Cross-pollination in seed-blended refuge and selection for Vip3A resistance in a lepidopteran pest as detected by genomic monitoring.

The evolution of pest resistance to management tools reduces productivity and results in economic losses in agricultural systems. To slow its emergence and spread, monitoring and prevention practices are implemented in resistance management programs. Recent work suggests that genomic approaches can identify signs of emerging resistance to aid in resistance management. Here, we empirically examined the sensitivity of genomic monitoring for resistance management in transgenic Bt crops, a globally important agricultural innovation. Whole genome resequencing of wild North American Helicoverpa zea collected from non-expressing refuge and plants expressing Cry1Ab confirmed that resistance-associated signatures of selection were detectable after a single generation of exposure. Upon demonstrating its sensitivity, we applied genomic monitoring to wild H. zea that survived Vip3A exposure resulting from cross-pollination of refuge plants in seed-blended plots. Refuge seed interplanted with transgenic seed exposed H. zea to sublethal doses of Vip3A protein in corn ears and was associated with allele frequency divergence across the genome. Some of the greatest allele frequency divergence occurred in genomic regions adjacent to a previously described candidate gene for Vip3A resistance. Our work highlights the power of genomic monitoring to sensitively detect heritable changes associated with field exposure to Bt toxins and suggests that seed-blended refuge will likely hasten the evolution of resistance to Vip3A in lepidopteran pests.

The "New Synthesis".

When Mendel's work was rediscovered in 1900, and extended to establish classical genetics, it was initially seen in opposition to Darwin's theory of evolution by natural selection on continuous variation, as represented by the biometric research program that was the foundation of quantitative genetics. As Fisher, Haldane, and Wright established a century ago, Mendelian inheritance is exactly what is needed for natural selection to work efficiently. Yet, the synthesis remains unfinished. We do not understand why sexual reproduction and a fair meiosis predominate in eukaryotes, or how far these are responsible for their diversity and complexity. Moreover, although quantitative geneticists have long known that adaptive variation is highly polygenic, and that this is essential for efficient selection, this is only now becoming appreciated by molecular biologists-and we still do not have a good framework for understanding polygenic variation or diffuse function.

Polygenic dynamics underlying the response of quantitative traits to directional selection.

We study the response of a quantitative trait to exponential directional selection in a finite haploid population, both at the genetic and the phenotypic level. We assume an infinite sites model, in which the number of new mutations per generation in the population follows a Poisson distribution (with mean Θ) and each mutation occurs at a new, previously monomorphic site. Mutation effects are beneficial and drawn from a distribution. Sites are unlinked and contribute additively to the trait. Assuming that selection is stronger than random genetic drift, we model the initial phase of the dynamics by a supercritical Galton-Watson process. This enables us to obtain time-dependent results. We show that the copy-number distribution of the mutant in generation n, conditioned on non-extinction until n, is described accurately by the deterministic increase from an initial distribution with mean 1. This distribution is related to the absolutely continuous part W+ of the random variable, typically denoted W, that characterizes the stochasticity accumulating during the mutant's sweep. A suitable transformation yields the approximate dynamics of the mutant frequency distribution in a Wright-Fisher population of size N. Our expression provides a very accurate approximation except when mutant frequencies are close to 1. On this basis, we derive explicitly the (approximate) time dependence of the expected mean and variance of the trait and of the expected number of segregating sites. Unexpectedly, we obtain highly accurate approximations for all times, even for the quasi-stationary phase when the expected per-generation response and the trait variance have equilibrated. The latter refine classical results. In addition, we find that Θ is the main determinant of the pattern of adaptation at the genetic level, i.e., whether the initial allele-frequency dynamics are best described by sweep-like patterns at few loci or small allele-frequency shifts at many. The number of segregating sites is an appropriate indicator for these patterns. The selection strength determines primarily the rate of adaptation. The accuracy of our results is tested by comprehensive simulations in a Wright-Fisher framework. We argue that our results apply to more complex forms of directional selection.

Genome evolution in an agricultural pest following adoption of transgenic crops.

Replacing synthetic insecticides with transgenic crops for pest management has been economically and environmentally beneficial, but these benefits erode as pests evolve resistance. It has been proposed that novel genomic approaches could track molecular signals of emerging resistance to aid in resistance management. To test this, we quantified patterns of genomic change in Helicoverpa zea, a major lepidopteran pest and target of transgenic Bacillus thuringiensis (Bt) crops, between 2002 and 2017 as both Bt crop adoption and resistance increased in North America. Genomic scans of wild H. zea were paired with quantitative trait locus (QTL) analyses and showed the genomic architecture of field-evolved Cry1Ab resistance was polygenic, likely arising from standing genetic variation. Resistance to pyramided Cry1A.105 and Cry2Ab2 toxins was controlled by fewer loci. Of the 11 previously described Bt resistance genes, 9 showed no significant change over time or major effects on resistance. We were unable to rule out a contribution of aminopeptidases (apns), as a cluster of apn genes were found within a Cry-associated QTL. Molecular signals of emerging Bt resistance were detectable as early as 2012 in our samples, and we discuss the potential and pitfalls of whole-genome analysis for resistance monitoring based on our findings. This first study of Bt resistance evolution using whole-genome analysis of field-collected specimens demonstrates the need for a more holistic approach to examining rapid adaptation to novel selection pressures in agricultural ecosystems.

Evidence of Polygenic Adaptation in Sardinia at Height-Associated Loci Ascertained from the Biobank Japan.

Adult height is one of the earliest putative examples of polygenic adaptation in humans. However, this conclusion was recently challenged because residual uncorrected stratification from large-scale consortium studies was considered responsible for the previously noted genetic difference. It thus remains an open question whether height loci exhibit signals of polygenic adaptation in any human population. We re-examined this question, focusing on one of the shortest European populations, the Sardinians, in addition to mainland European populations. We utilized height-associated loci from the Biobank Japan (BBJ) dataset to further alleviate concerns of biased ascertainment of GWAS loci and showed that the Sardinians remain significantly shorter than expected under neutrality (∼0.22 standard deviation shorter than Utah residents with ancestry from northern and western Europe [CEU] on the basis of polygenic height scores, p = 3.89 × 10-4). We also found the trajectory of polygenic height scores between the Sardinian and the British populations diverged over at least the last 10,000 years (p = 0.0082), consistent with a signature of polygenic adaptation driven primarily by the Sardinian population. Although the polygenic score-based analysis showed a much subtler signature in mainland European populations, we found a clear and robust adaptive signature in the UK population by using a haplotype-based statistic, the trait singleton density score (tSDS), driven by the height-increasing alleles (p = 9.1 × 10-4). In summary, by ascertaining height loci in a distant East Asian population, we further supported the evidence of polygenic adaptation at height-associated loci among the Sardinians. In mainland Europeans, the adaptive signature was detected in haplotype-based analysis but not in polygenic score-based analysis.

Genomic vulnerability to climate change in Quercus acutissima, a dominant tree species in East Asian deciduous forests.

Understanding the evolutionary processes that shape the landscape of genetic variation and influence the response of species to future climate change is critical for biodiversity conservation. Here, we sampled 27 populations across the distribution range of a dominant forest tree, Quercus acutissima, in East Asia, and applied genome-wide analyses to track the evolutionary history and predict the fate of populations under future climate. We found two genetic groups (East and West) in Q. acutissima that diverged during Pliocene. We also found a heterogeneous landscape of genomic variation in this species, which may have been shaped by population demography and linked selections. Using genotype-environment association analyses, we identified climate-associated SNPs in a diverse set of genes and functional categories, indicating a model of polygenic adaptation in Q. acutissima. We further estimated three genetic offset metrics to quantify genomic vulnerability of this species to climate change due to the complex interplay between local adaptation and migration. We found that marginal populations are under higher risk of local extinction because of future climate change, and may not be able to track suitable habitats to maintain the gene-environment relationships observed under the current climate. We also detected higher reverse genetic offsets in northern China, indicating that genetic variation currently present in the whole range of Q. acutissima may not adapt to future climate conditions in this area. Overall, this study illustrates how evolutionary processes have shaped the landscape of genomic variation, and provides a comprehensive genome-wide view of climate maladaptation in Q. acutissima.

Nonparallel genome changes within subpopulations over time contributed to genetic diversity within the US Holstein population.

Maintaining genetic variation in a population is important for long-term genetic gain. The existence of subpopulations within a breed helps maintain genetic variation and diversity. The 20,990 genotyped animals, representing the breeding animals in the year 2014, were identified as the sires of animals born after 2010 with at least 25 progenies, and females measured for type traits within the last 2 yr of data. K-means clustering with 5 clusters (C1, C2, C3, C4, and C5) was applied to the genomic relationship matrix based on 58,990 SNP markers to stratify the selected candidates into subpopulations. The general higher inbreeding resulting from within-cluster mating than across-cluster mating suggests the successful stratification into genetically different groups. The largest cluster (C4) contained animals that were less related to each animal within and across clusters. The average fixation index was 0.03, indicating that the populations were differentiated, and allele differences across the subpopulations were not due to drift alone. Starting with the selected candidates within each cluster, a family unit was identified by tracing back through the pedigree, identifying the genotyped ancestors, and assigning them to a pseudogeneration. Each of the 5 families (F1, F2, F3, F4, and F5) was traced back for 10 generations, allowing for changes in frequency of individual SNPs over time to be observed, which we call allele frequencies change. Alternative procedures were used to identify SNPs changing in a parallel or nonparallel way across families. For example, markers that have changed the most in the whole population, markers that have changed differently across families, and genes previously identified as those that have changed in allele frequency. The genomic trajectory taken by each family involves selective sweeps, polygenic changes, hitchhiking, and epistasis. The replicate frequency spectrum was used to measure the similarity of change across families and showed that populations have changed differently. The proportion of markers that reversed direction in allele frequency change varied from 0.00 to 0.02 if the rate of change was greater than 0.02 per generation, or from 0.14 to 0.24 if the rate of change was greater than 0.005 per generation within each family. Cluster-specific SNP effects for stature were estimated using only females and applied to obtain indirect genomic predictions for males. Reranking occurs depending on SNP effects used. Additive genetic correlations between clusters show possible differences in populations. Further research is required to determine how this knowledge can be applied to maintain diversity and optimize selection decisions in the future.

Molecular Parallelism Underlies Convergent Highland Adaptation of Maize Landraces.

Convergent phenotypic evolution provides some of the strongest evidence for adaptation. However, the extent to which recurrent phenotypic adaptation has arisen via parallelism at the molecular level remains unresolved, as does the evolutionary origin of alleles underlying such adaptation. Here, we investigate genetic mechanisms of convergent highland adaptation in maize landrace populations and evaluate the genetic sources of recurrently selected alleles. Population branch excess statistics reveal substantial evidence of parallel adaptation at the level of individual single-nucleotide polymorphism (SNPs), genes, and pathways in four independent highland maize populations. The majority of convergently selected SNPs originated via migration from a single population, most likely in the Mesoamerican highlands, while standing variation introduced by ancient gene flow was also a contributor. Polygenic adaptation analyses of quantitative traits reveal that alleles affecting flowering time are significantly associated with elevation, indicating the flowering time pathway was targeted by highland adaptation. In addition, repeatedly selected genes were significantly enriched in the flowering time pathway, indicating their significance in adapting to highland conditions. Overall, our study system represents a promising model to study convergent evolution in plants with potential applications to crop adaptation across environmental gradients.

Thinking About the Evolution of Complex Traits in the Era of Genome-Wide Association Studies.

Many traits of interest are highly heritable and genetically complex, meaning that much of the variation they exhibit arises from differences at numerous loci in the genome. Complex traits and their evolution have been studied for more than a century, but only in the last decade have genome-wide association studies (GWASs) in humans begun to reveal their genetic basis. Here, we bring these threads of research together to ask how findings from GWASs can further our understanding of the processes that give rise to heritable variation in complex traits and of the genetic basis of complex trait evolution in response to changing selection pressures (i.e., of polygenic adaptation). Conversely, we ask how evolutionary thinking helps us to interpret findings from GWASs and informs related efforts of practical importance.

Signatures of polygenic adaptation align with genome-wide methylation patterns in wild strawberry plants.

Epigenetic inheritance can drive adaptive evolution independently of DNA sequence variation. However, to what extent epigenetic variation represents an autonomous evolutionary force remains largely elusive. Through gene ontology and comparative analyses of genomic and epigenomic variation of wild strawberry plants raised in distinct drought settings, we characterised genome-wide covariation between single nucleotide polymorphisms (SNPs) and differentially methylated cytosines (DMCs). Covariation between SNPs and DMCs was independent of genomic proximity, but instead associated with fitness-related processes such as stress responses, genome regulation and reproduction. We expected this functional SNP-DMC covariation to be driven by adaptive evolution canalising SNP and DMC variation, but instead observed significantly lower covariation with DMCs for adaptive rather than for neutral SNPs. Drought-induced DMCs frequently co-varied with tens of SNPs, suggesting high genomic redundancy as a broad potential basis for polygenic adaptation of gene expression. Our findings suggest that stress-responsive DMCs initially co-vary with many SNPs under increased environmental stress, and that natural selection acting upon several of these SNPs subsequently reduces standing covariation with stress-responsive DMCs. Our study supports DNA methylation profiles that represent complex quantitative traits rather than autonomous evolutionary forces. We provide a conceptual framework for polygenic regulation and adaptation shaping genome-wide methylation patterns in plants.

Gene Expression Modularity Reveals Footprints of Polygenic Adaptation in Theobroma cacao.

Separating footprints of adaptation from demography is challenging. When selection has acted on a single locus with major effect, this issue can be alleviated through signatures left by selective sweeps. However, as adaptation is often driven by small allele frequency shifts at many loci, studies focusing on single genes are able to identify only a small portion of genomic variants responsible for adaptation. In face of this challenge, we utilize coexpression information to search for signals of polygenetic adaptation in Theobroma cacao, a tropical tree species that is the source of chocolate. Using transcriptomics and a weighted correlation network analysis, we group genes with similar expression patterns into functional modules. We then ask whether modules enriched for specific biological processes exhibit cumulative effects of differential selection in the form of high FST and dXY between populations. Indeed, modules putatively involved in protein modification, flowering, and water transport show signs of polygenic adaptation even though individual genes that are members of those groups do not bear strong signatures of selection. Modeling of demography, background selection, and the effects of genomic features reveal that these patterns are unlikely to arise by chance. We also find that specific modules are enriched for signals of strong or relaxed purifying selection, with one module bearing signs of adaptive differentiation and an excess of deleterious mutations. Our results provide insight into polygenic adaptation and contribute to understanding of population structure, demographic history, and genome evolution in T. cacao.

Genomic history of the Italian population recapitulates key evolutionary dynamics of both Continental and Southern Europeans.

BACKGROUND: The cline of human genetic diversity observable across Europe is recapitulated at a micro-geographic scale by variation within the Italian population. Besides resulting from extensive gene flow, this might be ascribable also to local adaptations to diverse ecological contexts evolved by people who anciently spread along the Italian Peninsula. Dissecting the evolutionary history of the ancestors of present-day Italians may thus improve the understanding of demographic and biological processes that contributed to shape the gene pool of European populations. However, previous SNP array-based studies failed to investigate the full spectrum of Italian variation, generally neglecting low-frequency genetic variants and examining a limited set of small effect size alleles, which may represent important determinants of population structure and complex adaptive traits. To overcome these issues, we analyzed 38 high-coverage whole-genome sequences representative of population clusters at the opposite ends of the cline of Italian variation, along with a large panel of modern and ancient Euro-Mediterranean genomes. RESULTS: We provided evidence for the early divergence of Italian groups dating back to the Late Glacial and for Neolithic and distinct Bronze Age migrations having further differentiated their gene pools. We inferred adaptive evolution at insulin-related loci in people from Italian regions with a temperate climate, while possible adaptations to pathogens and ultraviolet radiation were observed in Mediterranean Italians. Some of these adaptive events may also have secondarily modulated population disease or longevity predisposition. CONCLUSIONS: We disentangled the contribution of multiple migratory and adaptive events in shaping the heterogeneous Italian genomic background, which exemplify population dynamics and gene-environment interactions that played significant roles also in the formation of the Continental and Southern European genomic landscapes.

Fungal heavy metal adaptation through single nucleotide polymorphisms and copy-number variation.

Human-altered environments can shape the evolution of organisms. Fungi are no exception, although little is known about how they withstand anthropogenic pollution. Here, we document adaptation in the mycorrhizal fungus Suillus luteus driven by soil heavy metal contamination. Genome scans across individuals from recently polluted and nearby unpolluted soils in Belgium revealed low divergence across isolates and no evidence of population structure based on soil type. However, we detected single nucleotide polymorphism divergence and gene copy-number variation, with different genetic combinations potentially conferring the ability to persist in contaminated soils. Variants were shared across the population but found to be under selection in isolates exposed to pollution and located across the genome, including in genes involved in metal exclusion, storage, immobilization and reactive oxygen species detoxification. Together, our results point to S. luteus undergoing the initial steps of adaptive divergence and contribute to understanding the processes underlying local adaptation under strong environmental selection.

Selection signatures for high-altitude adaptation in ruminants.

High-altitude areas are important socio-economical habitats with ruminants serving as a major source of food and commodities for humans. Living at high altitude, however, is extremely challenging, predominantly due to the exposure to hypoxic conditions, but also because of cold temperatures and limited feed for livestock. To survive in high-altitude environments over the long term, ruminants have evolved adaptation strategies, e.g. physiological and morphological modifications, which allow them to cope with these harsh conditions. Identification of such selection signatures in ruminants may contribute to more informed breeding decisions, and thus improved productivity. Moreover, studying the genetic background of altitude adaptation in ruminants provides insights into a common molecular basis across species and thus a better understanding of the physiological basis of this adaptation. In this paper, we review the major effects of high altitude on the mammalian body and highlight some of the most important short-term (coping) and genetically evolved (adaptation) physiological modifications. We then discuss the genetic architecture of altitude adaptation and target genes that show evidence of being under selection based on recent studies in various species, with a focus on ruminants. The yak is presented as an interesting native species that has adapted to the high-altitude regions of Tibet. Finally, we conclude with implications and challenges of selection signature studies on altitude adaptation in general. We found that the number of studies on genetic mechanisms that enable altitude adaptation in ruminants is growing, with a strong focus on identifying selection signatures, and hypothesise that the investigation of genetic data from multiple species and regions will contribute greatly to the understanding of the genetic basis of altitude adaptation.

Population genomics of rapid evolution in natural populations: polygenic selection in response to power station thermal effluents.

BACKGROUND: Examples of rapid evolution are common in nature but difficult to account for with the standard population genetic model of adaptation. Instead, selection from the standing genetic variation permits rapid adaptation via soft sweeps or polygenic adaptation. Empirical evidence of this process in nature is currently limited but accumulating. RESULTS: We provide genome-wide analyses of rapid evolution in Fundulus heteroclitus populations subjected to recently elevated temperatures due to coastal power station thermal effluents using 5449 SNPs across two effluent-affected and four reference populations. Bayesian and multivariate analyses of population genomic structure reveal a substantial portion of genetic variation that is most parsimoniously explained by selection at the site of thermal effluents. An FST outlier approach in conjunction with additional conservative requirements identify significant allele frequency differentiation that exceeds neutral expectations among exposed and closely related reference populations. Genomic variation patterns near these candidate loci reveal that individuals living near thermal effluents have rapidly evolved from the standing genetic variation through small allele frequency changes at many loci in a pattern consistent with polygenic selection on the standing genetic variation. CONCLUSIONS: While the ultimate trajectory of selection in these populations is unknown and we survey only a minority of genomic loci, our findings suggest that polygenic models of adaptation may play important roles in large, natural populations experiencing recent selection due to environmental changes that cause broad physiological impacts.

Recombination Alters the Dynamics of Adaptation on Standing Variation in Laboratory Yeast Populations.

The rates and selective effects of beneficial mutations, together with population genetic factors such as population size and recombination rate, determine the outcomes of adaptation and the signatures this process leaves in patterns of genetic diversity. Previous experimental studies of microbial evolution have focused primarily on initially clonal populations, finding that adaptation is characterized by new strongly selected beneficial mutations that sweep rapidly to fixation. Here, we study evolution in diverse outcrossed yeast populations, tracking the rate and genetic basis of adaptation over time. We combine time-serial measurements of fitness and allele frequency changes in 18 populations of budding yeast evolved at different outcrossing rates to infer the drivers of adaptation on standing genetic variation. In contrast to initially clonal populations, we find that adaptation is driven by a large number of weakly selected, linked variants. Populations undergoing different rates of outcrossing make use of this selected variation differently: whereas asexual populations evolve via rapid, inefficient, and highly variable fixation of clones, sexual populations adapt continuously by gradually breaking down linkage disequilibrium between selected variants. Our results demonstrate how recombination can sustain adaptation over long timescales by inducing a transition from selection on genotypes to selection on individual alleles, and show how pervasive linked selection can affect evolutionary dynamics.

Evolutionary genomics of gypsy moth populations sampled along a latitudinal gradient.

The European gypsy moth (Lymantria dispar L.) was first introduced to Massachusetts in 1869 and within 150 years has spread throughout eastern North America. This large-scale invasion across a heterogeneous landscape allows examination of the genetic signatures of adaptation potentially associated with rapid geographical spread. We tested the hypothesis that spatially divergent natural selection has driven observed changes in three developmental traits that were measured in a common garden for 165 adult moths sampled from six populations across a latitudinal gradient covering the entirety of the range. We generated genotype data for 91,468 single nucleotide polymorphisms based on double digest restriction-site associated DNA sequencing and used these data to discover genome-wide associations for each trait, as well as to test for signatures of selection on the discovered architectures. Genetic structure across the introduced range of gypsy moth was low in magnitude (FST  = 0.069), with signatures of bottlenecks and spatial expansion apparent in the rare portion of the allele frequency spectrum. Results from applications of Bayesian sparse linear mixed models were consistent with the presumed polygenic architectures of each trait. Further analyses indicated spatially divergent natural selection acting on larval development time and pupal mass, with the linkage disequilibrium component of this test acting as the main driver of observed patterns. The populations most important for these signals were two range-edge populations established less than 30 generations ago. We discuss the importance of rapid polygenic adaptation to the ability of non-native species to invade novel environments.

Regulatory and sequence evolution in response to selection for improved associative learning ability in Nasonia vitripennis.

BACKGROUND: Selection acts on the phenotype, yet only the genotype is inherited. While both the phenotypic and genotypic response to short-term selection can be measured, the link between these is a major unsolved problem in evolutionary biology, in particular for complex behavioural phenotypes. RESULTS: Here we characterize the genomic and the transcriptomic basis of associative learning ability in the parasitic wasp Nasonia vitripennis and use gene network analysis to link the two. We artificially selected for improved associative learning ability in four independent pairs of lines and identified signatures of selection across the genome. Allele frequency diverged consistently between the selected and control lines in 118 single nucleotide polymorphisms (SNPs), clustering in 51 distinct genomic regions containing 128 genes. The majority of SNPs were found in regulatory regions, suggesting a potential role for gene expression evolution. We therefore sequenced the transcriptomes of selected and control lines and identified 36 consistently differentially expressed transcripts with large changes in expression. None of the differentially expressed genes also showed sequence divergence as a result of selection. Instead, gene network analysis showed many of the genes with consistent allele frequency differences and all of the differentially expressed genes to cluster in a single co-expression network. At a functional level, both genomic and transcriptomic analyses implicated members of gene networks known to be involved in neural plasticity and cognitive processes. CONCLUSIONS: Taken together, our results reveal how specific cognitive abilities can readily respond to selection via a complex interplay between regulatory and sequence evolution.

Artificial Selection Response due to Polygenic Adaptation from a Multilocus, Multiallelic Genetic Architecture.

The ability of a population to adapt to changes in their living conditions, whether in nature or captivity, often depends on polymorphisms in multiple genes across the genome. In-depth studies of such polygenic adaptations are difficult in natural populations, but can be approached using the resources provided by artificial selection experiments. Here, we dissect the genetic mechanisms involved in long-term selection responses of the Virginia chicken lines, populations that after 40 generations of divergent selection for 56-day body weight display a 9-fold difference in the selected trait. In the F15 generation of an intercross between the divergent lines, 20 loci explained >60% of the additive genetic variance for the selected trait. We focused particularly on fine-mapping seven major QTL that replicated in this population and found that only two fine-mapped to single, bi-allelic loci; the other five contained linked loci, multiple alleles or were epistatic. This detailed dissection of the polygenic adaptations in the Virginia lines provides a deeper understanding of the range of different genome-wide mechanisms that have been involved in these long-term selection responses. The results illustrate that the genetic architecture of a highly polygenic trait can involve a broad range of genetic mechanisms, and that this can be the case even in a small population bred from founders with limited genetic diversity.

Genetic adaptation to levels of dietary selenium in recent human history.

As humans migrated around the world, they came to inhabit environments that differ widely in the soil levels of certain micronutrients, including selenium (Se). Coupled with cultural variation in dietary practices, these migrations have led to a wide range of Se intake levels in populations around the world. Both excess and deficiency of Se in the diet can have adverse health consequences in humans, with severe Se deficiency resulting in diseases of the bone and heart. Se is required by humans mainly due to its function in selenoproteins, which contain the amino acid selenocysteine as one of their constituent residues. To understand the evolution of the use of this micronutrient in humans, we surveyed the patterns of polymorphism in all selenoprotein genes and genes involved in their regulation in 50 human populations. We find that single nucleotide polymorphisms from populations in Asia, particularly in populations living in the extreme Se-deficient regions of China, have experienced concerted shifts in their allele frequencies. Such differentiation in allele frequencies across genes is not observed in other regions of the world and is not expected under neutral evolution, being better explained by the action of recent positive selection. Thus, recent changes in the use and regulation of Se may harbor the genetic adaptations that helped humans inhabit environments that do not provide adequate levels of Se in the diet.