Searching for genetic variants with unusual differentiation between subpopulations is an established approach for identifying signals of natural selection. However, existing methods generally require ...discrete subpopulations. We introduce a method that infers selection using principal components (PCs) by identifying variants whose differentiation along top PCs is significantly greater than the null distribution of genetic drift. To enable the application of this method to large datasets, we developed the FastPCA software, which employs recent advances in random matrix theory to accurately approximate top PCs while reducing time and memory cost from quadratic to linear in the number of individuals, a computational improvement of many orders of magnitude. We apply FastPCA to a cohort of 54,734 European Americans, identifying 5 distinct subpopulations spanning the top 4 PCs. Using the PC-based test for natural selection, we replicate previously known selected loci and identify three new genome-wide significant signals of selection, including selection in Europeans at ADH1B. The coding variant rs1229984∗T has previously been associated to a decreased risk of alcoholism and shown to be under selection in East Asians; we show that it is a rare example of independent evolution on two continents. We also detect selection signals at IGFBP3 and IGH, which have also previously been associated to human disease.
Some present-day humans derive up to ∼5% 1 of their ancestry from archaic Denisovans, an even larger proportion than the ∼2% from Neanderthals 2. We developed methods that can disambiguate the ...locations of segments of Denisovan and Neanderthal ancestry in present-day humans and applied them to 257 high-coverage genomes from 120 diverse populations, among which were 20 individual Oceanians with high Denisovan ancestry 3. In Oceanians, the average size of Denisovan fragments is larger than Neanderthal fragments, implying a more recent average date of Denisovan admixture in the history of these populations (p = 0.00004). We document more Denisovan ancestry in South Asia than is expected based on existing models of history, reflecting a previously undocumented mixture related to archaic humans (p = 0.0013). Denisovan ancestry, just like Neanderthal ancestry, has been deleterious on a modern human genetic background, as reflected by its depletion near genes. Finally, the reduction of both archaic ancestries is especially pronounced on chromosome X and near genes more highly expressed in testes than other tissues (p = 1.2 × 10−7 to 3.2 × 10−7 for Denisovan and 2.2 × 10−3 to 2.9 × 10−3 for Neanderthal ancestry even after controlling for differences in level of selective constraint across gene classes). This suggests that reduced male fertility may be a general feature of mixtures of human populations diverged by >500,000 years.
•Denisovan admixture into modern humans occurred after Neanderthal admixture•There is more Denisovan ancestry in South Asians than expected from current models•Denisovan ancestry has been subject to positive and negative selection after admixture•Male infertility most likely occurred after modern human interbreeding with Denisovans
Sankararaman et al. present a map of Denisovan and Neanderthal ancestry in 120 diverse populations and show that Denisovan admixture post-dated Neanderthal admixture. South Asians have more Denisovan ancestry than expected. There was selection both for and against archaic ancestry. Hybridization with Denisovans was probably associated with reduced male fertility.
Abstract
qpAdm is a statistical tool for studying the ancestry of populations with histories that involve admixture between two or more source populations. Using qpAdm, it is possible to identify ...plausible models of admixture that fit the population history of a group of interest and to calculate the relative proportion of ancestry that can be ascribed to each source population in the model. Although qpAdm is widely used in studies of population history of human (and nonhuman) groups, relatively little has been done to assess its performance. We performed a simulation study to assess the behavior of qpAdm under various scenarios in order to identify areas of potential weakness and establish recommended best practices for use. We find that qpAdm is a robust tool that yields accurate results in many cases, including when data coverage is low, there are high rates of missing data or ancient DNA damage, or when diploid calls cannot be made. However, we caution against co-analyzing ancient and present-day data, the inclusion of an extremely large number of reference populations in a single model, and analyzing population histories involving extended periods of gene flow. We provide a user guide suggesting best practices for the use of qpAdm.
Selective sweeps can increase genetic differentiation among populations and cause allele frequency spectra to depart from the expectation under neutrality. We present a likelihood method for ...detecting selective sweeps that involves jointly modeling the multilocus allele frequency differentiation between two populations. We use Brownian motion to model genetic drift under neutrality, and a deterministic model to approximate the effect of a selective sweep on single nucleotide polymorphisms (SNPs) in the vicinity. We test the method with extensive simulated data, and demonstrate that in some scenarios the method provides higher power than previously reported approaches to detect selective sweeps, and can provide surprisingly good localization of the position of a selected allele. A strength of our technique is that it uses allele frequency differentiation between populations, which is much more robust to ascertainment bias in SNP discovery than methods based on the allele frequency spectrum. We apply this method to compare continentally diverse populations, as well as Northern and Southern Europeans. Our analysis identifies a list of loci as candidate targets of selection, including well-known selected loci and new regions that have not been highlighted by previous scans for selection.
One enduring question in evolutionary biology is the extent of archaic admixture in the genomes of present-day populations. In this paper, we present a test for ancient admixture that exploits the ...asymmetry in the frequencies of the two nonconcordant gene trees in a three-population tree. This test was first applied to detect interbreeding between Neandertals and modern humans. We derive the analytic expectation of a test statistic, called the D statistic, which is sensitive to asymmetry under alternative demographic scenarios. We show that the D statistic is insensitive to some demographic assumptions such as ancestral population sizes and requires only the assumption that the ancestral populations were randomly mating. An important aspect of D statistics is that they can be used to detect archaic admixture even when no archaic sample is available. We explore the effect of sequencing error on the false-positive rate of the test for admixture, and we show how to estimate the proportion of archaic ancestry in the genomes of present-day populations. We also investigate a model of subdivision in ancestral populations that can result in D statistics that indicate recent admixture.
Genomic studies have shown that Neanderthals interbred with modern humans, and that non-Africans today are the products of this mixture. The antiquity of Neanderthal gene flow into modern humans ...means that genomic regions that derive from Neanderthals in any one human today are usually less than a hundred kilobases in size. However, Neanderthal haplotypes are also distinctive enough that several studies have been able to detect Neanderthal ancestry at specific loci. We systematically infer Neanderthal haplotypes in the genomes of 1,004 present-day humans. Regions that harbour a high frequency of Neanderthal alleles are enriched for genes affecting keratin filaments, suggesting that Neanderthal alleles may have helped modern humans to adapt to non-African environments. We identify multiple Neanderthal-derived alleles that confer risk for disease, suggesting that Neanderthal alleles continue to shape human biology. An unexpected finding is that regions with reduced Neanderthal ancestry are enriched in genes, implying selection to remove genetic material derived from Neanderthals. Genes that are more highly expressed in testes than in any other tissue are especially reduced in Neanderthal ancestry, and there is an approximately fivefold reduction of Neanderthal ancestry on the X chromosome, which is known from studies of diverse species to be especially dense in male hybrid sterility genes. These results suggest that part of the explanation for genomic regions of reduced Neanderthal ancestry is Neanderthal alleles that caused decreased fertility in males when moved to a modern human genetic background.
In a pair of seminal papers, Sewall Wright and Gustave Malécot introduced FST as a measure of structure in natural populations. In the decades that followed, a number of papers provided differing ...definitions, estimation methods, and interpretations beyond Wright's. While this diversity in methods has enabled many studies in genetics, it has also introduced confusion regarding how to estimate FST from available data. Considering this confusion, wide variation in published estimates of FST for pairs of HapMap populations is a cause for concern. These estimates changed-in some cases more than twofold-when comparing estimates from genotyping arrays to those from sequence data. Indeed, changes in FST from sequencing data might be expected due to population genetic factors affecting rare variants. While rare variants do influence the result, we show that this is largely through differences in estimation methods. Correcting for this yields estimates of FST that are much more concordant between sequence and genotype data. These differences relate to three specific issues: (1) estimating FST for a single SNP, (2) combining estimates of FST across multiple SNPs, and (3) selecting the set of SNPs used in the computation. Changes in each of these aspects of estimation may result in FST estimates that are highly divergent from one another. Here, we clarify these issues and propose solutions.
Population mixture is an important process in biology. We present a suite of methods for learning about population mixtures, implemented in a software package called ADMIXTOOLS, that support formal ...tests for whether mixture occurred and make it possible to infer proportions and dates of mixture. We also describe the development of a new single nucleotide polymorphism (SNP) array consisting of 629,433 sites with clearly documented ascertainment that was specifically designed for population genetic analyses and that we genotyped in 934 individuals from 53 diverse populations. To illustrate the methods, we give a number of examples that provide new insights about the history of human admixture. The most striking finding is a clear signal of admixture into northern Europe, with one ancestral population related to present-day Basques and Sardinians and the other related to present-day populations of northeast Asia and the Americas. This likely reflects a history of admixture between Neolithic migrants and the indigenous Mesolithic population of Europe, consistent with recent analyses of ancient bones from Sweden and the sequencing of the genome of the Tyrolean "Iceman."
Complex traits and common diseases are extremely polygenic, their heritability spread across thousands of loci. One possible explanation is that thousands of genes and loci have similarly important ...biological effects when mutated. However, we hypothesize that for most complex traits, relatively few genes and loci are critical, and negative selection—purging large-effect mutations in these regions—leaves behind common-variant associations in thousands of less critical regions instead. We refer to this phenomenon as flattening. To quantify its effects, we introduce a mathematical definition of polygenicity, the effective number of independently associated SNPs (Me), which describes how evenly the heritability of a trait is spread across the genome. We developed a method, stratified LD fourth moments regression (S-LD4M), to estimate Me, validating that it produces robust estimates in simulations. Analyzing 33 complex traits (average N = 361k), we determined that heritability is spread ∼4× more evenly among common SNPs than among low-frequency SNPs. This difference, together with evolutionary modeling of new mutations, suggests that complex traits would be orders of magnitude less polygenic if not for the influence of negative selection. We also determined that heritability is spread more evenly within functionally important regions in proportion to their heritability enrichment; functionally important regions do not harbor common SNPs with greatly increased causal effect sizes, due to selective constraint. Our results suggest that for most complex traits, the genes and loci with the most critical biological effects often differ from those with the strongest common-variant associations.
Genome-wide association (GWA) studies are an effective approach for identifying genetic variants associated with disease risk. GWA studies can be confounded by population stratification--systematic ...ancestry differences between cases and controls--which has previously been addressed by methods that infer genetic ancestry. Those methods perform well in data sets in which population structure is the only kind of structure present but are inadequate in data sets that also contain family structure or cryptic relatedness. Here, we review recent progress on methods that correct for stratification while accounting for these additional complexities.