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The Roma Diaspora-traditionally known as Gypsies-remains among the least explored population migratory events in historical times. It involved the migration of Roma ancestors out-of-India through the plateaus of Western Asia ultimately reaching Europe. The demographic effects of the Diaspora-bottlenecks, endogamy, and gene flow-might have left marked molecular traces in the Roma genomes. Here, we analyze the whole-genome sequence of 46 Roma individuals pertaining to four migrant groups in six European countries. Our analyses revealed a strong, early founder effect followed by a drastic reduction of ∼44% in effective population size. The Roma common ancestors split from the Punjabi population, from Northwest India, some generations before the Diaspora started, <2,000 years ago. The initial bottleneck and subsequent endogamy are revealed by the occurrence of extensive runs of homozygosity and identity-by-descent segments in all Roma populations. Furthermore, we provide evidence of gene flow from Armenian and Anatolian groups in present-day Roma, although the primary contribution to Roma gene pool comes from non-Roma Europeans, which accounts for >50% of their genomes. The linguistic and historical differentiation of Roma in migrant groups is confirmed by the differential proportion, but not a differential source, of European admixture in the Roma groups, which shows a westward cline. In the present study, we found that despite the strong admixture Roma had in their diaspora, the signature of the initial bottleneck and the subsequent endogamy is still present in Roma genomes., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

To characterize natural selection, various analytical methods for detecting candidate genomic regions have been developed. We propose to perform genome-wide scans of natural selection using principal component analysis (PCA). We show that the common FST index of genetic differentiation between populations can be viewed as the proportion of variance explained by the principal components. Considering the correlations between genetic variants and each principal component provides a conceptual framework to detect genetic variants involved in local adaptation without any prior definition of populations. To validate the PCA-based approach, we consider the 1000 Genomes data (phase 1) considering 850 individuals coming from Africa, Asia, and Europe. The number of genetic variants is of the order of 36 millions obtained with a low-coverage sequencing depth (3×). The correlations between genetic variation and each principal component provide well-known targets for positive selection (EDAR, SLC24A5, SLC45A2, DARC), and also new candidate genes (APPBPP2, TP1A1, RTTN, KCNMA, MYO5C) and noncoding RNAs. In addition to identifying genes involved in biological adaptation, we identify two biological pathways involved in polygenic adaptation that are related to the innate immune system (beta defensins) and to lipid metabolism (fatty acid omega oxidation). An additional analysis of European data shows that a genome scan based on PCA retrieves classical examples of local adaptation even when there are no well-defined populations. PCA-based statistics, implemented in the PCAdapt R package and the PCAdapt fast open-source software, retrieve well-known signals of human adaptation, which is encouraging for future whole-genome sequencing project, especially when defining populations is difficult., (© The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Genome-wide scans for selection have identified multiple regions of the human genome as being targeted by positive selection. However, only a small proportion has been replicated across studies, and the prevalence of positive selection as a mechanism of adaptive change in humans remains controversial. Here we explore the power of two haplotype-based statistics--the integrated haplotype score (iHS) and the Derived Intraallelic Nucleotide Diversity (DIND) test--in the context of next-generation sequencing data, and evaluate their robustness to demography and other selection modes. We show that these statistics are both powerful for the detection of recent positive selection, regardless of population history, and robust to variation in coverage, with DIND being insensitive to very low coverage. We apply these statistics to whole-genome sequence data sets from the 1000 Genomes Project and Complete Genomics. We found that putative targets of selection were highly significantly enriched in genic and nonsynonymous single nucleotide polymorphisms, and that DIND was more powerful than iHS in the context of small sample sizes, low-quality genotype calling, or poor coverage. As we excluded genomic confounders and alternative selection models, such as background selection, the observed enrichment attests to the action of recent, strong positive selection. Further support to the adaptive significance of these genomic regions came from their enrichment in functional variants detected by genome-wide association studies, informing the relationship between past selection and current benign and disease-related phenotypic variation. Our results indicate that hard sweeps targeting low-frequency standing variation have played a moderate, albeit significant, role in recent human evolution., (© The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Demographic changes are known to leave footprints on genetic polymorphism. Together with the increased availability of large polymorphism data sets, coalescent-based methods allow inferring the past demography of populations from their present-day patterns of genetic diversity. Here, we analyzed both nuclear (20 noncoding regions) and mitochondrial (HVS-I) resequencing data to infer the demographic history of 66 African and Eurasian human populations presenting contrasting lifestyles (nomadic hunter-gatherers, nomadic herders, and sedentary farmers). This allowed us to investigate the relationship between lifestyle and demography and to address the long-standing debate about the chronology of demographic expansions and the Neolithic transition. In Africa, we inferred expansion events for farmers, but constant population sizes or contraction events for hunter-gatherers. In Eurasia, we inferred higher expansion rates for farmers than herders with HVS-I data, except in Central Asia and Korea. Although isolation and admixture processes could have impacted our demographic inferences, these processes alone seem unlikely to explain the contrasted demographic histories inferred in populations with different lifestyles. The small expansion rates or constant population sizes inferred for herders and hunter-gatherers may thus result from constraints linked to nomadism. However, autosomal data revealed contraction events for two sedentary populations in Eurasia, which may be caused by founder effects. Finally, the inferred expansions likely predated the emergence of agriculture and herding. This suggests that human populations could have started to expand in Paleolithic times, and that strong Paleolithic expansions in some populations may have ultimately favored their shift toward agriculture during the Neolithic.

Natural selection is expected to act strongly on immune system genes as hosts adapt to novel, diverse, and coevolving pathogens. Population genetic studies of host defense genes with parallel functions in model organisms have revealed distinct evolutionary histories among the different components-receptors, adaptors, and effectors-of the innate immune system. In humans, however, detailed evolutionary studies have been mainly confined to the receptors and in particular to Toll-like receptors (TLRs). By virtue of a toll/interleukin-1 receptor (TIR) domain, TLRs activate distinct signaling pathways, which are mediated by the five TIR-containing adaptors: myeloid differentiation factor-88 (MyD88), myeloid differentiation factor-88 adaptor-like protein (MAL), toll/interleukin-1 receptor domain-containing adaptor protein inducing interferon (IFN)β (TRIF), toll/interleukin-1 receptor domain-containing adaptor protein inducing IFNβ-related adaptor molecule (TRAM), and sterile α- and armadillo motif-containing protein (SARM). Here, we have examined the extent to which natural selection has affected immune adaptors in humans, using as a paradigm the TIR-containing adaptors. To do so, we characterized their levels of naturally occurring genetic variation in various human populations. We found that MyD88 and TRIF have mainly evolved under purifying selection, suggesting that their role in the early stages of signal transduction is essential and nonredundant for host survival. In addition, the adaptors have been targeted by multiple episodes of positive selection, differing in timing and spatial location. MyD88 and SARM display signatures of a selective sweep that has occurred in all humans, whereas for the other three adaptors, we detected signatures of adaptive evolution that are restricted to specific populations. Our study provides evidence that the contemporary diversity of the five TIR-containing adaptors results from the intermingling of different selective events, swinging between constraint and adaptation.