Evolutionary history and adaptation from high-coverage whole-genome sequences of diverse African hunter-gatherers.

To reconstruct modern human evolutionary history and identify loci that have shaped hunter-gatherer adaptation, we sequenced the whole genomes of five individuals in each of three different hunter-gatherer populations at > 60× coverage: Pygmies from Cameroon and Khoesan-speaking Hadza and Sandawe from Tanzania. We identify 13.4 million variants, substantially increasing the set of known human variation. We found evidence of archaic introgression in all three populations, and the distribution of time to most recent common ancestors from these regions is similar to that observed for introgressed regions in Europeans. Additionally, we identify numerous loci that harbor signatures of local adaptation, including genes involved in immunity, metabolism, olfactory and taste perception, reproduction, and wound healing. Within the Pygmy population, we identify multiple highly differentiated loci that play a role in growth and anterior pituitary function and are associated with height.

Challenges of accurately estimating sex-biased admixture from X chromosomal and autosomal ancestry proportions.

Sex-biased admixture can be inferred from ancestry-specific proportions of X chromosome and autosomes. In a paper published in the American Journal of Human Genetics, Micheletti et al.1 used this approach to quantify male and female contributions following the transatlantic slave trade. Using a large dataset from 23andMe, they concluded that African and European contributions to gene pools in the Americas were much more sex biased than previously thought. We show that the reported extreme sex-specific contributions can be attributed to unassigned genetic ancestry as well as the limitations of simple models of sex-biased admixture. Unassigned ancestry proportions in the study by Micheletti et al. ranged from ∼1% to 21%, depending on the type of chromosome and geographic region. A sensitivity analysis illustrates how this unassigned ancestry can create false patterns of sex bias and that mathematical models are highly sensitive to slight sampling errors when inferring mean ancestry proportions, making confidence intervals necessary. Thus, unassigned ancestry and the sensitivity of the models effectively prohibit the interpretation of estimated sex biases for many geographic regions in Micheletti et al. Furthermore, Micheletti et al. assumed models of a single admixture event. Using simulations, we find that violations of demographic assumptions, such as subsequent gene flow and/or sex-specific assortative mating, may have confounded the analyses of Micheletti et al., but unassigned ancestry was likely the more important confounding factor. Our findings underscore the importance of using complete ancestry information, sufficiently large sample sizes, and appropriate models when inferring sex-biased patterns of demography. This Matters Arising paper is in response to Micheletti et al.,1 published in American Journal of Human Genetics. See also the response by Micheletti et al.,2 published in this issue.

Genomic analyses inform on migration events during the peopling of Eurasia.

High-coverage whole-genome sequence studies have so far focused on a limited number of geographically restricted populations, or been targeted at specific diseases, such as cancer. Nevertheless, the availability of high-resolution genomic data has led to the development of new methodologies for inferring population history and refuelled the debate on the mutation rate in humans. Here we present the Estonian Biocentre Human Genome Diversity Panel (EGDP), a dataset of 483 high-coverage human genomes from 148 populations worldwide, including 379 new genomes from 125 populations, which we group into diversity and selection sets. We analyse this dataset to refine estimates of continent-wide patterns of heterozygosity, long- and short-distance gene flow, archaic admixture, and changes in effective population size through time as well as for signals of positive or balancing selection. We find a genetic signature in present-day Papuans that suggests that at least 2% of their genome originates from an early and largely extinct expansion of anatomically modern humans (AMHs) out of Africa. Together with evidence from the western Asian fossil record, and admixture between AMHs and Neanderthals predating the main Eurasian expansion, our results contribute to the mounting evidence for the presence of AMHs out of Africa earlier than 75,000 years ago.

Phylogeny Estimation by Integration over Isolation with Migration Models.

Phylogeny estimation is difficult for closely related populations and species, especially if they have been exchanging genes. We present a hierarchical Bayesian, Markov-chain Monte Carlo method with a state space that includes all possible phylogenies in a full Isolation-with-Migration model framework. The method is based on a new type of genealogy augmentation called a "hidden genealogy" that enables efficient updating of the phylogeny. This is the first likelihood-based method to fully incorporate directional gene flow and genetic drift for estimation of a species or population phylogeny. Application to human hunter-gatherer populations from Africa revealed a clear phylogenetic history, with strong support for gene exchange with an unsampled ghost population, and relatively ancient divergence between a ghost population and modern human populations, consistent with human/archaic divergence. In contrast, a study of five chimpanzee populations reveals a clear phylogeny with several pairs of populations having exchanged DNA, but does not support a history with an unsampled ghost population.

Whole-genome sequence analyses of Western Central African Pygmy hunter-gatherers reveal a complex demographic history and identify candidate genes under positive natural selection.

African Pygmies practicing a mobile hunter-gatherer lifestyle are phenotypically and genetically diverged from other anatomically modern humans, and they likely experienced strong selective pressures due to their unique lifestyle in the Central African rainforest. To identify genomic targets of adaptation, we sequenced the genomes of four Biaka Pygmies from the Central African Republic and jointly analyzed these data with the genome sequences of three Baka Pygmies from Cameroon and nine Yoruba famers. To account for the complex demographic history of these populations that includes both isolation and gene flow, we fit models using the joint allele frequency spectrum and validated them using independent approaches. Our two best-fit models both suggest ancient divergence between the ancestors of the farmers and Pygmies, 90,000 or 150,000 yr ago. We also find that bidirectional asymmetric gene flow is statistically better supported than a single pulse of unidirectional gene flow from farmers to Pygmies, as previously suggested. We then applied complementary statistics to scan the genome for evidence of selective sweeps and polygenic selection. We found that conventional statistical outlier approaches were biased toward identifying candidates in regions of high mutation or low recombination rate. To avoid this bias, we assigned P-values for candidates using whole-genome simulations incorporating demography and variation in both recombination and mutation rates. We found that genes and gene sets involved in muscle development, bone synthesis, immunity, reproduction, cell signaling and development, and energy metabolism are likely to be targets of positive natural selection in Western African Pygmies or their recent ancestors.

Model-based analyses of whole-genome data reveal a complex evolutionary history involving archaic introgression in Central African Pygmies.

Comparisons of whole-genome sequences from ancient and contemporary samples have pointed to several instances of archaic admixture through interbreeding between the ancestors of modern non-Africans and now extinct hominids such as Neanderthals and Denisovans. One implication of these findings is that some adaptive features in contemporary humans may have entered the population via gene flow with archaic forms in Eurasia. Within Africa, fossil evidence suggests that anatomically modern humans (AMH) and various archaic forms coexisted for much of the last 200,000 yr; however, the absence of ancient DNA in Africa has limited our ability to make a direct comparison between archaic and modern human genomes. Here, we use statistical inference based on high coverage whole-genome data (greater than 60×) from contemporary African Pygmy hunter-gatherers as an alternative means to study the evolutionary history of the genus Homo. Using whole-genome simulations that consider demographic histories that include both isolation and gene flow with neighboring farming populations, our inference method rejects the hypothesis that the ancestors of AMH were genetically isolated in Africa, thus providing the first whole genome-level evidence of African archaic admixture. Our inferences also suggest a complex human evolutionary history in Africa, which involves at least a single admixture event from an unknown archaic population into the ancestors of AMH, likely within the last 30,000 yr.

A recent bottleneck of Y chromosome diversity coincides with a global change in culture.

It is commonly thought that human genetic diversity in non-African populations was shaped primarily by an out-of-Africa dispersal 50-100 thousand yr ago (kya). Here, we present a study of 456 geographically diverse high-coverage Y chromosome sequences, including 299 newly reported samples. Applying ancient DNA calibration, we date the Y-chromosomal most recent common ancestor (MRCA) in Africa at 254 (95% CI 192-307) kya and detect a cluster of major non-African founder haplogroups in a narrow time interval at 47-52 kya, consistent with a rapid initial colonization model of Eurasia and Oceania after the out-of-Africa bottleneck. In contrast to demographic reconstructions based on mtDNA, we infer a second strong bottleneck in Y-chromosome lineages dating to the last 10 ky. We hypothesize that this bottleneck is caused by cultural changes affecting variance of reproductive success among males.

Biased gene conversion skews allele frequencies in human populations, increasing the disease burden of recessive alleles.

Gene conversion results in the nonreciprocal transfer of genetic information between two recombining sequences, and there is evidence that this process is biased toward G and C alleles. However, the strength of GC-biased gene conversion (gBGC) in human populations and its effects on hereditary disease have yet to be assessed on a genomic scale. Using high-coverage whole-genome sequences of African hunter-gatherers, agricultural populations, and primate outgroups, we quantified the effects of GC-biased gene conversion on population genomic data sets. We find that genetic distances (FST and population branch statistics) are modified by gBGC. In addition, the site frequency spectrum is left-shifted when ancestral alleles are favored by gBGC and right-shifted when derived alleles are favored by gBGC. Allele frequency shifts due to gBGC mimic the effects of natural selection. As expected, these effects are strongest in high-recombination regions of the human genome. By comparing the relative rates of fixation of unbiased and biased sites, the strength of gene conversion was estimated to be on the order of Nb ≈ 0.05 to 0.09. We also find that derived alleles favored by gBGC are much more likely to be homozygous than derived alleles at unbiased SNPs (+42.2% to 62.8%). This results in a curse of the converted, whereby gBGC causes substantial increases in hereditary disease risks. Taken together, our findings reveal that GC-biased gene conversion has important population genetic and public health implications.

The Genomic Health of Ancient Hominins.

The genomes of ancient humans, Neandertals, and Denisovans contain many alleles that influence disease risks. Using genotypes at 3,180 disease-associated loci, we estimated the disease burden of 147 ancient genomes. After correcting for missing data, genetic risk scores (GRS) were generated for nine disease categories and the set of all combined diseases. We used these genetic risk scores to examine the effects of different types of subsistence, geography, and sample age on the number of risk alleles in each ancient genome. On a broad scale, hereditary disease risks are similar for ancient hominins and modern-day humans, and the GRS percentiles of ancient individuals span the full range of what is observed in present-day individuals. In addition, there is evidence that ancient pastoralists may have had healthier genomes than hunter-gatherers and agriculturalists. We also observed a temporal trend whereby genomes from the recent past are more likely to be healthier than genomes from the deep past. This calls into question the idea that modern lifestyles have caused genetic load to increase over time. Focusing on individual genomes, we found that the overall genomic health of the Altai Neandertal is worse than 97% of present-day humans and that Ötzi, the Tyrolean Iceman, had a genetic predisposition for gastrointestinal and cardiovascular diseases. As demonstrated by this work, ancient genomes afford us new opportunities to diagnose past human health, which has previously been limited by the quality and completeness of remains.

SNP ascertainment bias in population genetic analyses: why it is important, and how to correct it.

Whole genome sequencing and SNP genotyping arrays can paint strikingly different pictures of demographic history and natural selection. This is because genotyping arrays contain biased sets of pre-ascertained SNPs. In this short review, we use comparisons between high-coverage whole genome sequences of African hunter-gatherers and data from genotyping arrays to highlight how SNP ascertainment bias distorts population genetic inferences. Sample sizes and the populations in which SNPs are discovered affect the characteristics of observed variants. We find that SNPs on genotyping arrays tend to be older and present in multiple populations. In addition, genotyping arrays cause allele frequency distributions to be shifted towards intermediate frequency alleles, and estimates of linkage disequilibrium are modified. Since population genetic analyses depend on allele frequencies, it is imperative that researchers are aware of the effects of SNP ascertainment bias. With this in mind, we describe multiple ways to correct for SNP ascertainment bias.

Population Genomics of Human Adaptation.

Recent advances in genotyping technologies have facilitated genome-wide scans for natural selection. Identification of targets of natural selection will shed light on processes of human adaptation and evolution and could be important for identifying variation that influences both normal human phenotypic variation as well as disease susceptibility. Here we focus on studies of natural selection in modern humans who originated ~200,000 years go in Africa and migrated across the globe ~50,000 - 100,000 years ago. Movement into new environments, as well as changes in culture and technology including plant and animal domestication, resulted in local adaptation to diverse environments. We summarize statistical approaches for detecting targets of natural selection and for distinguishing the effects of demographic history from natural selection. On a genome-wide scale, immune-related genes appear to be major targets of positive selection. Genes associated with reproduction and fertility also appear to be fast evolving. Additional examples of recent human adaptation include genes associated with lactase persistence, eccrine glands, and response to hypoxia. Lastly, we emphasize the need to supplement scans of selection with functional studies to demonstrate the physiologic impact of candidate loci.

Does Effective Population Size Govern Evolutionary Differences in Telomere Length?

Lengths of telomeres vary by an order of magnitude across mammalian species. Similarly, age- and sex-standardized telomere lengths differ by up to 1 kb (14%) across human populations. How to explain these differences? Telomeres play a central role in senescence and aging, and genes that affect telomere length are likely under weak selection (i.e. telomere length is a trait that is subject to nearly neutral evolution). Importantly, natural selection is more effective in large populations than in small populations. Here, we propose that observed differences in telomere length across species and populations are largely due to differences in effective population sizes. In this perspective, we present preliminary evolutionary genetic evidence supporting this hypothesis and highlight the need for more data.

Uncovering the genetic architecture and evolutionary roots of androgenetic alopecia in African men.

Androgenetic alopecia is a highly heritable trait. However, much of our understanding about the genetics of male pattern baldness comes from individuals of European descent. Here, we examined a novel dataset comprising 2,136 men from Ghana, Nigeria, Senegal, and South Africa that were genotyped using a custom array. We first tested how genetic predictions of baldness generalize from Europe to Africa, finding that polygenic scores from European GWAS yielded AUC statistics that ranged from 0.513 to 0.546, indicating that genetic predictions of baldness in African populations performed notably worse than in European populations. Subsequently, we conducted the first African GWAS of androgenetic alopecia, focusing on self-reported baldness patterns at age 45. After correcting for present age, population structure, and study site, we identified 266 moderately significant associations, 51 of which were independent (p-value < 10-5, r2 < 0.2). Most baldness associations were autosomal, and the X chromosomes does not appear to have a large impact on baldness in African men. Finally, we examined the evolutionary causes of continental differences in genetic architecture. Although Neanderthal alleles have previously been associated with skin and hair phenotypes, we did not find evidence that European-ascertained baldness hits were enriched for signatures of ancient introgression. Most loci that are associated with androgenetic alopecia are evolving neutrally. However, multiple baldness-associated SNPs near the EDA2R and AR genes have large allele frequency differences between continents. Collectively, our findings illustrate how evolutionary history contributes to the limited portability of genetic predictions across ancestries.

Evolutionary Genetics and Admixture in African Populations.

As the ancestral homeland of our species, Africa contains elevated levels of genetic diversity and substantial population structure. Importantly, African genomes are heterogeneous: They contain mixtures of multiple ancestries, each of which have experienced different evolutionary histories. In this review, we view population genetics through the lens of admixture, highlighting how multiple demographic events have shaped African genomes. Each of these historical vignettes paints a recurring picture of population divergence followed by secondary contact. First, we give a brief overview of genetic variation in Africa and examine deep population structure within Africa, including the evidence of ancient introgression from archaic "ghost" populations. Second, we describe the genetic legacies of admixture events that have occurred during the past 10,000 years. This includes gene flow between different click-speaking Khoe-San populations, the stepwise spread of pastoralism from eastern to southern Africa, multiple migrations of Bantu speakers across the continent, as well as admixture from the Middle East and Europe into the Sahel region and North Africa. Furthermore, the genomic signatures of more recent admixture can be found in the Cape Peninsula and throughout the African diaspora. Third, we highlight how natural selection has shaped patterns of genetic variation across the continent, noting that gene flow provides a potent source of adaptive variation and that selective pressures vary across Africa. Finally, we explore the biomedical implications of population structure in Africa on health and disease and call for more ethically conducted studies of genetic variation in Africa.

Evidence of Novel Susceptibility Variants for Prostate Cancer and a Multiancestry Polygenic Risk Score Associated with Aggressive Disease in Men of African Ancestry.

BACKGROUND: Genetic factors play an important role in prostate cancer (PCa) susceptibility. OBJECTIVE: To discover common genetic variants contributing to the risk of PCa in men of African ancestry. DESIGN, SETTING, AND PARTICIPANTS: We conducted a meta-analysis of ten genome-wide association studies consisting of 19378 cases and 61620 controls of African ancestry. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Common genotyped and imputed variants were tested for their association with PCa risk. Novel susceptibility loci were identified and incorporated into a multiancestry polygenic risk score (PRS). The PRS was evaluated for associations with PCa risk and disease aggressiveness. RESULTS AND LIMITATIONS: Nine novel susceptibility loci for PCa were identified, of which seven were only found or substantially more common in men of African ancestry, including an African-specific stop-gain variant in the prostate-specific gene anoctamin 7 (ANO7). A multiancestry PRS of 278 risk variants conferred strong associations with PCa risk in African ancestry studies (odds ratios [ORs] >3 and >5 for men in the top PRS decile and percentile, respectively). More importantly, compared with men in the 40-60% PRS category, men in the top PRS decile had a significantly higher risk of aggressive PCa (OR = 1.23, 95% confidence interval = 1.10-1.38, p = 4.4 × 10-4). CONCLUSIONS: This study demonstrates the importance of large-scale genetic studies in men of African ancestry for a better understanding of PCa susceptibility in this high-risk population and suggests a potential clinical utility of PRS in differentiating between the risks of developing aggressive and nonaggressive disease in men of African ancestry. PATIENT SUMMARY: In this large genetic study in men of African ancestry, we discovered nine novel prostate cancer (PCa) risk variants. We also showed that a multiancestry polygenic risk score was effective in stratifying PCa risk, and was able to differentiate risk of aggressive and nonaggressive disease.

Genome-wide association study of prostate-specific antigen levels in 392,522 men identifies new loci and improves cross-ancestry prediction.

We conducted a multi-ancestry genome-wide association study of prostate-specific antigen (PSA) levels in 296,754 men (211,342 European ancestry; 58,236 African ancestry; 23,546 Hispanic/Latino; 3,630 Asian ancestry; 96.5% of participants were from the Million Veteran Program). We identified 318 independent genome-wide significant (p≤5e-8) variants, 184 of which were novel. Most demonstrated evidence of replication in an independent cohort (n=95,768). Meta-analyzing discovery and replication (n=392,522) identified 447 variants, of which a further 111 were novel. Out-of-sample variance in PSA explained by our new polygenic risk score reached 16.9% (95% CI=16.1%-17.8%) in European ancestry, 9.5% (95% CI=7.0%-12.2%) in African ancestry, 18.6% (95% CI=15.8%-21.4%) in Hispanic/Latino, and 15.3% (95% CI=12.7%-18.1%) in Asian ancestry, and lower for higher age. Our study highlights how including proportionally more participants from underrepresented populations improves genetic prediction of PSA levels, with potential to personalize prostate cancer screening.

Hybrid fitness effects modify fixation probabilities of introgressed alleles.

Hybridization is a common occurrence in natural populations, and introgression is a major source of genetic variation. Despite the evolutionary importance of adaptive introgression, classical population genetics theory does not take into account hybrid fitness effects. Specifically, heterosis (i.e. hybrid vigor) and Dobzhansky-Muller incompatibilities influence the fates of introgressed alleles. Here, we explicitly account for polygenic, unlinked hybrid fitness effects when tracking a rare introgressed marker allele. These hybrid fitness effects quickly decay over time due to repeated backcrossing, enabling a separation-of-timescales approach. Using diffusion and branching process theory in combination with computer simulations, we formalize the intuition behind how hybrid fitness effects affect introgressed alleles. We find that hybrid fitness effects can significantly hinder or boost the fixation probability of introgressed alleles, depending on the relative strength of heterosis and Dobzhansky-Muller incompatibilities effects. We show that the inclusion of a correction factor (α, representing the compounded effects of hybrid fitness effects over time) into classic population genetics theory yields accurate fixation probabilities. Despite having a strong impact on the probability of fixation, hybrid fitness effects only subtly change the distribution of fitness effects of introgressed alleles that reach fixation. Although strong Dobzhansky-Muller incompatibility effects may expedite the loss of introgressed alleles, fixation times are largely unchanged by hybrid fitness effects.

Adaptive eQTLs reveal the evolutionary impacts of pleiotropy and tissue-specificity while contributing to health and disease.

Large numbers of expression quantitative trait loci (eQTLs) have recently been identified in humans, and many of these regulatory variants have large allele frequency differences between populations. Here, we conducted genome-wide scans of selection to identify adaptive eQTLs (i.e., eQTLs with large population branch statistics). We then tested if tissue pleiotropy affects whether eQTLs are more or less likely to be adaptive and identified tissues that have been key targets of positive selection during the last 100,000 years. Top adaptive eQTL outliers include rs1043809, rs66899053, and rs2814778 (a SNP that is associated with malaria resistance). We found that effect sizes of eQTLs were negatively correlated with population branch statistics and that adaptive eQTLs affect two-thirds as many tissues as do non-adaptive eQTLs. Because the tissue breadth of an eQTL can be viewed as a measure of pleiotropy, these results imply that pleiotropy inhibits adaptation. The proportion of eQTLs that are adaptive varies by tissue, and we found that eQTLs that regulate expression in testis, thyroid, blood, or sun-exposed skin are enriched for signatures of positive selection. By contrast, eQTLs that regulate expression in the cerebrum or female-specific tissues have a relative lack of adaptive outliers. Scans of selections also reveal that many adaptive eQTLs are closely linked to disease-associated loci. Taken together, our results indicate that eQTLs have played an important role in recent human evolution.