Guillaume Laval

Natural selection has driven population differentiation in modern humans

The considerable range of observed phenotypic variation in human populations may reflect, in part, distinctive processes of natural selection and adaptation to variable environmental conditions. Although recent genome-wide studies have identified candidate regions under selection, it is not yet clear how natural selection has shaped population differentiation. Here, we have analyzed the degree of population differentiation at 2.8 million Phase II HapMap single-nucleotide polymorphisms. We find that negative selection has globally reduced population differentiation at amino acid–altering mutations, particularly in disease-related genes. Conversely, positive selection has ensured the regional adaptation of human populations by increasing population differentiation in gene regions, primarily at nonsynonymous and 5′-UTR variants. Our analyses identify a fraction of loci that have contributed, and probably still contribute, to the morphological and disease-related phenotypic diversity of current human populations.

Evolutionary dynamics of human Toll-like receptors and their different contributions to host defense.

Infectious diseases have been paramount among the threats to health and survival throughout human evolutionary history. Natural selection is therefore expected to act strongly on host defense genes, particularly on innate immunity genes whose products mediate the direct interaction between the host and the microbial environment. In insects and mammals, the Toll-like receptors (TLRs) appear to play a major role in initiating innate immune responses against microbes. In humans, however, it has been speculated that the set of TLRs could be redundant for protective immunity. We investigated how natural selection has acted upon human TLRs, as an approach to assess their level of biological redundancy. We sequenced the ten human TLRs in a panel of 158 individuals from various populations worldwide and found that the intracellular TLRs—activated by nucleic acids and particularly specialized in viral recognition—have evolved under strong purifying selection, indicating their essential non-redundant role in host survival. Conversely, the selective constraints on the TLRs expressed on the cell surface—activated by compounds other than nucleic acids—have been much more relaxed, with higher rates of damaging nonsynonymous and stop mutations tolerated, suggesting their higher redundancy. Finally, we tested whether TLRs have experienced spatially-varying selection in human populations and found that the region encompassing TLR10-TLR1-TLR6 has been the target of recent positive selection among non-Africans. Our findings indicate that the different TLRs differ in their immunological redundancy, reflecting their distinct contributions to host defense. The insights gained in this study foster new hypotheses to be tested in clinical and epidemiological genetics of infectious disease.

Evolutionary genetic dissection of human interferons

As revealed by population genetic analyses, different human interferon genes evolved under distinct selective constraints and signatures of positive selection vary according to geographic region, suggesting that some sequence changes may have conferred an advantage by increasing resistance to viral infection.

Formulating a Historical and Demographic Model of Recent Human Evolution Based on Resequencing Data from Noncoding Regions

Background Estimating the historical and demographic parameters that characterize modern human populations is a fundamental part of reconstructing the recent history of our species. In addition, the development of a model of human evolution that can best explain neutral genetic diversity is required to identify confidently regions of the human genome that have been targeted by natural selection. Methodology/Principal Findings We have resequenced 20 independent noncoding autosomal regions dispersed throughout the genome in 213 individuals from different continental populations, corresponding to a total of ∼6 Mb of diploid resequencing data. We used these data to explore and co-estimate an extensive range of historical and demographic parameters with a statistical framework that combines the evaluation of multiple models of human evolution via a best-fit approach, followed by an Approximate Bayesian Computation (ABC) analysis. From a methodological standpoint, evaluating the accuracy of the parameter co-estimation allowed us to identify the most accurate set of statistics to be used for the estimation of each of the different historical and demographic parameters characterizing recent human evolution. Conclusions/Significance Our results support a model in which modern humans left Africa through a single major dispersal event occurring ∼60,000 years ago, corresponding to a drastic reduction of ∼5 times the effective population size of the ancestral African population of ∼13,800 individuals. Subsequently, the ancestors of modern Europeans and East Asians diverged much later, ∼22,500 years ago, from the population of ancestral migrants. This late diversification of Eurasians after the African exodus points to the occurrence of a long maturation phase in which the ancestral Eurasian population was not yet diversified.

Causal mechanisms and balancing selection inferred from genetic associations with polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is the most common reproductive disorder in women, yet there is little consensus regarding its aetiology. Here we perform a genome-wide association study of PCOS in up to 5,184 self-reported cases of White European ancestry and 82,759 controls, with follow-up in a further ∼2,000 clinically validated cases and ∼100,000 controls. We identify six signals for PCOS at genome-wide statistical significance (P<5 × 10−8), in/near genes ERBB4/HER4, YAP1, THADA, FSHB, RAD50 and KRR1. Variants in/near three of the four epidermal growth factor receptor genes (ERBB2/HER2, ERBB3/HER3 and ERBB4/HER4) are associated with PCOS at or near genome-wide significance. Mendelian randomization analyses indicate causal roles in PCOS aetiology for higher BMI (P=2.5 × 10−9), higher insulin resistance (P=6 × 10−4) and lower serum sex hormone binding globulin concentrations (P=5 × 10−4). Furthermore, genetic susceptibility to later menopause is associated with higher PCOS risk (P=1.6 × 10−8) and PCOS-susceptibility alleles are associated with higher serum anti-Müllerian hormone concentrations in girls (P=8.9 × 10−5). This large-scale study implicates an aetiological role of the epidermal growth factor receptors, infers causal mechanisms relevant to clinical management and prevention, and suggests balancing selection mechanisms involved in PCOS risk.

Genomic Signatures of Selective Pressures and Introgression from Archaic Hominins at Human Innate Immunity Genes

Human genes governing innate immunity provide a valuable tool for the study of the selective pressure imposed by microorganisms on host genomes. A comprehensive, genome-wide study of how selective constraints and adaptations have driven the evolution of innate immunity genes is missing. Using full-genome sequence variation from the 1000 Genomes Project, we first show that innate immunity genes have globally evolved under stronger purifying selection than the remainder of protein-coding genes. We identify a gene set under the strongest selective constraints, mutations in which are likely to predispose individuals to life-threatening disease, as illustrated by STAT1 and TRAF3. We then evaluate the occurrence of local adaptation and detect 57 high-scoring signals of positive selection at innate immunity genes, variation in which has been associated with susceptibility to common infectious or autoimmune diseases. Furthermore, we show that most adaptations targeting coding variation have occurred in the last 6,000-13,000 years, the period at which populations shifted from hunting and gathering to farming. Finally, we show that innate immunity genes present higher Neandertal introgression than the remainder of the coding genome. Notably, among the genes presenting the highest Neandertal ancestry, we find the TLR6-TLR1-TLR10 cluster, which also contains functional adaptive variation in Europeans. This study identifies highly constrained genes that fulfill essential, non-redundant functions in host survival and reveals others that are more permissive to change-containing variation acquired from archaic hominins or adaptive variants in specific populations-improving our understanding of the relative biological importance of innate immunity pathways in natural conditions.

Genetic Adaptation and Neandertal Admixture Shaped the Immune System of Human Populations

Summary Humans differ in the outcome that follows exposure to life-threatening pathogens, yet the extent of population differences in immune responses and their genetic and evolutionary determinants remain undefined. Here, we characterized, using RNA sequencing, the transcriptional response of primary monocytes from Africans and Europeans to bacterial and viral stimuli—ligands activating Toll-like receptor pathways (TLR1/2, TLR4, and TLR7/8) and influenza virus—and mapped expression quantitative trait loci (eQTLs). We identify numerous cis-eQTLs that contribute to the marked differences in immune responses detected within and between populations and a strong trans-eQTL hotspot at TLR1 that decreases expression of pro-inflammatory genes in Europeans only. We find that immune-responsive regulatory variants are enriched in population-specific signals of natural selection and show that admixture with Neandertals introduced regulatory variants into European genomes, affecting preferentially responses to viral challenges. Together, our study uncovers evolutionarily important determinants of differences in host immune responsiveness between human populations.

Exploring the Occurrence of Classic Selective Sweeps in Humans Using Whole-Genome Sequencing Data Sets

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.

Detecting genomic signatures of natural selection with principal component analysis: application to the 1000 Genomes data

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.

A genomic portrait of the genetic architecture and regulatory impact of microRNA expression in response to infection

MicroRNAs (miRNAs) are critical regulators of gene expression, and their role in a wide variety of biological processes, including host antimicrobial defense, is increasingly well described. Consistent with their diverse functional effects, miRNA expression is highly context dependent and shows marked changes upon cellular activation. However, the genetic control of miRNA expression in response to external stimuli and the impact of such perturbations on miRNA-mediated regulatory networks at the population level remain to be determined. Here we assessed changes in miRNA expression upon Mycobacterium tuberculosis infection and mapped expression quantitative trait loci (eQTL) in dendritic cells from a panel of healthy individuals. Genome-wide expression profiling revealed that ∼40% of miRNAs are differentially expressed upon infection. We find that the expression of 3% of miRNAs is controlled by proximate genetic factors, which are enriched in a promoter-specific histone modification associated with active transcription. Notably, we identify two infection-specific response eQTLs, for miR-326 and miR-1260, providing an initial assessment of the impact of genotype-environment interactions on miRNA molecular phenotypes. Furthermore, we show that infection coincides with a marked remodeling of the genome-wide relationships between miRNA and mRNA expression levels. This observation, supplemented by experimental data using the model of miR-29a, sheds light on the role of a set of miRNAs in cellular responses to infection. Collectively, this study increases our understanding of the genetic architecture of miRNA expression in response to infection, and highlights the wide-reaching impact of altering miRNA expression on the transcriptional landscape of a cell.