The role of geography in human adaptation. PLoS Genet. 2009;5:e1000500. [PMID: 19503611 PMCID: PMC2685456 DOI: 10.1371/journal.pgen.1000500]

Species divergence and environmental adaptation of Picea asperata complex at the whole genome level

To study the interspecific differentiation characteristics of species originating from recent radiation, the genotyping-by-sequencing (GBS) technique was used to explore the kinship, population structure, gene flow, genetic variability, genotype-environment association and selective sweeps of Picea asperata complex with similar phenotypes from a genome-wide perspective. The following results were obtained: 14 populations of P. asperata complex could be divided into 5 clades; P. wilsonii and P. neoveitchii diverged earlier and were more distantly related to the remaining 6 spruce species. Various geological events have promoted the species differentiation of P. asperata complex. There were four instances of gene flow among P. koraiensis, P. meyeri, P. asperata, P. crassifolia and P. mongolica. The population of P. mongolica had the highest level of nucleotide diversity, and P. neoveitchii may have experienced a bottleneck recently. Genotype-environment association found that a total of 20,808 genes were related to the environmental variables, which enhanced the adaptability of spruce in different environments. Genes that were selectively swept in the P. asperata complex were primarily associated with plant stress resistance. Among them were some genes involved in plant growth and development, heat stress, circadian rhythms and flowering. In addition to the commonly selected genes, different spruce species also displayed unique genes subjected to selective sweeps that improved their adaptability to different habitats. Understanding the interspecific gene flow and adaptive evolution of Picea species is beneficial to further understanding the species relationships of spruce and can provide a basis for studying spruce introgression and functional genomics.

Adaptive divergence, historical population dynamics, and simulation of suitable distributions for Picea Meyeri and P. Mongolica at the whole-genome level

The taxonomic classification of Picea meyeri and P. mongolica has long been controversial. To investigate the genetic relatedness, evolutionary history, and population history dynamics of these species, genotyping-by-sequencing (GBS) technology was utilized to acquire whole-genome single nucleotide polymorphism (SNP) markers, which were subsequently used to assess population structure, population dynamics, and adaptive differentiation. Phylogenetic and population structural analyses at the genomic level indicated that although the ancestor of P. mongolica was a hybrid of P. meyeri and P. koraiensis, P. mongolica is an independent Picea species. Additionally, P. mongolica is more closely related to P. meyeri than to P. koraiensis, which is consistent with its geographic distribution. There were up to eight instances of interspecific and intraspecific gene flow between P. meyeri and P. mongolica. The P. meyeri and P. mongolica effective population sizes generally decreased, and Maxent modeling revealed that from the Last Glacial Maximum (LGM) to the present, their habitat areas decreased initially and then increased. However, under future climate scenarios, the habitat areas of both species were projected to decrease, especially under high-emission scenarios, which would place P. mongolica at risk of extinction and in urgent need of protection. Local adaptation has promoted differentiation between P. meyeri and P. mongolica. Genotype‒environment association analysis revealed 96,543 SNPs associated with environmental factors, mainly related to plant adaptations to moisture and temperature. Selective sweeps revealed that the selected genes among P. meyeri, P. mongolica and P. koraiensis are primarily associated in vascular plants with flowering, fruit development, and stress resistance. This research enhances our understanding of Picea species classification and provides a basis for future genetic improvement and species conservation efforts.

Chromatin activity identifies differential gene regulation across human ancestries

BACKGROUND

Current evidence suggests that cis-regulatory elements controlling gene expression may be the predominant target of natural selection in humans and other species. Detecting selection acting on these elements is critical to understanding evolution but remains challenging because we do not know which mutations will affect gene regulation.

RESULTS

To address this, we devise an approach to search for lineage-specific selection on three critical steps in transcriptional regulation: chromatin activity, transcription factor binding, and chromosomal looping. Applying this approach to lymphoblastoid cells from 831 individuals of either European or African descent, we find strong signals of differential chromatin activity linked to gene expression differences between ancestries in numerous contexts, but no evidence of functional differences in chromosomal looping. Moreover, we show that enhancers rather than promoters display the strongest signs of selection associated with sites of differential transcription factor binding.

CONCLUSIONS

Overall, our study indicates that some cis-regulatory adaptation may be more easily detected at the level of chromatin than DNA sequence. This work provides a vast resource of genomic interaction data from diverse human populations and establishes a novel selection test that will benefit future study of regulatory evolution in humans and other species.

An evolutionary perspective on complex neuropsychiatric disease

The forces of evolution-mutation, selection, migration, and genetic drift-shape the genetic architecture of human traits, including the genetic architecture of complex neuropsychiatric illnesses. Studying these illnesses in populations that are diverse in genetic ancestry, historical demography, and cultural history can reveal how evolutionary forces have guided adaptation over time and place. A fundamental truth of shared human biology is that an allele responsible for a disease in anyone, anywhere, reveals a gene critical to the normal biology underlying that condition in everyone, everywhere. Understanding the genetic causes of neuropsychiatric disease in the widest possible range of human populations thus yields the greatest possible range of insight into genes critical to human brain development. In this perspective, we explore some of the relationships between genes, adaptation, and history that can be illuminated by an evolutionary perspective on studies of complex neuropsychiatric disease in diverse populations.

Structure-informed clustering for population stratification in association studies

BACKGROUND

Identifying variants associated with complex traits is a challenging task in genetic association studies due to linkage disequilibrium (LD) between genetic variants and population stratification, unrelated to the disease risk. Existing methods of population structure correction use principal component analysis or linear mixed models with a random effect when modeling associations between a trait of interest and genetic markers. However, due to stringent significance thresholds and latent interactions between the markers, these methods often fail to detect genuinely associated variants.

RESULTS

To overcome this, we propose CluStrat, which corrects for complex arbitrarily structured populations while leveraging the linkage disequilibrium induced distances between genetic markers. It performs an agglomerative hierarchical clustering using the Mahalanobis distance covariance matrix of the markers. In simulation studies, we show that our method outperforms existing methods in detecting true causal variants. Applying CluStrat on WTCCC2 and UK Biobank cohorts, we found biologically relevant associations in Schizophrenia and Myocardial Infarction. CluStrat was also able to correct for population structure in polygenic adaptation of height in Europeans.

CONCLUSIONS

CluStrat highlights the advantages of biologically relevant distance metrics, such as the Mahalanobis distance, which captures the cryptic interactions within populations in the presence of LD better than the Euclidean distance.

Analyses of allele age and fitness impact reveal human beneficial alleles to be older than neutral controls

A classic population genetic prediction is that alleles experiencing directional selection should swiftly traverse allele frequency space, leaving detectable reductions in genetic variation in linked regions. However, despite this expectation, identifying clear footprints of beneficial allele passage has proven to be surprisingly challenging. We addressed the basic premise underlying this expectation by estimating the ages of large numbers of beneficial and deleterious alleles in a human population genomic data set. Deleterious alleles were found to be young, on average, given their allele frequency. However, beneficial alleles were older on average than non-coding, non-regulatory alleles of the same frequency. This finding is not consistent with directional selection and instead indicates some type of balancing selection. Among derived beneficial alleles, those fixed in the population show higher local recombination rates than those still segregating, consistent with a model in which new beneficial alleles experience an initial period of balancing selection due to linkage disequilibrium with deleterious recessive alleles. Alleles that ultimately fix following a period of balancing selection will leave a modest 'soft' sweep impact on the local variation, consistent with the overall paucity of species-wide 'hard' sweeps in human genomes.

Adaptation in Outbred Sexual Yeast is Repeatable, Polygenic and Favors Rare Haplotypes

We carried out a 200 generation Evolve and Resequence (E&R) experiment initiated from an outbred diploid recombined 18-way synthetic base population. Replicate populations were evolved at large effective population sizes (>105 individuals), exposed to several different chemical challenges over 12 weeks of evolution, and whole-genome resequenced. Weekly forced outcrossing resulted in an average between adjacent-gene per cell division recombination rate of ∼0.0008. Despite attempts to force weekly sex, roughly half of our populations evolved cheaters and appear to be evolving asexually. Focusing on seven chemical stressors and 55 total evolved populations that remained sexual we observed large fitness gains and highly repeatable patterns of genome-wide haplotype change within chemical challenges, with limited levels of repeatability across chemical treatments. Adaptation appears highly polygenic with almost the entire genome showing significant and consistent patterns of haplotype change with little evidence for long-range linkage disequilibrium in a subset of populations for which we sequenced haploid clones. That is, almost the entire genome is under selection or drafting with selected sites. At any given locus adaptation was almost always dominated by one of the 18 founder's alleles, with that allele varying spatially and between treatments, suggesting that selection acts primarily on rare variants private to a founder or haplotype blocks harboring multiple mutations.

MPYS Modulates Fatty Acid Metabolism and Immune Tolerance at Homeostasis Independent of Type I IFNs

MPYS/STING (stimulator of IFN genes) senses cyclic dinucleotides (CDNs), generates type I IFNs, and plays a critical role in infection, inflammation, and cancer. In this study, analyzing genotype and haplotype data from the 1000 Genomes Project, we found that the R71H-G230A-R293Q (HAQ) MPYS allele frequency increased 57-fold in East Asians compared with sub-Saharan Africans. Meanwhile, the G230A-R293Q (AQ) allele frequency decreased by 98% in East Asians compared with sub-Saharan Africans. We propose that the HAQ and AQ alleles underwent a natural selection during the out-of-Africa migration. We used mouse models of HAQ and AQ to investigate the underlying mechanism. We found that the mice carrying the AQ allele, which disappeared in East Asians, had normal CDN-type I IFN responses. Adult AQ mice, however, had less fat mass than did HAQ or wild-type mice on a chow diet. AQ epididymal adipose tissue had increased regulatory T cells and M2 macrophages with protein expression associated with enhanced fatty acid oxidation. Conditional knockout mice and adoptive cell transfer indicate a macrophage and regulatory T cell-intrinsic role of MPYS in fatty acid metabolism. Mechanistically, AQ/IFNAR1-/- mice had a similar lean phenotype as for the AQ mice. MPYS intrinsic tryptophan fluorescence revealed that the R71H change increased MPYS hydrophilicity. Lastly, we found that the second transmembrane (TM) and the TM2-TM3 linker region of MPYS interact with activated fatty acid, fatty acyl-CoA. In summary, studying the evolution of the human MPYS gene revealed an MPYS function in modulating fatty acid metabolism that may be critical during the out-of-Africa migration.

A pleiotropic hypoxia-sensitive EPAS1 enhancer is disrupted by adaptive alleles in Tibetans

In Tibetans, noncoding alleles in EPAS1-whose protein product hypoxia-inducible factor 2α (HIF-2α) drives the response to hypoxia-carry strong signatures of positive selection; however, their functional mechanism has not been systematically examined. Here, we report that high-altitude alleles disrupt the activity of four EPAS1 enhancers in one or more cell types. We further characterize one enhancer (ENH5) whose activity is both allele specific and hypoxia dependent. Deletion of ENH5 results in down-regulation of EPAS1 and HIF-2α targets in acute hypoxia and in a blunting of the transcriptional response to sustained hypoxia. Deletion of ENH5 in mice results in dysregulation of gene expression across multiple tissues. We propose that pleiotropic adaptive effects of the Tibetan alleles in EPAS1 underlie the strong selective signal at this gene.

Spatial structure alters the site frequency spectrum produced by hitchhiking

The reduction of genetic diversity due to genetic hitchhiking is widely used to find past selective sweeps from sequencing data, but very little is known about how spatial structure affects hitchhiking. We use mathematical modeling and simulations to find the unfolded site frequency spectrum left by hitchhiking in the genomic region of a sweep in a population occupying a 1D range. For such populations, sweeps spread as Fisher waves, rather than logistically. We find that this leaves a characteristic 3-part site frequency spectrum at loci very close to the swept locus. Very low frequencies are dominated by recent mutations that occurred after the sweep and are unaffected by hitchhiking. At moderately low frequencies, there is a transition zone primarily composed of alleles that briefly "surfed" on the wave of the sweep before falling out of the wavefront, leaving a spectrum close to that expected in well-mixed populations. However, for moderate-to-high frequencies, there is a distinctive scaling regime of the site frequency spectrum produced by alleles that drifted to fixation in the wavefront and then were carried throughout the population. For loci slightly farther away from the swept locus on the genome, recombination is much more effective at restoring diversity in 1D populations than it is in well-mixed ones. We find that these signatures of space can be strong even in apparently well-mixed populations with negligible spatial genetic differentiation, suggesting that spatial structure may frequently distort the signatures of hitchhiking in natural populations.

Genetic polymorphisms of toll-like receptors in leprosy patients from southern Brazil

Leprosy is a chronic disease and also a global health issue, with a high number of new cases per year. Toll-like receptors can respond to mycobacterial molecules in the early stage of infection. As important components of the innate immune response, alterations in genes coding for these receptors may contribute to susceptibility/protection against diseases. In this context, we used a case-control study model (183 leprosy cases vs. 185 controls) to investigate whether leprosy patients and the control group, in southern Brazil, have different frequencies in TLR1 (TLR1 G>T; rs5743618), TLR2 (TLR2 T>C, rs1816702 and rs4696483), and TLR4 (TLR4 A>G, rs1927911) polymorphisms. Analysis of the TLR1 1805G>T polymorphism presented the G/G genotype more frequently in the control group. TLR2 T>C rs1816702 and TLR2 T>C rs4696483, the T/T and C/T genotype, respectively, were more frequent in the control group than in leprosy patients, suggesting protection from leprosy when the T allele is present (rs4696483). Haplotype analyses between TLR1 (rs5743618) and TLR2 (rs1816702 and rs4696483) polymorphisms suggest risk for the presence of the TCC haplotype and protection in the presence of the TCT haplotype. This study suggests that polymorphisms in TLR1 and TLR2 are factors that may contribute to development/resistance of leprosy.

Analysis of Common SNPs across Continents Reveals Major Genomic Differences between Human Populations

Common alleles tend to be more ancient than rare alleles. These common SNPs appeared thousands of years ago and reflect intricate human evolution including various adaptations, admixtures, and migration events. Eighty-four thousand abundant region-specific alleles (ARSAs) that are common in one continent but absent in the rest of the world have been characterized by processing 3100 genomes from 230 populations. Also computed were 17,446 polymorphic sites with regional absence of common alleles (RACAs), which are widespread globally but absent in one region. A majority of these region-specific SNPs were found in Africa. America has the second greatest number of ARSAs (3348) and is even ahead of Europe (1911). Surprisingly, East Asia has the highest number of RACAs (10,524) and the lowest number of ARSAs (362). ARSAs and RACAs have distinct compositions of ancestral versus derived alleles in different geographical regions, reflecting their unique evolution. Genes associated with ARSA and RACA SNPs were identified and their functions were analyzed. The core 100 genes shared by multiple populations and associated with region-specific natural selection were examined. The largest part of them (42%) are related to the nervous system. ARSA and RACA SNPs are important for both association and human evolution studies.

Human follicular mites: Ectoparasites becoming symbionts

Most humans carry mites in the hair follicles of their skin for their entire lives. Follicular mites are the only metazoans tha continuously live on humans. We propose that Demodex folliculorum (Acari) represents a transitional stage from a host-injuring obligate parasite to an obligate symbiont. Here, we describe the profound impact of this transition on the genome and physiology of the mite. Genome sequencing revealed that the permanent host association of D. folliculorum led to an extensive genome reduction through relaxed selection and genetic drift, resulting in the smallest number of protein-coding genes yet identified among panarthropods. Confocal microscopy revealed that this gene loss coincided with an extreme reduction in the number of cells. Single uninucleate muscle cells are sufficient to operate each of the three segments that form each walking leg. While it has been assumed that the reduction of the cell number in parasites starts early in development, we identified a greater total number of cells in the last developmental stage (nymph) than in the terminal adult stage, suggesting that reduction starts at the adult or ultimate stage of development. This is the first evolutionary step in an arthropod species adopting a reductive, parasitic or endosymbiotic lifestyle. Somatic nuclei show underreplication at the diploid stage. Novel eye structures or photoreceptors as well as a unique human host melatonin-guided day/night rhythm are proposed for the first time. The loss of DNA repair genes coupled with extreme endogamy might have set this mite species on an evolutionary dead-end trajectory.

Population differentiation of polygenic score predictions under stabilizing selection

Given the many small-effect loci uncovered by genome-wide association studies (GWAS), polygenic scores have become central to genomic medicine, and have found application in diverse settings including evolutionary studies of adaptation. Despite their promise, polygenic scores have been found to suffer from limited portability across human populations. This at first seems in conflict with the observation that most common genetic variation is shared among populations. We investigate one potential cause of this discrepancy: stabilizing selection on complex traits. Counterintuitively, while stabilizing selection constrains phenotypic evolution, it accelerates the loss and fixation of alleles underlying trait variation within populations (GWAS loci). Thus even when populations share an optimum phenotype, stabilizing selection erodes the variance contributed by their shared GWAS loci, such that predictions from GWAS in one population explain less of the phenotypic variation in another. We develop theory to quantify how stabilizing selection is expected to reduce the prediction accuracy of polygenic scores in populations not represented in GWAS samples. In addition, we find that polygenic scores can substantially overstate average genetic differences of phenotypes among populations. We emphasize stabilizing selection around a common optimum as a useful null model to connect patterns of allele frequency and polygenic score differentiation. This article is part of the theme issue 'Celebrating 50 years since Lewontin's apportionment of human diversity'.

KLFDAPC: a supervised machine learning approach for spatial genetic structure analysis

Geographic patterns of human genetic variation provide important insights into human evolution and disease. A commonly used tool to detect and describe them is principal component analysis (PCA) or the supervised linear discriminant analysis of principal components (DAPC). However, genetic features produced from both approaches could fail to correctly characterize population structure for complex scenarios involving admixture. In this study, we introduce Kernel Local Fisher Discriminant Analysis of Principal Components (KLFDAPC), a supervised non-linear approach for inferring individual geographic genetic structure that could rectify the limitations of these approaches by preserving the multimodal space of samples. We tested the power of KLFDAPC to infer population structure and to predict individual geographic origin using neural networks. Simulation results showed that KLFDAPC has higher discriminatory power than PCA and DAPC. The application of our method to empirical European and East Asian genome-wide genetic datasets indicated that the first two reduced features of KLFDAPC correctly recapitulated the geography of individuals and significantly improved the accuracy of predicting individual geographic origin when compared to PCA and DAPC. Therefore, KLFDAPC can be useful for geographic ancestry inference, design of genome scans and correction for spatial stratification in GWAS that link genes to adaptation or disease susceptibility.

Recombination affects allele-specific expression of deleterious variants in human populations

How the genetic composition of a population changes through stochastic processes, such as genetic drift, in combination with deterministic processes, such as selection, is critical to understanding how phenotypes vary in space and time. Here, we show how evolutionary forces affecting selection, including recombination and effective population size, drive genomic patterns of allele-specific expression (ASE). Integrating tissue-specific genotypic and transcriptomic data from 1500 individuals from two different cohorts, we demonstrate that ASE is less often observed in regions of low recombination, and loci in high or normal recombination regions are more efficient at using ASE to underexpress harmful mutations. By tracking genetic ancestry, we discriminate between ASE variability due to past demographic effects, including subsequent bottlenecks, versus local environment. We observe that ASE is not randomly distributed along the genome and that population parameters influencing the efficacy of natural selection alter ASE levels genome wide.

The genomic signatures of natural selection in admixed human populations

Admixture has been a pervasive phenomenon in human history, extensively shaping the patterns of population genetic diversity. There is increasing evidence to suggest that admixture can also facilitate genetic adaptation to local environments, i.e., admixed populations acquire beneficial mutations from source populations, a process that we refer to as "adaptive admixture." However, the role of adaptive admixture in human evolution and the power to detect it remain poorly characterized. Here, we use extensive computer simulations to evaluate the power of several neutrality statistics to detect natural selection in the admixed population, assuming multiple admixture scenarios. We show that statistics based on admixture proportions, F_adm and LAD, show high power to detect mutations that are beneficial in the admixed population, whereas other statistics, including iHS and F_ST, falsely detect neutral mutations that have been selected in the source populations only. By combining F_adm and LAD into a single, powerful statistic, we scanned the genomes of 15 worldwide, admixed populations for signatures of adaptive admixture. We confirm that lactase persistence and resistance to malaria have been under adaptive admixture in West Africans and in Malagasy, North Africans, and South Asians, respectively. Our approach also uncovers other cases of adaptive admixture, including APOL1 in Fulani nomads and PKN2 in East Indonesians, involved in resistance to infection and metabolism, respectively. Collectively, our study provides evidence that adaptive admixture has occurred in human populations whose genetic history is characterized by periods of isolation and spatial expansions resulting in increased gene flow.

Geographical variation in nest defense among cinereous tit populations in China

Behavioral divergence among populations is common across taxonomic groups, still we know very little about anti-predator behaviors. Animal exposure to predation risk is variable in different ecological contexts. In addition, reproduction value of animals in different geographical regions usually varies. In this study, we tested whether cinereous tits Parus cinereus in different populations exhibited nest defense behaviors similar to those of nest or adult predators and whether their nest defense behaviors showed geographical variation. By using field dummy experiments, we observed tits’ nest defense behavior in nest predator common chipmunk Tamias sibiricus and red squirrel Sciurus vulgaris, adult predator Eurasian sparrowhawk Accipiter nisus and nonthreatening species Oriental turtle dove Streptopelia orientalis in the ZJ (44° N), DLS (18° N) and DZ (31° N) populations, respectively. The response scores varied significantly across the four dummies in ZJ-tits and DLS-tits but did not in DZ-tits. When facing the chipmunk, ZJ-tits showed the highest response score, and DZ-tits showed the lowest response score. When facing the squirrel, ZJ-tits showed a higher response score than tits in the other two populations. However, tits among the three populations responded similarly to a sparrowhawk or dove with slight response behaviors. In addition, response scores to nest predators were positively correlated with brood size across the three populations, but no trend was found for sparrowhawks or doves. Our results indicated that the nest defense behaviors of cinereous tits have evolved in response to large-scale geographical variation in ecological contexts and reproduction value.

Novel alleles gained during the Beringian isolation period

During the Last Glacial Maximum, a small band of Siberians entered the Beringian corridor, where they persisted, isolated from gene flow, for several thousand years before expansion into the Americas. The ecological features of the Beringian environment, coupled with an extended period of isolation at small population size, would have provided evolutionary opportunity for novel genetic variation to arise as both rare standing variants and new mutations were driven to high frequency through both neutral and directed processes. Here we perform a full genome investigation of Native American populations in the Thousand Genomes Project Phase 3 to identify unique high frequency alleles that can be dated to an origin in Beringia. Our analyses demonstrate that descendant populations of Native Americans harbor 20,424 such variants, which is on a scale comparable only to Africa and the Out of Africa bottleneck. This is consistent with simulations of a serial founder effects model. Tests for selection reveal that some of these Beringian variants were likely driven to high frequency by adaptive processes, and bioinformatic analyses suggest possible phenotypic pathways that were under selection during the Beringian Isolation period. Specifically, pathways related to cardiac processes and melanocyte function appear to be enriched for selected Beringian variants.

A neurodegenerative disease landscape of rare mutations in Colombia due to founder effects

BACKGROUND

The Colombian population, as well as those in other Latin American regions, arose from a recent tri-continental admixture among Native Americans, Spanish invaders, and enslaved Africans, all of whom passed through a population bottleneck due to widespread infectious diseases that left small isolated local settlements. As a result, the current population reflects multiple founder effects derived from diverse ancestries.

METHODS

We characterized the role of admixture and founder effects on the origination of the mutational landscape that led to neurodegenerative disorders under these historical circumstances. Genomes from 900 Colombian individuals with Alzheimer's disease (AD) [n = 376], frontotemporal lobar degeneration-motor neuron disease continuum (FTLD-MND) [n = 197], early-onset dementia not otherwise specified (EOD) [n = 73], and healthy participants [n = 254] were analyzed. We examined their global and local ancestry proportions and screened this cohort for deleterious variants in disease-causing and risk-conferring genes.

RESULTS

We identified 21 pathogenic variants in AD-FTLD related genes, and PSEN1 harbored the majority (11 pathogenic variants). Variants were identified from all three continental ancestries. TREM2 heterozygous and homozygous variants were the most common among AD risk genes (102 carriers), a point of interest because the disease risk conferred by these variants differed according to ancestry. Several gene variants that have a known association with MND in European populations had FTLD phenotypes on a Native American haplotype. Consistent with founder effects, identity by descent among carriers of the same variant was frequent.

CONCLUSIONS

Colombian demography with multiple mini-bottlenecks probably enhanced the detection of founder events and left a proportionally higher frequency of rare variants derived from the ancestral populations. These findings demonstrate the role of genomically defined ancestry in phenotypic disease expression, a phenotypic range of different rare mutations in the same gene, and further emphasize the importance of inclusiveness in genetic studies.

Polygenic adaptation after a sudden change in environment

Polygenic adaptation is thought to be ubiquitous, yet remains poorly understood. Here, we model this process analytically, in the plausible setting of a highly polygenic, quantitative trait that experiences a sudden shift in the fitness optimum. We show how the mean phenotype changes over time, depending on the effect sizes of loci that contribute to variance in the trait, and characterize the allele dynamics at these loci. Notably, we describe the two phases of the allele dynamics: The first is a rapid phase, in which directional selection introduces small frequency differences between alleles whose effects are aligned with or opposed to the shift, ultimately leading to small differences in their probability of fixation during a second, longer phase, governed by stabilizing selection. As we discuss, key results should hold in more general settings and have important implications for efforts to identify the genetic basis of adaptation in humans and other species.

Revisiting the malaria hypothesis: accounting for polygenicity and pleiotropy

The malaria hypothesis predicts local, balancing selection of deleterious alleles that confer strong protection from malaria. Three protective variants, recently discovered in red cell genes, are indeed more common in African than European populations. Still, up to 89% of the heritability of severe malaria is attributed to many genome-wide loci with individually small effects. Recent analyses of hundreds of genome-wide association studies (GWAS) in humans suggest that most functional, polygenic variation is pleiotropic for multiple traits. Interestingly, GWAS alleles and red cell traits associated with small reductions in malaria risk are not enriched in African populations. We propose that other selective and neutral forces, in addition to malaria prevalence, explain the global distribution of most genetic variation impacting malaria risk.

Sporadic occurrence of recent selective sweeps from standing variation in humans as revealed by an approximate Bayesian computation approach

During their dispersals over the last 100,000 years, modern humans have been exposed to a large variety of environments, resulting in genetic adaptation. While genome-wide scans for the footprints of positive Darwinian selection have increased knowledge of genes and functions potentially involved in human local adaptation, they have globally produced evidence of a limited contribution of selective sweeps in humans. Conversely, studies based on machine learning algorithms suggest that recent sweeps from standing variation are widespread in humans, an observation that has been recently questioned. Here, we sought to formally quantify the number of recent selective sweeps in humans, by leveraging approximate Bayesian computation and whole-genome sequence data. Our computer simulations revealed suitable ABC estimations, regardless of the frequency of the selected alleles at the onset of selection and the completion of sweeps. Under a model of recent selection from standing variation, we inferred that an average of 68 (from 56 to 79) and 140 (from 94 to 198) sweeps occurred over the last 100,000 years of human history, in African and Eurasian populations, respectively. The former estimation is compatible with human adaptation rates estimated since divergence with chimps, and reveals numbers of sweeps per generation per site in the range of values estimated in Drosophila. Our results confirm the rarity of selective sweeps in humans and show a low contribution of sweeps from standing variation to recent human adaptation.

Selection shapes the landscape of functional variation in wild house mice

BACKGROUND

Through human-aided dispersal over the last ~ 10,000 years, house mice (Mus musculus) have recently colonized diverse habitats across the globe, promoting the emergence of new traits that confer adaptive advantages in distinct environments. Despite their status as the premier mammalian model system, the impact of this demographic and selective history on the global patterning of disease-relevant trait variation in wild mouse populations is poorly understood.

RESULTS

Here, we leveraged 154 whole-genome sequences from diverse wild house mouse populations to survey the geographic organization of functional variation and systematically identify signals of positive selection. We show that a significant proportion of wild mouse variation is private to single populations, including numerous predicted functional alleles. In addition, we report strong signals of positive selection at many genes associated with both complex and Mendelian diseases in humans. Notably, we detect a significant excess of selection signals at disease-associated genes relative to null expectations, pointing to the important role of adaptation in shaping the landscape of functional variation in wild mouse populations. We also uncover strong signals of selection at multiple genes involved in starch digestion, including Mgam and Amy1. We speculate that the successful emergence of the human-mouse commensalism may have been facilitated, in part, by dietary adaptations at these loci. Finally, our work uncovers multiple cryptic structural variants that manifest as putative signals of positive selection, highlighting an important and under-appreciated source of false-positive signals in genome-wide selection scans.

CONCLUSIONS

Overall, our findings highlight the role of adaptation in shaping wild mouse genetic variation at human disease-associated genes. Our work also highlights the biomedical relevance of wild mouse genetic diversity and underscores the potential for targeted sampling of mice from specific populations as a strategy for developing effective new mouse models of both rare and common human diseases.

Similarity-based analysis of allele frequency distribution among multiple populations identifies adaptive genomic structural variants

Structural variants have a considerable impact on human genomic diversity. However, their evolutionary history remains mostly unexplored. Here, we developed a new method to identify potentially adaptive structural variants based on a similarity-based analysis that incorporates genotype frequency data from 26 populations simultaneously. Using this method, we analyzed 57,629 structural variants and identified 576 structural variants that show unusual population differentiation. Of these putatively adaptive structural variants, we further showed that 24 variants are multiallelic and overlap with coding sequences, and 20 variants are significantly associated with GWAS traits. Closer inspection of the haplotypic variation associated with these putatively adaptive and functional structural variants reveals deviations from neutral expectations due to: 1) population differentiation of rapidly evolving multiallelic variants, 2) incomplete sweeps, and 3) recent population-specific negative selection. Overall, our study provides new methodological insights, documents hundreds of putatively adaptive variants, and introduces evolutionary models that may better explain the complex evolution of structural variants.

Positive selection of skeleton-related genes during duck domestication revealed by whole genome sequencing

BACKGROUND

Domestication alters several phenotypic, neurological, and physiological traits in domestic animals compared to those in their wild ancestors. Domestic ducks originated from mallards, and some studies have shown that spot-billed ducks may have also made minor genetic contributions to domestication. Compared with the two ancestral species, domestic ducks generally differ in body size and bone morphology. In this study, we performed both genomic and transcriptomic analyses to identify candidate genes for elucidating the genetic mechanisms underlying phenotypic variation.

METHODS

In this study, the duck genome data from eight domestic breeds and two wild species were collected to study the genetic changes during domestication. And the transcriptome data of different tissues from wild ducks and seven domestic ducks were used to reveal the expression difference between wild and domestic ducks.

RESULTS

Using fixation index (Fst) algorithm and transcriptome data, we found that the genes related to skeletal development had high Fst values in wild and domestic breeds, and the differentially expressed genes were mainly enriched in the ossification pathway. Our data strongly suggest that the skeletal systems of domestic ducks were changed to adapt to artificial selection for larger sizes. In addition, by combining the genome and transcriptome data, we found that some Fst candidate genes exhibited different expression patterns, and these genes were found to be involved in digestive, immune, and metabolic functions.

CONCLUSIONS

A wide range of phenotypic differences exists between domestic and wild ducks. Through both genome and transcriptome analyses, we found that genes related to the skeletal system in domestic ducks were strongly selected. Our findings provide new insight into duck domestication and selection effects during the domestication.

Ethnicity-dependent effects of Zinc finger 804A variant on schizophrenia: a systematic review and meta-analysis

OBJECTIVES

Previous studies and meta-analysis indicated that rs1344706 was associated with schizophrenia in European population, whereas the conclusions in other populations were disputed. To further explore whether the allele A of rs1344706 would increase the risk of schizophrenia in different populations and update the original meta-analysis, we conducted a systematic review and meta-analysis worldwide.

METHODS

A literature search was performed in PubMed, Embase, Cochrane Library, PsycINFO and Web of Science (up to 10 July 2019) according to the inclusion criteria.

RESULTS

A total of 27 articles were included. Our meta-analysis showed an association between rs1344706 and schizophrenia in total populations [P = 0.000; odds ratio (OR) = 1.105; 95% confidence interval (CI), 1.048-1.165], Europe population (P = 0.025; OR = 1.108; 95% CI, 1.013-1.222) and Asian population(P = 0.005; OR = 1.094; 95% CI, 1.027-1.164).

CONCLUSIONS

Our findings suggested that the risk of single nucleotide polymorphism rs1344706 A-allele may increase the risk of schizophrenia worldwide. Also, this ethnicity-dependent effects of ZNF804A variant on schizophrenia may be related to the opposite allele direction. But to elucidate the underlying biological mechanism, further studies with large participant populations are needed.

Genome structural variation in human evolution

Structural variation (SV) is a large difference (typically >100 bp) in the genomic structure of two genomes and includes both copy number variation and variation that does not change copy number of a genomic region, such as an inversion. Improved reference genomes, combined with widespread genome sequencing using short-read sequencing technology, and increasingly using long-read sequencing, have reignited interest in SV. Recent large-scale studies and functional focused analyses have highlighted the role of SV in human evolution. In this review, we highlight human-specific SVs involved in changes in the brain, population-specific SVs that affect response to the environment, including adaptation to diet and infectious diseases, and summarise the contribution of archaic hominin admixture to present-day human SV.

Association of the PINX1 Variant rs6984094, Which Lengthens Telomeres, with Systemic Lupus Erythematosus Susceptibility in Chinese Populations

A recent genome-wide association study (GWAS) of Asian ancestry reported that single nucleotide polymorphism (SNP) in TERT (telomerase reverse transcriptase) was associated with systemic lupus erythematosus (SLE). TERT has a critical role in maintaining the chromosomal stability and the length of telomere. Given that only a small portion of the genetic heritability of SLE has been explained so far, we aimed to identify novel loci in telomere-related genes responsible for SLE susceptibility in Chinese populations. We performed a comprehensive genetic association analysis of SLE with telomere-related genes. To identify functional significance, we analyzed the publicly available HaploReg v4.1 and RegulomeDB databases. Differential gene expression analysis was also performed using ArrayExpress. A novel signal of PINX1 rs6984094 was identified (P _discovery = 4.13 × 10^-2, OR = 0.58, 95% CI 0.35-0.98) and successfully replicated (P _replication = 5.73 × 10^-3, OR = 0.45, 95% CI 0.26-0.81). Multiple layers of functional analysis suggested that the PINX1 rs6984094 risk T allele exhibited increased nuclear protein binding. We also observed an increased expression of PINX1 mRNA in peripheral blood mononuclear cells from SLE patients compared with healthy controls. Overall, we observed a novel genetic association between PINX1 (encodes the PinX1 protein, an inhibitory telomerase enzyme that lengthens telomeres) and SLE susceptibility in Chinese populations.

How natural selection shapes genetic differentiation in the MHC region: A case study with Native Americans

The Human Leukocyte Antigen (HLA) loci are extremely well documented targets of balancing selection, yet few studies have explored how selection affects population differentiation at these loci. In the present study we investigate genetic differentiation at HLA genes by comparing differentiation at microsatellites distributed genomewide to those in the MHC region. Our study uses a sample of 494 individuals from 30 human populations, 28 of which are Native Americans, all of whom were typed for genomewide and MHC region microsatellites. We find greater differentiation in the MHC than in the remainder of the genome (FST-MHC = 0.130 and FST-Genomic = 0.087), and use a permutation approach to show that this difference is statistically significant, and not accounted for by confounding factors. This finding lies in the opposite direction to the expectation that balancing selection reduces population differentiation. We interpret our findings as evidence that selection favors different sets of alleles in distinct localities, leading to increased differentiation. Thus, balancing selection at HLA genes simultaneously increases intra-population polymorphism and inter-population differentiation in Native Americans.

A genome-wide association study identifies novel gene associations with facial skin wrinkling and mole count in Latin Americans

BACKGROUND

Genome-wide association studies (GWASs) have identified genes influencing skin ageing and mole count in Europeans, but little is known about the relevance of these (or other genes) in non-Europeans.

OBJECTIVES

To conduct a GWAS for facial skin ageing and mole count in adults < 40 years old, of mixed European, Native American and African ancestry, recruited in Latin America.

METHODS

Skin ageing and mole count scores were obtained from facial photographs of over 6000 individuals. After quality control checks, three wrinkling traits and mole count were retained for genetic analyses. DNA samples were genotyped with Illumina's HumanOmniExpress chip. Association testing was performed on around 8 703 729 single-nucleotide polymorphisms (SNPs) across the autosomal genome.

RESULTS

Genome-wide significant association was observed at four genome regions: two were associated with wrinkling (in 1p13·3 and 21q21·2), one with mole count (in 1q32·3) and one with both wrinkling and mole count (in 5p13·2). Associated SNPs in 5p13·2 and in 1p13·3 are intronic within SLC45A2 and VAV3, respectively, while SNPs in 1q32·3 are near the SLC30A1 gene, and those in 21q21·2 occur in a gene desert. Analyses of SNPs in IRF4 and MC1R are consistent with a role of these genes in skin ageing.

CONCLUSIONS

We replicate the association of wrinkling with variants in SLC45A2, IRF4 and MC1R reported in Europeans. We identify VAV3 and SLC30A1 as two novel candidate genes impacting on wrinkling and mole count, respectively. We provide the first evidence that SLC45A2 influences mole count, in addition to variants in this gene affecting melanoma risk in Europeans.

Where do successful populations originate from?

In order to understand the dynamics of emergence and spreading of socio-technical innovations and population moves it is important to determine the place of origin of these populations. Here we focus on the role of geographical factors, such as land fertility and mountains in the context of human population evolution and distribution dynamics. We use a constrained diffusion-based computational model, computer simulations and the analysis of geographical and land-quality data. Our analysis shows that successful human populations, i.e. those which become dominant in their socio - geographical environment, originate from lands of many valleys with relatively low land fertility, which are close to areas of high land fertility. Many of the homelands predicted by our analysis match the assumed homelands of known successful populations (e.g. Bantus, Turkic, Maya). We also predict other likely homelands as well, where further archaeological, linguistic or genetic exploration may confirm the place of origin for populations with no currently identified urheimat. Our work is significant because it advances the understanding of human population dynamics by guiding the identification of the origin locations of successful populations.

Estimating FST and kinship for arbitrary population structures

F_ST and kinship are key parameters often estimated in modern population genetics studies in order to quantitatively characterize structure and relatedness. Kinship matrices have also become a fundamental quantity used in genome-wide association studies and heritability estimation. The most frequently-used estimators of F_ST and kinship are method-of-moments estimators whose accuracies depend strongly on the existence of simple underlying forms of structure, such as the independent subpopulations model of non-overlapping, independently evolving subpopulations. However, modern data sets have revealed that these simple models of structure likely do not hold in many populations, including humans. In this work, we analyze the behavior of these estimators in the presence of arbitrarily-complex population structures, which results in an improved estimation framework specifically designed for arbitrary population structures. After generalizing the definition of F_ST to arbitrary population structures and establishing a framework for assessing bias and consistency of genome-wide estimators, we calculate the accuracy of existing F_ST and kinship estimators under arbitrary population structures, characterizing biases and estimation challenges unobserved under their originally-assumed models of structure. We then present our new approach, which consistently estimates kinship and F_ST when the minimum kinship value in the dataset is estimated consistently. We illustrate our results using simulated genotypes from an admixture model, constructing a one-dimensional geographic scenario that departs nontrivially from the independent subpopulations model. Our simulations reveal the potential for severe biases in estimates of existing approaches that are overcome by our new framework. This work may significantly improve future analyses that rely on accurate kinship and F_ST estimates.

Kinship coefficients and F_ST, which measure relatedness and population structure, respectively, are important quantities needed to accurately perform various analyses on genetic data, including genome-wide association studies and heritability estimation. However, existing estimators require restrictive assumptions of independence that are not met by real human and other datasets. In this work we find that existing estimators can be severely biased under reasonable scenarios, first by theoretically determining their properties, and then using an admixture simulation to illustrate our findings. In particular, we find that existing F_ST estimators are downwardly biased, and that existing kinship matrix estimators have related biases that are on average downward and of similar magnitude but vary for every pair of individuals. These insights led us to a new estimation framework for kinship and F_ST that is practically unbiased for any population structure, as demonstrated by theory and simulations. Our new approaches—available as open-source R packages—are easy to use and are more widely applicable than existing approaches, and they are likely to improve downstream analyses that require accurate kinship and F_ST estimates.

The evolution of group differences in changing environments

The selection pressures that have shaped the evolution of complex traits in humans remain largely unknown, and in some contexts highly contentious, perhaps above all where they concern mean trait differences among groups. To date, the discussion has focused on whether such group differences have any genetic basis, and if so, whether they are without fitness consequences and arose via random genetic drift, or whether they were driven by selection for different trait optima in different environments. Here, we highlight a plausible alternative: that many complex traits evolve under stabilizing selection in the face of shifting environmental effects. Under this scenario, there will be rapid evolution at the loci that contribute to trait variation, even when the trait optimum remains the same. These considerations underscore the strong assumptions about environmental effects that are required in ascribing trait differences among groups to genetic differences.

Population dynamics in pre-Inca human groups from the Osmore Valley, the Azapa Valley and the coast of the South Central Andes

The present study applies a dental morphological perspective to the understanding of the complex pre-contact population history of the South Central Andes, through the detection of the underlying dynamics, and the assessment of the biological ties among groups. It presents an analysis of 1591 individuals from 66 sites that date from the Archaic to the Late Intermediate phases from Bolivia, Chile and Peru. The results suggest this area is characterized by significant movement of people and cultures and, at the same time, by long standing population continuity, and highlight the need for wider perspectives capable of taking into account both the different micro-regional realities and the region in its entirety.

Pervasive Selection against MicroRNA Target Sites in Human Populations

MicroRNA target sites are often conserved during evolution and purifying selection to maintain such sites is expected. On the other hand, comparative analyses identified a paucity of microRNA target sites in coexpressed transcripts, and novel target sites can potentially be deleterious. We proposed that selection against novel target sites pervasive. The analysis of derived allele frequencies revealed that, when the derived allele is a target site, the proportion of nontarget sites is higher than expected, particularly for highly expressed microRNAs. Thus, new alleles generating novel microRNA target sites can be deleterious and selected against. When we analyzed ancestral target sites, the derived (nontarget) allele frequency does not show statistical support for microRNA target allele conservation. We investigated the joint effects of microRNA conservation and expression and found that selection against microRNA target sites depends mostly on the expression level of the microRNA. We identified microRNA target sites with relatively high levels of population differentiation. However, when we analyze separately target sites in which the target allele is ancestral to the population, the proportion of single-nucleotide polymorphisms with high F_st significantly increases. These findings support that population differentiation is more likely in target sites that are lost than in the gain of new target sites. Our results indicate that selection against novel microRNA target sites is prevalent and, although individual sites may have a weak selective pressure, the overall effect across untranslated regions is not negligible and should be accounted when studying the evolution of genomic sequences.

Differential admixture in Latin American populations and its impact on the study of colorectal cancer

Genome-wide association studies focused on searching genes responsible for several diseases. Admixture mapping studies proposed a more efficient alternative capable of detecting polymorphisms contributing with a small effect on the disease risk. This method focuses on the higher values of linkage disequilibrium in admixed populations. To test this, we analyzed 10 genomic regions previously defined as related with colorectal cancer among nine populations and studied the variation pattern of haplotypic structures and heterozygosity values on seven categories of SNPs. Both analyses showed differences among chromosomal regions and studied populations. Admixed Latin-American samples generally show intermediate values. Heterozygosity of the SNPs grouped in categories varies more in each gene than in each population. African related populations have more blocks per chromosomal region, coherently with their antiquity. In sum, some similarities were found among Latin American populations, but each chromosomal region showed a particular behavior, despite the fact that the study refers to genes and regions related with one particular complex disease. This study strongly suggests the necessity of developing statistical methods to deal with di- or tri-hybrid populations, as well as to carefully analyze the different historic and demographic scenarios, and the different characteristics of particular chromosomal regions and evolutionary forces.

Development of a highly efficient 50K single nucleotide polymorphism genotyping array for the large and complex genome of Norway spruce (Picea abies L. Karst) by whole genome resequencing and its transferability to other spruce species

Norway spruce (Picea abies L. Karst) is one of the most important forest tree species with significant economic and ecological impact in Europe. For decades, genomic and genetic studies on Norway spruce have been challenging due to the large and repetitive genome (19.6 Gb with more than 70% being repetitive). To accelerate genomic studies, including population genetics, genome‐wide association studies (GWAS) and genomic selection (GS), in Norway spruce and related species, we here report on the design and performance of a 50K single nucleotide polymorphism (SNP) genotyping array for Norway spruce. The array is developed based on whole genome resequencing (WGS), making it the first WGS‐based SNP array in any conifer species so far. After identifying SNPs using genome resequencing data from 29 trees collected in northern Europe, we adopted a two‐step approach to design the array. First, we built a 450K screening array and used this to genotype a population of 480 trees sampled from both natural and breeding populations across the Norway spruce distribution range. These samples were then used to select high‐confidence probes that were put on the final 50K array. The SNPs selected are distributed over 45,552 scaffolds from the P. abies version 1.0 genome assembly and target 19,954 unique gene models with an even coverage of the 12 linkage groups in Norway spruce. We show that the array has a 99.5% probe specificity, >98% Mendelian allelic inheritance concordance, an average sample call rate of 96.30% and an SNP call rate of 98.90% in family trios and haploid tissues. We also observed that 23,797 probes (50%) could be identified with high confidence in three other spruce species (white spruce [Picea glauca], black spruce [P. mariana] and Sitka spruce [P. sitchensis]). The high‐quality genotyping array will be a valuable resource for genetic and genomic studies in Norway spruce as well as in other conifer species of the same genus.

Genomic insights on the contribution of balancing selection and local adaptation to the long-term survival of a widespread living fossil tree, Cercidiphyllum japonicum

'Living fossils' are testimonies of long-term sustained ecological success, but how demographic history and natural selection contributed to their survival, resilience, and persistence in the face of Quaternary climate fluctuations remains unclear. To better understand the interplay between demographic history and selection in shaping genomic diversity and evolution of such organisms, we assembled the whole genome of Cercidiphyllum japonicum, a widespread East Asian Tertiary relict tree, and resequenced 99 individuals of C. japonicum and its sister species, Cercidiphyllum magnificum (Central Japan). We dated this speciation event to the mid-Miocene, and the intraspecific lineage divergence of C. japonicum (China vs Japan) to the Early Pliocene. Throughout climatic upheavals of the late Tertiary/Quaternary, population bottlenecks greatly reduced the genetic diversity of C. japonicum. However, this polymorphism loss was likely counteracted by, first, long-term balancing selection at multiple chromosomal and heterozygous gene regions, potentially reflecting overdominance, and, second, selective sweeps at stress response and growth-related genes likely involved in local adaptation. Our findings contribute to a better understanding of how living fossils have survived climatic upheaval and maintained an extensive geographic range; that is, both types of selection could be major factors contributing to the species' survival, resilience, and persistence.

Demographic history and selection at HLA loci in Native Americans

The American continent was the last to be occupied by modern humans, and native populations bear the marks of recent expansions, bottlenecks, natural selection, and population substructure. Here we investigate how this demographic history has shaped genetic variation at the strongly selected HLA loci. In order to disentangle the relative contributions of selection and demography process, we assembled a dataset with genome-wide microsatellites and HLA-A, -B, -C, and -DRB1 typing data for a set of 424 Native American individuals. We find that demographic history explains a sizeable fraction of HLA variation, both within and among populations. A striking feature of HLA variation in the Americas is the existence of alleles which are present in the continent but either absent or very rare elsewhere in the world. We show that this feature is consistent with demographic history (i.e., the combination of changes in population size associated with bottlenecks and subsequent population expansions). However, signatures of selection at HLA loci are still visible, with significant evidence selection at deeper timescales for most loci and populations, as well as population differentiation at HLA loci exceeding that seen at neutral markers.

Positive selection in admixed populations from Ethiopia

BACKGROUND

In the process of adaptation of humans to their environment, positive or adaptive selection has played a main role. Positive selection has, however, been under-studied in African populations, despite their diversity and importance for understanding human history.

RESULTS

Here, we have used 119 available whole-genome sequences from five Ethiopian populations (Amhara, Oromo, Somali, Wolayta and Gumuz) to investigate the modes and targets of positive selection in this part of the world. The site frequency spectrum-based test SFselect was applied to idfentify a wide range of events of selection (old and recent), and the haplotype-based statistic integrated haplotype score to detect more recent events, in each case with evaluation of the significance of candidate signals by extensive simulations. Additional insights were provided by considering admixture proportions and functional categories of genes. We identified both individual loci that are likely targets of classic sweeps and groups of genes that may have experienced polygenic adaptation. We found population-specific as well as shared signals of selection, with folate metabolism and the related ultraviolet response and skin pigmentation standing out as a shared pathway, perhaps as a response to the high levels of ultraviolet irradiation, and in addition strong signals in genes such as IFNA, MRC1, immunoglobulins and T-cell receptors which contribute to defend against pathogens.

CONCLUSIONS

Signals of positive selection were detected in Ethiopian populations revealing novel adaptations in East Africa, and abundant targets for functional follow-up.

The search for sexually antagonistic genes: Practical insights from studies of local adaptation and statistical genomics

Sexually antagonistic (SA) genetic variation-in which alleles favored in one sex are disfavored in the other-is predicted to be common and has been documented in several animal and plant populations, yet we currently know little about its pervasiveness among species or its population genetic basis. Recent applications of genomics in studies of SA genetic variation have highlighted considerable methodological challenges to the identification and characterization of SA genes, raising questions about the feasibility of genomic approaches for inferring SA selection. The related fields of local adaptation and statistical genomics have previously dealt with similar challenges, and lessons from these disciplines can therefore help overcome current difficulties in applying genomics to study SA genetic variation. Here, we integrate theoretical and analytical concepts from local adaptation and statistical genomics research-including F ST and F IS statistics, genome-wide association studies, pedigree analyses, reciprocal transplant studies, and evolve-and-resequence experiments-to evaluate methods for identifying SA genes and genome-wide signals of SA genetic variation. We begin by developing theoretical models for between-sex F ST and F IS, including explicit null distributions for each statistic, and using them to critically evaluate putative multilocus signals of sex-specific selection in previously published datasets. We then highlight new statistics that address some of the limitations of F ST and F IS, along with applications of more direct approaches for characterizing SA genetic variation, which incorporate explicit fitness measurements. We finish by presenting practical guidelines for the validation and evolutionary analysis of candidate SA genes and discussing promising empirical systems for future work.

Population Structure, Stratification, and Introgression of Human Structural Variation

Structural variants contribute substantially to genetic diversity and are important evolutionarily and medically, but they are still understudied. Here we present a comprehensive analysis of structural variation in the Human Genome Diversity panel, a high-coverage dataset of 911 samples from 54 diverse worldwide populations. We identify, in total, 126,018 variants, 78% of which were not identified in previous global sequencing projects. Some reach high frequency and are private to continental groups or even individual populations, including regionally restricted runaway duplications and putatively introgressed variants from archaic hominins. By de novo assembly of 25 genomes using linked-read sequencing, we discover 1,643 breakpoint-resolved unique insertions, in aggregate accounting for 1.9 Mb of sequence absent from the GRCh38 reference. Our results illustrate the limitation of a single human reference and the need for high-quality genomes from diverse populations to fully discover and understand human genetic variation.

Identifying and Classifying Shared Selective Sweeps from Multilocus Data

Positive selection causes beneficial alleles to rise to high frequency, resulting in a selective sweep of the diversity surrounding the selected sites. Accordingly, the signature of a selective sweep in an ancestral population may still remain in its descendants. Identifying signatures of selection in the ancestor that are shared among its descendants is important to contextualize the timing of a sweep, but few methods exist for this purpose. We introduce the statistic SS-H12, which can identify genomic regions under shared positive selection across populations and is based on the theory of the expected haplotype homozygosity statistic H12, which detects recent hard and soft sweeps from the presence of high-frequency haplotypes. SS-H12 is distinct from comparable statistics because it requires a minimum of only two populations, and properly identifies and differentiates between independent convergent sweeps and true ancestral sweeps, with high power and robustness to a variety of demographic models. Furthermore, we can apply SS-H12 in conjunction with the ratio of statistics we term [Formula: see text] and [Formula: see text] to further classify identified shared sweeps as hard or soft. Finally, we identified both previously reported and novel shared sweep candidates from human whole-genome sequences. Previously reported candidates include the well-characterized ancestral sweeps at LCT and SLC24A5 in Indo-Europeans, as well as GPHN worldwide. Novel candidates include an ancestral sweep at RGS18 in sub-Saharan Africans involved in regulating the platelet response and implicated in sudden cardiac death, and a convergent sweep at C2CD5 between European and East Asian populations that may explain their different insulin responses.

Genomic landscape of the signals of positive natural selection in populations of Northern Eurasia: A view from Northern Russia

Natural selection of beneficial genetic variants played a critical role in human adaptation to a wide range of environmental conditions. Northern Eurasia, despite its severe climate, is home to lots of ethnically diverse populations. The genetic variants associated with the survival of these populations have hardly been analyzed. We searched for the genomic signatures of positive selection in (1) the genome-wide microarray data of 432 people from eight different northern Russian populations and (2) the whole-genome sequences of 250 people from Northern Eurasia from a public repository through testing the extended haplotype homozigosity (EHH) and direct comparison of allele frequency, respectively. The 20 loci with the strongest selection signals were characterized in detail. Among the top EHH hits were the NRG3 and NBEA genes, which are involved in the development and functioning of the neural system, the PTPRM gene, which mediates cell-cell interactions and adhesion, and a region on chromosome 4 (chr4:28.7-28.9 Mb) that contained several loci affiliated with different classes of non-coding RNAs (RN7SL101P, MIR4275, MESTP3, and LINC02364). NBEA and the region on chromosome 4 were novel selection targets that were identified for the first time in Western Siberian populations. Cross-population comparisons of EHH profiles suggested a particular role for the chr4:28.7-28.9 Mb region in the local adaptation of Western Siberians. The strongest selection signal identified in Siberian sequenced genomes was formed by six SNPs on chromosome 11 (chr11:124.9-125.2 Mb). This region included well-known genes SLC37A2 and PKNOX2. SLC37A2 is most-highly expressed in the gut. Its expression is regulated by vitamin D, which is often deficient in northern regions. The PKNOX2 gene is a transcription factor of the homeobox family that is expressed in the brain and many other tissues. This gene is associated with alcohol addiction, which is widespread in many Northern Eurasian populations.

In the presence of population structure: From genomics to candidate genes underlying local adaptation

Understanding the genomic signatures, genes, and traits underlying local adaptation of organisms to heterogeneous environments is of central importance to the field evolutionary biology. To identify loci underlying local adaptation, models that combine allelic and environmental variation while controlling for the effects of population structure have emerged as the method of choice. Despite being evaluated in simulation studies, there has not been a thorough investigation of empirical evidence supporting local adaptation across these alleles. To evaluate these methods, we use 875 Arabidopsis thaliana Eurasian accessions and two mixed models (GEMMA and LFMM) to identify candidate SNPs underlying local adaptation to climate. Subsequently, to assess evidence of local adaptation and function among significant SNPs, we examine allele frequency differentiation and recent selection across Eurasian populations, in addition to their distribution along quantitative trait loci (QTL) explaining fitness variation between Italy and Sweden populations and cis-regulatory/nonsynonymous sites showing significant selective constraint. Our results indicate that significant LFMM/GEMMA SNPs show low allele frequency differentiation and linkage disequilibrium across locally adapted Italy and Sweden populations, in addition to a poor association with fitness QTL peaks (highest logarithm of odds score). Furthermore, when examining derived allele frequencies across the Eurasian range, we find that these SNPs are enriched in low-frequency variants that show very large climatic differentiation but low levels of linkage disequilibrium. These results suggest that their enrichment along putative functional sites most likely represents deleterious variation that is independent of local adaptation. Among all the genomic signatures examined, only SNPs showing high absolute allele frequency differentiation (AFD) and linkage disequilibrium (LD) between Italy and Sweden populations showed a strong association with fitness QTL peaks and were enriched along selectively constrained cis-regulatory/nonsynonymous sites. Using these SNPs, we find strong evidence linking flowering time, freezing tolerance, and the abscisic-acid pathway to local adaptation.

Multiple selective sweeps of ancient polymorphisms in and around LTα located in the MHC class III region on chromosome 6

BACKGROUND

Lymphotoxin-α (LTα), located in the Major Histocompatibility Complex (MHC) class III region on chromosome 6, encodes a cytotoxic protein that mediates a variety of antiviral responses among other biological functions. Furthermore, several genotypes at this gene have been implicated in the onset of a number of complex diseases, including myocardial infarction, autoimmunity, and various types of cancer. However, little is known about levels of nucleotide variation and linkage disequilibrium (LD) in and near LTα, which could also influence phenotypic variance. To address this gap in knowledge, we examined sequence variation across ~ 10 kilobases (kbs), encompassing LTα and the upstream region, in 2039 individuals from the 1000 Genomes Project originating from 21 global populations.

RESULTS

Here, we observed striking patterns of diversity, including an excess of intermediate-frequency alleles, the maintenance of multiple common haplotypes and a deep coalescence time for variation (dating > 1.0 million years ago), in global populations. While these results are generally consistent with a model of balancing selection, we also uncovered a signature of positive selection in the form of long-range LD on chromosomes with derived alleles primarily in Eurasian populations. To reconcile these findings, which appear to support different models of selection, we argue that selective sweeps (particularly, soft sweeps) of multiple derived alleles in and/or near LTα occurred in non-Africans after their ancestors left Africa. Furthermore, these targets of selection were predicted to alter transcription factor binding site affinity and protein stability, suggesting they play a role in gene function. Additionally, our data also showed that a subset of these functional adaptive variants are present in archaic hominin genomes.

CONCLUSIONS

Overall, this study identified candidate functional alleles in a biologically-relevant genomic region, and offers new insights into the evolutionary origins of these loci in modern human populations.