The Simons Genome Diversity Project: 300 genomes from 142 diverse populations.

Here we report the Simons Genome Diversity Project data set: high quality genomes from 300 individuals from 142 diverse populations. These genomes include at least 5.8 million base pairs that are not present in the human reference genome. Our analysis reveals key features of the landscape of human genome variation, including that the rate of accumulation of mutations has accelerated by about 5% in non-Africans compared to Africans since divergence. We show that the ancestors of some pairs of present-day human populations were substantially separated by 100,000 years ago, well before the archaeologically attested onset of behavioural modernity. We also demonstrate that indigenous Australians, New Guineans and Andamanese do not derive substantial ancestry from an early dispersal of modern humans; instead, their modern human ancestry is consistent with coming from the same source as that of other non-Africans.

Detecting past and ongoing natural selection among ethnically Tibetan women at high altitude in Nepal.

Adaptive evolution in humans has rarely been characterized for its whole set of components, i.e. selective pressure, adaptive phenotype, beneficial alleles and realized fitness differential. We combined approaches for detecting polygenic adaptations and for mapping the genetic bases of physiological and fertility phenotypes in approximately 1000 indigenous ethnically Tibetan women from Nepal, adapted to high altitude. The results of genome-wide association analyses and tests for polygenic adaptations showed evidence of positive selection for alleles associated with more pregnancies and live births and evidence of negative selection for those associated with higher offspring mortality. Lower hemoglobin level did not show clear evidence for polygenic adaptation, despite its strong association with an EPAS1 haplotype carrying selective sweep signals.

Genetic variant at coronary artery disease and ischemic stroke locus 1p32.2 regulates endothelial responses to hemodynamics.

Biomechanical cues dynamically control major cellular processes, but whether genetic variants actively participate in mechanosensing mechanisms remains unexplored. Vascular homeostasis is tightly regulated by hemodynamics. Exposure to disturbed blood flow at arterial sites of branching and bifurcation causes constitutive activation of vascular endothelium contributing to atherosclerosis, the major cause of coronary artery disease (CAD) and ischemic stroke (IS). Conversely, unidirectional flow promotes quiescent endothelium. Genome-wide association studies (GWAS) have identified chromosome 1p32.2 as strongly associated with CAD/IS; however, the causal mechanism related to this locus remains unknown. Using statistical analyses, assay of transposase accessible chromatin with whole-genome sequencing (ATAC-seq), H3K27ac/H3K4me2 ChIP with whole-genome sequencing (ChIP-seq), and CRISPR interference in human aortic endothelial cells (HAECs), our results demonstrate that rs17114036, a common noncoding polymorphism at 1p32.2, is located in an endothelial enhancer dynamically regulated by hemodynamics. CRISPR-Cas9-based genome editing shows that rs17114036-containing region promotes endothelial quiescence under unidirectional shear stress by regulating phospholipid phosphatase 3 (PLPP3). Chromatin accessibility quantitative trait locus (caQTL) mapping using HAECs from 56 donors, allelic imbalance assay from 7 donors, and luciferase assays demonstrate that CAD/IS-protective allele at rs17114036 in PLPP3 intron 5 confers increased endothelial enhancer activity. ChIP-PCR and luciferase assays show that CAD/IS-protective allele at rs17114036 creates a binding site for transcription factor Krüppel-like factor 2 (KLF2), which increases the enhancer activity under unidirectional flow. These results demonstrate that a human SNP contributes to critical endothelial mechanotransduction mechanisms and suggest that human haplotypes and related cis-regulatory elements provide a previously unappreciated layer of regulatory control in cellular mechanosensing mechanisms.

Inferring the model and onset of natural selection under varying population size from the site frequency spectrum and haplotype structure.

A fundamental question about adaptation in a population is the time of onset of the selective pressure acting on beneficial alleles. Inferring this time, in turn, depends on the selection model. We develop a framework of approximate Bayesian computation (ABC) that enables the use of the full site frequency spectrum and haplotype structure to test the goodness-of-fit of selection models and estimate the timing of selection under varying population size scenarios. We show that our method has sufficient power to distinguish natural selection from neutrality even if relatively old selection increased the frequency of a pre-existing allele from 20% to 50% or from 40% to 80%. Our ABC can accurately estimate the time of onset of selection on a new mutation. However, estimates are prone to bias under the standing variation model, possibly due to the uncertainty in the allele frequency at the onset of selection. We further extend our approach to take advantage of ancient DNA data that provides information on the allele frequency path of the beneficial allele. Applying our ABC, including both modern and ancient human DNA data, to four pigmentation alleles in Europeans, we detected selection on standing variants that occurred after the dispersal from Africa even though models of selection on a new mutation were initially supported for two of these alleles without the ancient data.

Long-term genetic stability and a high-altitude East Asian origin for the peoples of the high valleys of the Himalayan arc.

The high-altitude transverse valleys [>3,000 m above sea level (masl)] of the Himalayan arc from Arunachal Pradesh to Ladahk were among the last habitable places permanently colonized by prehistoric humans due to the challenges of resource scarcity, cold stress, and hypoxia. The modern populations of these valleys, who share cultural and linguistic affinities with peoples found today on the Tibetan plateau, are commonly assumed to be the descendants of the earliest inhabitants of the Himalayan arc. However, this assumption has been challenged by archaeological and osteological evidence suggesting that these valleys may have been originally populated from areas other than the Tibetan plateau, including those at low elevation. To investigate the peopling and early population history of this dynamic high-altitude contact zone, we sequenced the genomes (0.04×-7.25×, mean 2.16×) and mitochondrial genomes (20.8×-1,311.0×, mean 482.1×) of eight individuals dating to three periods with distinct material culture in the Annapurna Conservation Area (ACA) of Nepal, spanning 3,150-1,250 y before present (yBP). We demonstrate that the region is characterized by long-term stability of the population genetic make-up despite marked changes in material culture. The ancient genomes, uniparental haplotypes, and high-altitude adaptive alleles suggest a high-altitude East Asian origin for prehistoric Himalayan populations.

Genetic structure in the Sherpa and neighboring Nepalese populations.

BACKGROUND: We set out to describe the fine-scale population structure across the Eastern region of Nepal. To date there is relatively little known about the genetic structure of the Sherpa residing in Nepal and their genetic relationship with the Nepalese. We assembled dense genotype data from a total of 1245 individuals representing Nepal and a variety of different populations resident across the greater Himalayan region including Tibet, China, India, Pakistan, Kazakhstan, Uzbekistan, Tajikistan and Kirghizstan. We performed analysis of principal components, admixture and homozygosity. RESULTS: We identified clear substructure across populations resident in the Himalayan arc, with genetic structure broadly mirroring geographical features of the region. Ethnic subgroups within Nepal show distinct genetic structure, on both admixture and principal component analysis. We detected differential proportions of ancestry from northern Himalayan populations across Nepalese subgroups, with the Nepalese Rai, Magar and Tamang carrying the greatest proportions of Tibetan ancestry. CONCLUSIONS: We show that populations dwelling on the Himalayan plateau have had a clear impact on the Northern Indian gene pool. We illustrate how the Sherpa are a remarkably isolated population, with little gene flow from surrounding Nepalese populations.

Estimating the Ages of Selection Signals from Different Epochs in Human History.

Genetic variation harbors signatures of natural selection driven by selective pressures that are often unknown. Estimating the ages of selection signals may allow reconstructing the history of environmental changes that shaped human phenotypes and diseases. We have developed an approximate Bayesian computation (ABC) approach to estimate allele ages under a model of selection on new mutations and under demographic models appropriate for human populations. We have applied it to two resequencing data sets: An ultra-high depth data set from a relatively small sample of unrelated individuals and a lower depth data set in a larger sample with transmission information. In addition to evaluating the accuracy of our method based on simulations, for each SNP, we assessed the consistency between the posterior probabilities estimated by the ABC approach and the ancient DNA record, finding good agreement between the two types of data and methods. Applying this ABC approach to data for eight single nucleotide polymorphisms (SNPs), we were able to rule out an onset of selection prior to the dispersal out-of-Africa for three of them and more recent than the spread of agriculture for an additional three SNPs.

Strong artificial selection in domestic mammals did not result in an increased recombination rate.

Recombination rates vary in intensity and location at the species, individual, sex and chromosome levels. Despite the fundamental biological importance of this process, the selective forces that operate to shape recombination rate and patterns are unclear. Domestication offers a unique opportunity to study the interplay between recombination and selection. In domesticates, intense selection for particular traits is imposed on small populations over many generations, resulting in organisms that differ, sometimes dramatically, in morphology and physiology from their wild ancestor. Although earlier studies suggested increased recombination rate in domesticates, a formal comparison of recombination rates between domestic mammals and their wild congeners was missing. In order to determine broad-scale recombination rate, we used immunolabeling detection of MLH1 foci as crossover markers in spermatocytes in three pairs of closely related wild and domestic species (dog and wolf, goat and ibex, and sheep and mouflon). In the three pairs, and contrary to previous suggestions, our data show that contemporary recombination rate is higher in the wild species. Subsequently, we inferred recombination breakpoints in sequence data for 16 genomic regions in dogs and wolves, each containing a locus associated with a dog phenotype potentially under selection during domestication. No difference in the number and distribution of recombination breakpoints was found between dogs and wolves. We conclude that our data indicate that strong directional selection did not result in changes in recombination in domestic mammals, and that both upper and lower bounds for crossover rates may be tightly regulated.

Genetic mapping with multiple levels of phenotypic information reveals determinants of lymphocyte glucocorticoid sensitivity.

Clinical response to glucocorticoids, steroid hormones widely used as pharmaceuticals, varies extensively in that many individuals (∼30%) show a weak response to treatment. Although little is known about the molecular basis of this variation, regulatory polymorphisms are likely to play a key role given that glucocorticoids act largely through activation of a transcription factor, the glucocorticoid receptor. In an effort to characterize the molecular basis of variation in glucocorticoid sensitivity, we measured in vitro lymphocyte glucocorticoid sensitivity and transcriptome-wide response to glucocorticoids in peripheral-blood mononuclear cells from African American healthy donors. We found that variation in lymphocyte glucocorticoid sensitivity was correlated with transcriptional response at 27 genes (false-discovery rate < 0.1). Furthermore, a genome-wide association scan revealed a quantitative trait locus (QTL) for lymphocyte glucocorticoid sensitivity (rs11129354, p = 4 × 10(-8)); it was also associated with transcriptional response at multiple genes, including many (14/27) where transcriptional response was correlated with lymphocyte glucocorticoid sensitivity. Using allelic-imbalance assays, we show that this QTL is a glucocorticoid-dependent cis-regulatory polymorphism for RBMS3, which encodes an RNA-binding protein known as a tumor suppressor. We found that siRNA-mediated knockdown of RBMS3 expression increased cellular proliferation in PBMCs, consistent with the role of the gene as a negative regulator of proliferation. We propose that differences in lymphocyte glucocorticoid sensitivity reflect variation in transcriptional response, which is influenced by a glucocorticoid-dependent regulatory polymorphism that acts in cis relative to RBMS3 and in trans to affect the transcriptional response of multiple distant genes.

Adaptation - not by sweeps alone.

There has been recent progress in identifying selective sweeps underlying a range of adaptations. Jonathan Pritchard and Anna Di Rienzo argue that many adaptive events in natural populations may occur by polygenic adaptation, which would largely go undetected by conventional methods for detecting selection.

Spatial patterns of variation due to natural selection in humans.

Empowered by technology and sampling efforts designed to facilitate genome-wide association mapping, human geneticists are now studying the geography of genetic variation in unprecedented detail. With high genomic coverage and geographic resolution, these studies are identifying loci with spatial signatures of selection, such as extreme levels of differentiation and correlations with environmental variables. Collectively, patterns at these loci are beginning to provide new insights into the process of human adaptation. Here, we review the challenges of these studies and emerging results, including how human population structure has influenced the response to novel selective pressures.

The genetic architecture of adaptations to high altitude in Ethiopia.

Although hypoxia is a major stress on physiological processes, several human populations have survived for millennia at high altitudes, suggesting that they have adapted to hypoxic conditions. This hypothesis was recently corroborated by studies of Tibetan highlanders, which showed that polymorphisms in candidate genes show signatures of natural selection as well as well-replicated association signals for variation in hemoglobin levels. We extended genomic analysis to two Ethiopian ethnic groups: Amhara and Oromo. For each ethnic group, we sampled low and high altitude residents, thus allowing genetic and phenotypic comparisons across altitudes and across ethnic groups. Genome-wide SNP genotype data were collected in these samples by using Illumina arrays. We find that variants associated with hemoglobin variation among Tibetans or other variants at the same loci do not influence the trait in Ethiopians. However, in the Amhara, SNP rs10803083 is associated with hemoglobin levels at genome-wide levels of significance. No significant genotype association was observed for oxygen saturation levels in either ethnic group. Approaches based on allele frequency divergence did not detect outliers in candidate hypoxia genes, but the most differentiated variants between high- and lowlanders have a clear role in pathogen defense. Interestingly, a significant excess of allele frequency divergence was consistently detected for genes involved in cell cycle control and DNA damage and repair, thus pointing to new pathways for high altitude adaptations. Finally, a comparison of CpG methylation levels between high- and lowlanders found several significant signals at individual genes in the Oromo.

Discovery and functional assessment of gene variants in the vascular endothelial growth factor pathway.

Angiogenesis is a host-mediated mechanism in disease pathophysiology. The vascular endothelial growth factor (VEGF) pathway is a major determinant of angiogenesis, and a comprehensive annotation of the functional variation in this pathway is essential to understand the genetic basis of angiogenesis-related diseases. We assessed the allelic heterogeneity of gene expression, population specificity of cis expression quantitative trait loci (eQTLs), and eQTL function in luciferase assays in CEU and Yoruba people of Ibadan, Nigeria (YRI) HapMap lymphoblastoid cell lines in 23 resequenced genes. Among 356 cis-eQTLs, 155 and 174 were unique to CEU and YRI, respectively, and 27 were shared between CEU and YRI. Two cis-eQTLs provided mechanistic evidence for two genome-wide association study findings. Five eQTLs were tested for function in luciferase assays and the effect of two KRAS variants was concordant with the eQTL effect. Two eQTLs found in each of PRKCE, PIK3C2A, and MAP2K6 could predict 44%, 37%, and 45% of the variance in gene expression, respectively. This is the first analysis focusing on the pattern of functional genetic variation of the VEGF pathway genes in CEU and YRI populations and providing mechanistic evidence for genetic association studies of diseases for which angiogenesis plays a pathophysiologic role.

Gene expression of peripheral blood cells reveals pathways downstream of glucocorticoid receptor antagonism and nab-paclitaxel treatment.

OBJECTIVES: Whereas paclitaxel treatment is associated with leukopenia, the mechanisms that underlie this effect are not well-characterized. In addition, despite the importance of glucocorticoid signaling in cancer treatment, the genomic effects of glucocorticoid receptor antagonism by mifepristone treatment in primary human cells have never been described. METHODS: As part of a randomized phase 1 clinical trial, we used microarrays to profile gene expression in peripheral blood cells sampled from each of four patients at baseline, after placebo/nanoparticle albumin-bound paclitaxel (nab-paclitaxel) treatment (cycle 1), and after mifepristone/nab-paclitaxel treatment (cycle 2). RESULTS: We found that 63 genes were differentially expressed following treatment with nab-paclitaxel, including multiple genes in the tubulin pathway. We also found 606 genes that were differentially expressed in response to mifepristone; genes downregulated by mifepristone overlapped significantly with those previously identified as being upregulated by dexamethasone. CONCLUSION: These results provide insights into the mechanisms of paclitaxel and glucocorticoid receptor inhibition in peripheral blood cells.

A reduced representation approach to population genetic analyses and applications to human evolution.

Second-generation sequencing technologies allow surveys of sequence variation on an unprecedented scale. However, despite the rapid decrease in sequencing costs, collecting whole-genome sequence data on a population scale is still prohibitive for many laboratories. We have implemented an inexpensive, reduced representation protocol for preparing resequencing targets, and we have developed the analytical tools necessary for making population genetic inferences. This approach can be applied to any species for which a draft or complete reference genome sequence is available. The new tools we have developed include methods for aligning reads, calling genotypes, and incorporating sample-specific sequencing error rates in the estimate of evolutionary parameters. When applied to 19 individuals from a total of 18 human populations, our approach allowed sampling regions that are largely overlapping across individuals and that are representative of the entire genome. The resequencing data were used to test the serial founder model of human dispersal and to estimate the time of the Out of Africa migration. Our results also represent the first attempt to provide a time frame for the colonization of Australia based on large-scale resequencing data.

Interactions between glucocorticoid treatment and cis-regulatory polymorphisms contribute to cellular response phenotypes.

Glucocorticoids (GCs) mediate physiological responses to environmental stress and are commonly used as pharmaceuticals. GCs act primarily through the GC receptor (GR, a transcription factor). Despite their clear biomedical importance, little is known about the genetic architecture of variation in GC response. Here we provide an initial assessment of variability in the cellular response to GC treatment by profiling gene expression and protein secretion in 114 EBV-transformed B lymphocytes of African and European ancestry. We found that genetic variation affects the response of nearby genes and exhibits distinctive patterns of genotype-treatment interactions, with genotypic effects evident in either only GC-treated or only control-treated conditions. Using a novel statistical framework, we identified interactions that influence the expression of 26 genes known to play central roles in GC-related pathways (e.g. NQO1, AIRE, and SGK1) and that influence the secretion of IL6.

Adaptations to climate-mediated selective pressures in humans.

Humans inhabit a remarkably diverse range of environments, and adaptation through natural selection has likely played a central role in the capacity to survive and thrive in extreme climates. Unlike numerous studies that used only population genetic data to search for evidence of selection, here we scan the human genome for selection signals by identifying the SNPs with the strongest correlations between allele frequencies and climate across 61 worldwide populations. We find a striking enrichment of genic and nonsynonymous SNPs relative to non-genic SNPs among those that are strongly correlated with these climate variables. Among the most extreme signals, several overlap with those from GWAS, including SNPs associated with pigmentation and autoimmune diseases. Further, we find an enrichment of strong signals in gene sets related to UV radiation, infection and immunity, and cancer. Our results imply that adaptations to climate shaped the spatial distribution of variation in humans.

Natural selection and functional genetic variation in the p53 pathway.

The allele frequencies of two functional single-nucleotide polymorphisms (SNPs) in the p53 pathway, the MDM2 SNP309 and TP53 Arg72Pro, vary dramatically among populations. That the frequencies of the TP53 SNP follow a clinal distribution may suggest that selective pressure from environmental variables correlated with latitude contributed to these observed population differences. Recently, winter temperature and UV radiation were found to be significantly correlated with the TP53 and the MDM2 SNPs, respectively, in East Asians; whether these correlations are more extreme than expected based upon nonselective factors such as patterns of human migration remains unclear. Here, we genotyped these two SNPs in 971 unrelated individuals from 52 unique populations worldwide and tested for correlations with both latitude and a number of climate-related environmental variables on a global scale, controlling for these neutral processes. The TP53 SNP was associated with a significant selection signal for a few climate variables, such as short-wave radiation flux in the winter, but these signals were no longer significant after correction for multiple tests. The MDM2 SNP did not exhibit a significant signal with any climate variable. Therefore, these SNPs are unlikely to be under selective pressure driven by these variables. Thus, these data underscore the need to incorporate population history when assessing signatures of selection.

Allele-specific down-regulation of RPTOR expression induced by retinoids contributes to climate adaptations.

The mechanistic target of rapamycin (MTOR) pathway regulates cell growth, energy homeostasis, apoptosis, and immune response. The regulatory associated protein of MTOR encoded by the RPTOR gene is a key component of this pathway. A previous survey of candidate genes found that RPTOR contains multiple SNPs with strong correlations between allele frequencies and climate variables, consistent with the action of selective pressures that vary across environments. Using data from a recent genome scan for selection signals, we honed in on a SNP (rs11868112) 26 kb upstream to the transcription start site of RPTOR that exhibits the strongest association with temperature variables. Transcription factor motif scanning and mining of recently mapped transcription factor binding sites identified a binding site for POU class 2 homeobox 1 (POU2F1) spanning the SNP and an adjacent retinoid acid receptor (RAR) binding site. Using expression quantification, chromatin immunoprecipitation (ChIP), and reporter gene assays, we demonstrate that POU2F1 and RARA do bind upstream of the RPTOR gene to regulate its expression in response to retinoids; this regulation is affected by the allele status at rs11868112 with the derived allele resulting in lower expression levels. We propose a model in which the derived allele influences thermogenesis or immune response by altering MTOR pathway activity and thereby increasing fitness in colder climates. Our results show that signatures of genetic adaptations can identify variants with functional effects, consistent with the idea that selection signals may be used for SNP annotation.

Colloquium paper: human adaptations to diet, subsistence, and ecoregion are due to subtle shifts in allele frequency.

Human populations use a variety of subsistence strategies to exploit an exceptionally broad range of ecoregions and dietary components. These aspects of human environments have changed dramatically during human evolution, giving rise to new selective pressures. To understand the genetic basis of human adaptations, we combine population genetics data with ecological information to detect variants that increased in frequency in response to new selective pressures. Our approach detects SNPs that show concordant differences in allele frequencies across populations with respect to specific aspects of the environment. Genic and especially nonsynonymous SNPs are overrepresented among those most strongly correlated with environmental variables. This provides genome-wide evidence for selection due to changes in ecoregion, diet, and subsistence. We find particularly strong signals associated with polar ecoregions, with foraging, and with a diet rich in roots and tubers. Interestingly, several of the strongest signals overlap with those implicated in energy metabolism phenotypes from genome-wide association studies, including SNPs influencing glucose levels and susceptibility to type 2 diabetes. Furthermore, several pathways, including those of starch and sucrose metabolism, are enriched for strong signals of adaptations to a diet rich in roots and tubers, whereas signals associated with polar ecoregions are overrepresented in genes associated with energy metabolism pathways.