-G expression.

VKORC1 (vitamin K epoxide reductase complex subunit 1, 16p11.2) is the main genetic determinant of human response to oral anticoagulants of antivitamin K type (AVK). This gene was recently suggested to be a putative target of positive selection in East Asian populations. In this study, we genotyped the HGDP-CEPH Panel for six VKORC1 SNPs and downloaded chromosome 16 genotypes from the HGDP-CEPH database in order to characterize the geographic distribution of footprints of positive selection within and around this locus. A unique VKORC1 haplotype carrying the promoter mutation associated with AVK sensitivity showed especially high frequencies in all the 17 HGDP-CEPH East Asian population samples. VKORC1 and 24 neighboring genes were found to lie in a 505 kb region of strong linkage disequilibrium in these populations. Patterns of allele frequency differentiation and haplotype structure suggest that this genomic region has been submitted to a near complete selective sweep in all East Asian populations and only in this geographic area. The most extreme scores of the different selection tests are found within a smaller 45 kb region that contains VKORC1 and three other genes (BCKDK, MYST1 (KAT8), and PRSS8) with different functions. Because of the strong linkage disequilibrium, it is not possible to determine if VKORC1 or one of the three other genes is the target of this strong positive selection that could explain present-day differences among human populations in AVK dose requirement. Our results show that the extended region surrounding a presumable single target of positive selection should be analyzed for genetic variation in a wide range of genetically diverse populations in order to account for other neighboring and confounding selective events and the hitchhiking effect. © 2012 Patillon et al.

Genes and proteins rarely act in isolation, but they rather operate as components of complex networks of interacting molecules. Therefore, for understanding their evolution, it may be helpful to take into account the interaction networks in which they participate. It has been shown that selective constraints acting on genes depend on the position that they occupy in the network. Less understood is how the impact of local adaptation at the intraspecific level is affected by the network structure. Here, we analyzed the patterns of molecular evolution of 67 genes involved in the insulin/target of rapamycin (TOR) signal transduction pathway. This well-characterized pathway plays a key role in fundamental processes such as energetic metabolism, growth, reproduction, and aging and is involved in metabolic disorders such as obesity, insulin resistance, and diabetes. For that purpose, we combined genotype data from worldwide human populations with current knowledge of the structure and function of the pathway. We identified the footprint of recent positive selection in nine of the studied genomic regions. Most of the adaptation signals were observed among Middle East and North African, European, and Central South Asian populations. We found that positive selection preferentially targets the most central elements in the pathway, in contrast to previous observations in the whole human interactome. This observation indicates that the impact of positive selection on genes involved in the insulin/TOR pathway is affected by the pathway structure. © The Author 2011.

[Background] Asparagine N-Glycosylation is one of the most important forms of protein post-translational modification in eukaryotes. This metabolic pathway can be subdivided into two parts: an upstream sub-pathway required for achieving proper folding for most of the proteins synthesized in the secretory pathway, and a downstream sub-pathway required to give variability to trans-membrane proteins, and involved in adaptation to the environment and innate immunity. Here we analyze the nucleotide variability of the genes of this pathway in human populations, identifying which genes show greater population differentiation and which genes show signatures of recent positive selection. We also compare how these signals are distributed between the upstream and the downstream parts of the pathway, with the aim of exploring how forces of population differentiation and positive selection vary among genes involved in the same metabolic pathway but subject to different functional constraints., [Results] Our results show that genes in the downstream part of the pathway are more likely to show a signature of population differentiation, while events of positive selection are equally distributed among the two parts of the pathway. Moreover, events of positive selection are frequent on genes that are known to be at bifurcation points, and that are identified as being in key position by a network-level analysis such as MGAT3 and GCS1., [Conclusions] These findings indicate that the upstream part of the Asparagine N-Glycosylation pathway has lower diversity among populations, while the downstream part is freer to tolerate diversity among populations. Moreover, the distribution of signatures of population differentiation and positive selection can change between parts of a pathway, especially between parts that are exposed to different functional constraints. Our results support the hypothesis that genes involved in constitutive processes can be expected to show lower population differentiation, while genes involved in traits related to the environment should show higher variability. Taken together, this work broadens our knowledge on how events of population differentiation and of positive selection are distributed among different parts of a metabolic pathway.