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Population bottlenecks followed by re-expansions have been common throughout history of many populations. The response of alleles under selection to such demographic perturbations has been a subject of great interest in population genetics. On the basis of theoretical analysis and computer simulations, we suggest that this response qualitatively depends on dominance. The number of dominant or additive deleterious alleles per haploid genome is expected to be slightly increased following the bottleneck and re-expansion. In contrast, the number of completely or partially recessive alleles should be sharply reduced. Changes of population size expose differences between recessive and additive selection, potentially providing insight into the prevalence of dominance in natural populations. Specifically, we use a simple statistic, BR≡∑xipop1/∑xjpop2, where x i represents the derived allele frequency, to compare the number of mutations in different populations, and detail its functional dependence on the strength of selection and the intensity of the population bottleneck. We also provide empirical evidence showing that gene sets associated with autosomal recessive disease in humans may have a B R indicative of recessive selection. Together, these theoretical predictions and empirical observations show that complex demographic history may facilitate rather than impede inference of parameters of natural selection., Author Summary Dominance has played a central role in classical genetics since its inception. However, the effect of dominance introduces substantial technical complications into theoretical models describing dynamics of alleles in populations. As a result, dominance is often ignored in population genetic models. Statistical tests for selection built on these models do not discriminate between recessive and additive alleles. We show that historical changes in population size can provide a way to differentiate between recessive and additive selection. Our analysis compares two sub-populations with different demographic histories. History of our own species provides plenty of examples of sub-populations that went through population bottlenecks followed by re-expansions. We show that demographic differences, which generally complicate the analysis, can instead aid in the inference of features of natural selection.

There has been extensive debate over whether certain classes of genes are more likely than others to contain the causal variants responsible for phenotypic differences in complex traits between individuals. One hypothesis states that input/output genes positioned in signal transduction bottlenecks are more likely than other genes to contain causal natural variation. The IME1 gene resides at such a signaling bottleneck in the yeast sporulation pathway, suggesting that it may be more likely to contain causal variation than other genes in the sporulation pathway. Through crosses between natural isolates of yeast, we demonstrate that the specific causal nucleotides responsible for differences in sporulation efficiencies reside not only in IME1 but also in the genes that surround IME1 in the signaling pathway, including RME1, RSF1, RIM15, and RIM101. Our results support the hypothesis that genes at the critical decision making points in signaling cascades will be enriched for causal variants responsible for phenotypic differences., Author Summary Distinguishing the small number of genetic variants that impact phenotypes from the huge number of innocuous variants within an individual's genome is a difficult problem. Several hypotheses concerning the location of causal variants have been put forward based on the fact that genes are often organized into signaling cascades where the activation of a gene at the top of a pathway in turn activates large numbers of downstream genes. One hypothesis states that causal variations are more likely to reside in the genes at the top of these pathways because their effects are amplified by the signaling cascade. Here we provide support for this hypothesis by showing that causal genetic variants in yeast sporulation cluster around a gene at the top of the sporulation signaling cascade. Our result suggests a way to focus the search for causal genetic variants, including those that cause disease, on a smaller number of genes that are more likely to harbor important variations.

In mammals, observations of rapid shifts in mitochondrial DNA (mtDNA) variants between generations have led to the creation of the bottleneck theory for the transmission of mtDNA. The bottleneck could be attributed to a marked decline of mtDNA content in germ cells giving rise to the next generation, to a small effective number of mtDNA segregation units resulting from homoplasmic nucleoids rather than the single mtDNA molecule serving as the units of segregation, or to the selective transmission of a subgroup of the mtDNA population to the progeny. We have previously determined mtDNA copy number in single germ cells and shown that the bottleneck occurs without the reduction in germline mtDNA content. Recently one study suggested that the bottleneck is driven by a remarkable decline of mtDNA copies in early primordial germ cells (PGCs), while another study reported that the mtDNA genetic bottleneck results from replication of a subpopulation of the mtDNA genome during postnatal oocyte maturation and not during embryonic oogenesis, despite a detected a reduction in mtDNA content in early PGCs. To clarify these contradictory results, we examined the mtDNA copy number in PGCs isolated from transgenic mice expressing fluorescent proteins specifically in PGCs as in the aforementioned two other studies. We provide clear evidence to confirm that no remarkable reduction in mtDNA content occurs in PGCs and reinforce that the bottleneck is generated without reduction of mtDNA content in germ cells., Author Summary Mutations of mtDNA are responsible for many types of mitochondrial diseases in humans, including myopathy and neurological disorders. Females carrying a mixture of mutant and wild-type mtDNA variants transmit a variable amount of mutant mtDNA to each offspring. The proportion of mutated mtDNA inherited from the mother determines the onset and severity of diseases. Studies have suggested that the mtDNA genome is transmitted through a bottleneck, but the underlying mechanism remains controversial. By detecting mtDNA copy number in single cells, we previously showed that the bottleneck occurs without reduction of mtDNA content in germline cells. However, recently a study reported a marked decline of mtDNA copies in embryonic germ cells and attributed this reduction to the creation of the bottleneck. Yet another study concluded that the bottleneck occurs during postnatal oocyte maturation and not during embryonic oogenesis. To resolve these controversies, we examined mtDNA copies in embryonic germ cells identified using the same methodology as in the other two studies. We show solid evidence to confirm our previous findings. This confirmation is important because the understanding of mtDNA content in female germ cells will facilitate the development of therapeutic strategies preventing the transmission of mitochondrial diseases from mother to offspring.

Forward genetics screens with N-ethyl-N-nitrosourea (ENU) provide a powerful way to illuminate gene function and generate mouse models of human disease; however, the identification of causative mutations remains a limiting step. Current strategies depend on conventional mapping, so the propagation of affected mice requires non-lethal screens; accurate tracking of phenotypes through pedigrees is complex and uncertain; out-crossing can introduce unexpected modifiers; and Sanger sequencing of candidate genes is inefficient. Here we show how these problems can be efficiently overcome using whole-genome sequencing (WGS) to detect the ENU mutations and then identify regions that are identical by descent (IBD) in multiple affected mice. In this strategy, we use a modification of the Lander-Green algorithm to isolate causative recessive and dominant mutations, even at low coverage, on a pure strain background. Analysis of the IBD regions also allows us to calculate the ENU mutation rate (1.54 mutations per Mb) and to model future strategies for genetic screens in mice. The introduction of this approach will accelerate the discovery of causal variants, permit broader and more informative lethal screens to be used, reduce animal costs, and herald a new era for ENU mutagenesis., Author Summary Damaging mutations in single genes are an important source of information about the causes of disease, including more complex genetic disease; but these single gene disorders are typically rare in humans. An important strategy for identifying new disease mechanisms is to introduce multiple random mutations in mice and test the mice for biological differences; these mice act as models of human disease. However, discovering the disease-causing mutation is time-consuming and complex, requiring further generations of breeding. In this study we demonstrate a method that overcomes these problems by sequencing the entire genomes of multiple mice that have inherited a disease-causing mutation from a common ancestor. We use an algorithm that uses knowledge of all the mutations carried by the sequenced mice to identify the regions of the genome and mutations that are common to all the mice. Using this method we can rapidly link biological traits to genetic mutations. In contrast to current approaches, our strategy does not require large amounts of breeding, and it permits more accurate measurement of a wider range of traits; consequently its introduction will significantly reduce the number of mice required in the future, increase the number of traits that can be detected, and accelerate the discovery of new pathways and gene functions relevant to human diseases.

Transmission between hosts is a critical part of the viral lifecycle. Recent studies of viral transmission have used genome sequence data to evaluate the number of particles transmitted between hosts, and the role of selection as it operates during the transmission process. However, the interpretation of sequence data describing transmission events is a challenging task. We here present a novel and comprehensive framework for using short-read sequence data to understand viral transmission events, designed for influenza virus, but adaptable to other viral species. Our approach solves multiple shortcomings of previous methods for this purpose; for example, we consider transmission as an event involving whole viruses, rather than sets of independent alleles. We demonstrate how selection during transmission and noisy sequence data may each affect naive inferences of the population bottleneck, accounting for these in our framework so as to achieve a correct inference. We identify circumstances in which selection for increased viral transmission may or may not be identified from data. Applying our method to experimental data in which transmission occurs in the presence of strong selection, we show that our framework grants a more quantitative insight into transmission events than previous approaches, inferring the bottleneck in a manner that accounts for selection, both for within-host virulence, and for inherent viral transmissibility. Our work provides new opportunities for studying transmission processes in influenza, and by extension, in other infectious diseases., Author summary In order to spread, pathogens must not only be able to grow within an infected host, but also transmit to found new infections. Population genetics can exploit genome sequence data to provide a great deal of insight into transmission processes. For example, the number of particles which found a new infection determine the extent to which genetic diversity is passed from host to host. The identification of genetic variants which increase the propensity of a pathogen to transmit from host to host is a valuable step in understanding how an infection might spread. Here we set out a new population genetic framework for understanding transmission events from genome sequence data collected before and after transmission. Our approach corrects for the shortcomings of existing methods for this purpose, setting out a new baseline for the statistical analysis of transmission events. We demonstrate the ability of our method to draw novel quantitative insights by application to data from simulated and real transmission events.

Populations change in size over time due to factors such as population growth, migration, bottleneck events, natural disasters, and disease. The historical effective size of a population affects the power and resolution of genetic association studies. For admixed populations, it is not only the overall effective population size that is of interest, but also the effective sizes of the component ancestral populations. We use identity by descent and local ancestry inferred from genome-wide genetic data to estimate overall and ancestry-specific effective population size during the past hundred generations for nine admixed American populations from the Hispanic Community Health Study/Study of Latinos, and for African-American and European-American populations from two US cities. In these populations, the estimated pre-admixture effective sizes of the ancestral populations vary by sampled population, suggesting that the ancestors of different sampled populations were drawn from different sub-populations. In addition, we estimate that overall effective population sizes dropped substantially in the generations immediately after the commencement of European and African immigration, reaching a minimum around 12 generations ago, but rebounded within a small number of generations afterwards. Of the populations that we considered, the population of individuals originating from Puerto Rico has the smallest bottleneck size of one thousand, while the Pittsburgh African-American population has the largest bottleneck size of two hundred thousand., Author summary Using genome-wide genetic data on several hundred individuals sampled from a population, we can estimate the current effective size of the population and the changes in effective size that have occurred over the past hundred generations. Many populations in the Americas are admixed, having ancestry from Europe, Africa, and the Americas. In such cases, one can learn not only about the effective population size history of the admixed population since admixture, but also about the effective population size histories of the contributing ancestral populations. In this paper we develop methodology for estimating past effective population size and analyze data from Hispanic, African-American, and European-American populations resident in the United States. We observe differences between populations in their historical effective sizes. These differences are useful for understanding differences in disease incidence between populations and for identifying populations that will maximize power in genetic association studies.

Evolutionary responses to environmental change depend on the time available for adaptation before environmental degradation leads to extinction. Explicit tests of this relationship are limited to microbes where adaptation usually depends on the sequential fixation of de novo mutations, excluding standing variation for genotype-by-environment fitness interactions that should be key for most natural species. For natural species evolving from standing genetic variation, adaptation at slower rates of environmental change may be impeded since the best genotypes at the most extreme environments can be lost during evolution due to genetic drift or founder effects. To address this hypothesis, we perform experimental evolution with self-fertilizing populations of the nematode Caenorhabditis elegans and develop an inference model to describe natural selection on extant genotypes under environmental change. Under a sudden environmental change, we find that selection rapidly increases the frequency of genotypes with high fitness in the most extreme environment. In contrast, under a gradual environmental change selection first favors genotypes that are worse at the most extreme environment. We demonstrate with a second set of evolution experiments that, as a consequence of slower environmental change and thus longer periods to reach the most extreme environments, genetic drift and founder effects can lead to the loss of the most beneficial genotypes. We further find that maintenance of standing genetic variation can retard the fixation of the best genotypes in the most extreme environment because of interference between them. Taken together, these results show that slower environmental change can hamper adaptation from standing genetic variation and they support theoretical models indicating that standing variation for genotype-by-environment fitness interactions critically alters the pace and outcome of adaptation under environmental change., Author summary Adaptation under environmental change is expected to depend on the time available for the sequential fixation of mutations, but also on standing variation in genotype-by-environment fitness interactions. In the later circumstances, some genotypes might be initially favored but then disfavored and overtaken by other genotypes that are better at more extreme environments if they were not lost by genetic drift or founder effects in the meantime. We addressed this idea with experimental evolution in Caenorhabditis elegans populations with standing variation for genotype-by-environment fitness interactions and by developing a model to describe natural selection on extant genotypes during experimental evolution. We find that under slower environmental change, the genotypes that are initially selected are not the best at the most extreme environments, and as a consequence, that these best genotypes can be lost due to genetic drift and founder effects. We further find that the longer polymorphism is maintained the more likely that selective interference will reduce the best genotypes to low frequencies and increase the chances for their loss through genetic drift. We conclude that under slower environmental change adaptation will be deterred if populations can only rely on standing genetic variation.

Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey), PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles., Author Summary Molecular data sampled from extant individuals contains considerable information about their demographic history. In particular, one classical question in population genetics is to reconstruct past population size changes from such data. Relating these changes to various climatic, geological or anthropogenic events allows characterizing the main factors driving genetic diversity and can have major outcomes for conservation. Until recently, mostly very simple histories, including one or two population size changes, could be estimated from genetic data. This has changed with the sequencing of entire genomes in many species, and several methods allow now inferring complex histories consisting of several tens of population size changes. However, analyzing entire genomes, while accounting for recombination, remains a statistical and numerical challenge. These methods, therefore, can only be applied to small samples with a few diploid genomes. We overcome this limitation by using an approximate estimation approach, where observed genomes are summarized using a small number of statistics related to allele frequencies and linkage disequilibrium. In contrast to previous approaches, we show that our method allows us to reconstruct also the most recent part (the last 100 generations) of the population size history. As an illustration, we apply it to large samples of whole-genome sequences in four cattle breeds.

Whole-exome or gene targeted resequencing in hundreds to thousands of individuals has shown that the majority of genetic variants are at low frequency in human populations. Rare variants are enriched for functional mutations and are expected to explain an important fraction of the genetic etiology of human disease, therefore having a potential medical interest. In this work, we analyze the whole-exome sequences of French-Canadian individuals, a founder population with a unique demographic history that includes an original population bottleneck less than 20 generations ago, followed by a demographic explosion, and the whole exomes of French individuals sampled from France. We show that in less than 20 generations of genetic isolation from the French population, the genetic pool of French-Canadians shows reduced levels of diversity, higher homozygosity, and an excess of rare variants with low variant sharing with Europeans. Furthermore, the French-Canadian population contains a larger proportion of putatively damaging functional variants, which could partially explain the increased incidence of genetic disease in the province. Our results highlight the impact of population demography on genetic fitness and the contribution of rare variants to the human genetic variation landscape, emphasizing the need for deep cataloguing of genetic variants by resequencing worldwide human populations in order to truly assess disease risk., Author Summary Recent resequencing of the whole genome or the coding part of the genome (the exome) in thousands of individuals has described a large excess of low frequency variants in humans, probably arising as a consequence of recent rapid growth in human population sizes. Most rare variants are private to specific populations and are enriched for functional mutations, thus potentially having some medical relevance. In this study, we analyze whole-exome sequences from over a hundred individuals from the French-Canadian population, which was founded less than 400 years ago by about 8,500 French settlers who colonized the province between the 17th and 18th centuries. We show that in a remarkably short period of time this population has accumulated substantial differences, including an excess of rare, functional and potentially damaging variants, when compared to the original European population. Our results show the effects of population history on genetic variation that may have an impact on genetic fitness and disease, and have implications in the design of genetic studies, highlighting the importance of extending deep resequencing to worldwide human populations.

Inbreeding has long been recognized as a primary cause of fitness reduction in both wild and domesticated populations. Consanguineous matings cause inheritance of haplotypes that are identical by descent (IBD) and result in homozygous stretches along the genome of the offspring. Size and position of regions of homozygosity (ROHs) are expected to correlate with genomic features such as GC content and recombination rate, but also direction of selection. Thus, ROHs should be non-randomly distributed across the genome. Therefore, demographic history may not fully predict the effects of inbreeding. The porcine genome has a relatively heterogeneous distribution of recombination rate, making Sus scrofa an excellent model to study the influence of both recombination landscape and demography on genomic variation. This study utilizes next-generation sequencing data for the analysis of genomic ROH patterns, using a comparative sliding window approach. We present an in-depth study of genomic variation based on three different parameters: nucleotide diversity outside ROHs, the number of ROHs in the genome, and the average ROH size. We identified an abundance of ROHs in all genomes of multiple pigs from commercial breeds and wild populations from Eurasia. Size and number of ROHs are in agreement with known demography of the populations, with population bottlenecks highly increasing ROH occurrence. Nucleotide diversity outside ROHs is high in populations derived from a large ancient population, regardless of current population size. In addition, we show an unequal genomic ROH distribution, with strong correlations of ROH size and abundance with recombination rate and GC content. Global gene content does not correlate with ROH frequency, but some ROH hotspots do contain positive selected genes in commercial lines and wild populations. This study highlights the importance of the influence of demography and recombination on homozygosity in the genome to understand the effects of inbreeding., Author Summary Small populations have an increased risk of inbreeding depression due to a higher expression of deleterious alleles. This can have major consequences for the viability of these populations. In domesticated species like the pig that are artificially selected in breeding populations, but also in wild populations that experience habitat decline, maintaining genetic diversity is essential. Recent advances in sequence technology enabled us to identify patterns of nucleotide variation in individual genomes. We screened the full genome of wild boars and commercial pigs from Eurasia for regions of homozygosity. We found these regions of homozygosity were caused by the demographic history and effective population size of the pigs. European wild boars are least variable, but also European breeds contain large homozygous stretches in their genome. Moreover, the likelihood of a region becoming depleted depends on its position in the genome, because variation has a high correlation with recombination rate. The telomeric regions are much more variable, and the central region of chromosomes has a higher chance of containing long regions of homozygosity. These findings increase knowledge on the fine-scaled architecture of genomic variation, and they are particularly important for population genetic management.

Genome-wide scans of genetic variation can potentially provide detailed information on how modern humans colonized the world but require new methods of analysis. We introduce a statistical approach that uses Single Nucleotide Polymorphism (SNP) data to identify sharing of chromosomal segments between populations and uses the pattern of sharing to reconstruct a detailed colonization scenario. We apply our model to the SNP data for the 53 populations of the Human Genome Diversity Project described in Conrad et al. (Nature Genetics 38,1251-60, 2006). Our results are consistent with the consensus view of a single “Out-of-Africa” bottleneck and serial dilution of diversity during global colonization, including a prominent East Asian bottleneck. They also suggest novel details including: (1) the most northerly East Asian population in the sample (Yakut) has received a significant genetic contribution from the ancestors of the most northerly European one (Orcadian). (2) Native South Americans have received ancestry from a source closely related to modern North-East Asians (Mongolians and Oroquen) that is distinct from the sources for native North Americans, implying multiple waves of migration into the Americas. A detailed depiction of the peopling of the world is available in animated form., Author Summary Humans like to tell stories. Amongst the most captivating is the story of the global spread of modern humans from their original homeland in Africa. Traditionally this has been the preserve of anthropologists, but geneticists are starting to make an important contribution. However, genetic evidence is typically analyzed in the context of anthropological preconceptions. For genetics to provide an accurate and detailed history without reference to anthropology, methods are required that translate DNA sequence data into histories. We introduce a statistical method that has three virtues. First, it is based on a copying model that incorporates the block-by-block inheritance of DNA from one generation to the next. This allows it to capture the rich information provided by patterns of DNA sharing across the whole genome. Second, its parameter space includes an enormous number of possible colonization scenarios, meaning that inferences are correspondingly rich in detail. Third, the inferred colonization scenario is determined algorithmically. We have applied this method to data from 53 human populations and find that while the current consensus is broadly supported, some populations have surprising histories. This scenario can be viewed as a movie, making it transparent where statistical analysis ends and where interpretation begins.

The domestication of the dog from its wolf ancestors is perhaps the most complex genetic experiment in history, and certainly the most extensive. Beginning with the wolf, man has created dog breeds that are hunters or herders, big or small, lean or squat, and independent or loyal. Most breeds were established in the 1800s by dog fanciers, using a small number of founders that featured traits of particular interest. Popular sire effects, population bottlenecks, and strict breeding programs designed to expand populations with desirable traits led to the development of what are now closed breeding populations, with limited phenotypic and genetic heterogeneity, but which are ideal for genetic dissection of complex traits. In this review, we first discuss the advances in mapping and sequencing that accelerated the field in recent years. We then highlight findings of interest related to disease gene mapping and population structure. Finally, we summarize novel results on the genetics of morphologic variation.

Ecological divergence in a species provides a valuable opportunity to study the early stages of speciation. We focused on Metrosideros polymorpha, a unique example of the incipient radiation of woody species, to examine how an ecological divergence continues in the face of gene flow. We analyzed the whole genomes of 70 plants collected throughout the island of Hawaii, which is the youngest island with the highest altitude in the archipelago and encompasses a wide range of environments. The continuous M. polymorpha forest stands on the island of Hawaii were differentiated into three genetic clusters, each of which grows in a distinctive environment and includes substantial genetic and phenotypic diversity. The three genetic clusters showed signatures of selection in genomic regions encompassing genes relevant to environmental adaptations, including genes associated with light utilization, oxidative stress, and leaf senescence, which are likely associated with the ecological differentiation of the species. Our demographic modeling suggested that the glaberrima cluster in wet environments maintained a relatively large population size and two clusters split: polymorpha in the subalpine zone and incana in dry and hot conditions. This ecological divergence possibly began before the species colonized the island of Hawaii. Interestingly, the three clusters recovered genetic connectivity coincidentally with a recent population bottleneck, in line with the weak reproductive isolation observed in the species. This study highlights that the degree of genetic differentiation between ecologically-diverged populations can vary depending on the strength of natural selection in the very early phases of speciation., Author summary Knowledge about how genetic barriers are formed between populations in distinct environments is valuable to understand the processes of speciation and conserve biodiversity. Metrosideros polymorpha, an endemic woody species in the Hawaiian Islands, is a good system to study developing genetic barriers in a species, because it colonized the diverse environments and diversified the morphology for a relatively short period of time. We analyzed the genomes of 70 M. polymorpha plants from a broad range of environments on the island of Hawaii to infer the current and past genetic barriers among them. Currently, M. polymorpha plants growing in different environments have substantially different genomes, especially at the genomic regions with genes putatively controlling physiology to fit in distinct environment. However, in its history, they had hybridized with one another, possibly because plants formerly growing in different environments came into close contact due to the climate changes. It is suggested that genetic barriers can easily strengthen or weaken depending on environments splitting the ecology of a species before reproductive isolation becomes complete.

microRNAs (miRNAs) are increasingly recognized as important regulators of many biological processes in mosquitoes, vectors of numerous devastating infectious diseases. Identification of bona fide targets remains the bottleneck for functional studies of miRNAs. In this study, we used CLEAR-CLIP assays to systematically analyze miRNA-mRNA interactions in adult female Anopheles gambiae mosquitoes. Thousands of miRNA-target pairs were captured after direct ligation of the miRNA and its cognate target transcript in endogenous Argonaute–miRNA–mRNA complexes. Using two interactions detected in this manner, miR-309-SIX4 and let-7-kr-h1, we demonstrated the reliability of this experimental approach in identifying in vivo gene regulation by miRNAs. The miRNA-mRNA interaction dataset provided an invaluable opportunity to decipher targeting rules of mosquito miRNAs. Enriched motifs in the diverse targets of each miRNA indicated that the majority of mosquito miRNAs rely on seed-based canonical target recognition, while noncanonical miRNA binding sites are widespread and often contain motifs complementary to the central or 3’ ends of miRNAs. The time-lapse study of miRNA-target interactomes in adult female mosquitoes revealed dynamic miRNA regulation of gene expression in response to varying nutritional sources and physiological demands. Interestingly, some miRNAs exhibited flexibility to use distinct sequences at different stages for target recognition. Furthermore, many miRNA-mRNA interactions displayed stage-specific patterns, especially for those genes involved in metabolism, suggesting that miRNAs play critical roles in precise control of gene expression to cope with enormous physiological demands associated with egg production. The global mapping of miRNA-target interactions contributes to our understanding of miRNA targeting specificity in non-model organisms. It also provides a roadmap for additional studies focused on regulatory functions of miRNAs in Anopheles gambiae., Author summary Metazoan miRNAs typically bind to partially complementary sites in their target mRNAs. The interactions between miRNAs and target RNAs are generally stage-specific and context-dependent. Thus, identification of authentic miRNA targets remains a big challenge. Target identification is even more difficult in mosquitoes where miRNA-mRNA pairing rules are poorly characterized. Using an experimental approach, this study captures thousands of endogenous miRNA-target interactions in female mosquitoes at several critical stages during adult reproduction. Analyses of the target sequences reveal how individual miRNAs accomplish their target recognition in mosquitoes. Interestingly, many mosquito miRNAs exhibit flexibility to use distinct sequences at different stages to pair with their targets, greatly altering target selectivity and expanding target repertoire of miRNAs. Drastic changes in mRNA abundance have been previously reported when adult female mosquitoes attend to varying nutritional sources and physiological demands. The temporal patterns of miRNA-target interactions obtained in this study provide new insights into the roles of miRNAs in tightly controlled gene expression associated with blood-feeding and mosquito oogenesis.

The lack of predictive preclinical models is a fundamental barrier to translating knowledge about the molecular pathogenesis of cancer into improved therapies. Insertional mutagenesis (IM) in mice is a robust strategy for generating malignancies that recapitulate the extensive inter- and intra-tumoral genetic heterogeneity found in advanced human cancers. While the central role of "driver" viral insertions in IM models that aberrantly increase the expression of proto-oncogenes or disrupt tumor suppressors has been appreciated for many years, the contributions of cooperating somatic mutations and large chromosomal alterations to tumorigenesis are largely unknown. Integrated genomic studies of T lineage acute lymphoblastic leukemias (T-ALLs) generated by IM in wild-type (WT) and Kras mutant mice reveal frequent point mutations and other recurrent non-insertional genetic alterations that also occur in human T-ALL. These somatic mutations are sensitive and specific markers for defining clonal dynamics and identifying candidate resistance mechanisms in leukemias that relapse after an initial therapeutic response. Primary cancers initiated by IM and resistant clones that emerge during in vivo treatment close key gaps in existing preclinical models, and are robust platforms for investigating the efficacy of new therapies and for elucidating how drug exposure shapes tumor evolution and patterns of resistance., Author summary A lack of predictive cancer models is a major bottleneck for prioritizing new anti-cancer drugs for clinical trials. We comprehensively profiled a panel of primary mouse T lineage leukemias initiated by insertional mutagenesis and found remarkable similarities with human T-ALL in regard to overall mutational burden, the occurrence of specific somatic mutations and large chromosomal alterations, and concordant gene expression signatures. We observed frequent duplication of the Kras oncogene with loss of the normal allele, which has potential therapeutic implications that merit further investigation in human leukemia and in other preclinical models. Mutations identified in mouse leukemias that relapsed after in vivo treatment with signal transduction inhibitors were also observed in relapsed human T-ALL, indicating that this model system can be utilized to investigate strategies for overcoming intrinsic and acquired drug resistance. Finally, preclinical models similar to the one described here that are characterized by a normal endogenous tumor microenvironment and intact immune system will become increasingly important for testing immunotherapy approaches for human cancer.

Sex-biased demographic events (“sex-bias”) involve unequal numbers of females and males. These events are typically inferred from the relative amount of X-chromosomal to autosomal genetic variation and have led to conflicting conclusions about human demographic history. Though population size changes alter the relative amount of X-chromosomal to autosomal genetic diversity even in the absence of sex-bias, this has generally not been accounted for in sex-bias estimators to date. Here, we present a novel method to identify sex-bias from genetic sequence data that models population size changes and estimates the female fraction of the effective population size during each time epoch. Compared to recent sex-bias inference methods, our approach can detect sex-bias that changes on a single population branch without requiring data from an outgroup or knowledge of divergence events. When applied to simulated data, conventional sex-bias estimators are biased by population size changes, especially recent growth or bottlenecks, while our estimator is unbiased. We next apply our method to high-coverage exome data from the 1000 Genomes Project and estimate a male bias in Yorubans (47% female) and Europeans (44%), possibly due to stronger background selection on the X chromosome than on the autosomes. Finally, we apply our method to the 1000 Genomes Project Phase 3 high-coverage Complete Genomics whole-genome data and estimate a female bias in Yorubans (63% female), Europeans (84%), Punjabis (82%), as well as Peruvians (56%), and a male bias in the Southern Han Chinese (45%). Our method additionally identifies a male-biased migration out of Africa based on data from Europeans (20% female). Our results demonstrate that modeling population size change is necessary to estimate sex-bias parameters accurately. Our approach gives insight into signatures of sex-bias in sexual species, and the demographic models it produces can serve as more accurate null models for tests of selection., Author summary Sex-biased demographic events involve unequal numbers of females and males, and is referred to as “sex-bias”. In humans, short-range migrations (e.g., due to marriage practices) are known to be sex-biased, and some long-range migrations, such as the one out of Africa, are hypothesized to be sex-biased. The recent availability of large-scale genomic sequencing data provides a unique opportunity to study sex-bias in human populations. However, existing sex-bias methods do not account for population size changes, like expansions and bottlenecks, or can only estimate a single sex-bias parameter on a population branch, which can lead to incorrect conclusions. We developed a sex-bias method which explicitly models population size changes, and we show that it outperforms competing methods on simulated data. When applied to human genetic data, our method identifies an overall female sex-bias in globally-distributed populations and a male-biased bottleneck in Europeans. Our method can also be used to assess sex-bias in other sexual species.

Cellulosic plant biomass is a promising sustainable resource for generating alternative biofuels and biochemicals with microbial factories. But a remaining bottleneck is engineering microbes that are tolerant of toxins generated during biomass processing, because mechanisms of toxin defense are only beginning to emerge. Here, we exploited natural diversity in 165 Saccharomyces cerevisiae strains isolated from diverse geographical and ecological niches, to identify mechanisms of hydrolysate-toxin tolerance. We performed genome-wide association (GWA) analysis to identify genetic variants underlying toxin tolerance, and gene knockouts and allele-swap experiments to validate the involvement of implicated genes. In the process of this work, we uncovered a surprising difference in genetic architecture depending on strain background: in all but one case, knockout of implicated genes had a significant effect on toxin tolerance in one strain, but no significant effect in another strain. In fact, whether or not the gene was involved in tolerance in each strain background had a bigger contribution to strain-specific variation than allelic differences. Our results suggest a major difference in the underlying network of causal genes in different strains, suggesting that mechanisms of hydrolysate tolerance are very dependent on the genetic background. These results could have significant implications for interpreting GWA results and raise important considerations for engineering strategies for industrial strain improvement., Author summary Understanding the genetic architecture of complex traits is important for elucidating the genotype-phenotype relationship. Many studies have sought genetic variants that underlie phenotypic variation across individuals, both to implicate causal variants and to inform on architecture. Here we used genome-wide association analysis to identify genes and processes involved in tolerance of toxins found in plant-biomass hydrolysate, an important substrate for sustainable biofuel production. We found substantial variation in whether or not individual genes were important for tolerance across genetic backgrounds. Whether or not a gene was important in a given strain background explained more variation than the alleleic differences in the gene. These results suggest substantial variation in gene contributions, and perhaps underlying mechanisms, of toxin tolerance.

The Ashkenazi Jewish (AJ) population is important in genetics due to its high rate of Mendelian disorders. AJ appeared in Europe in the 10th century, and their ancestry is thought to comprise European (EU) and Middle-Eastern (ME) components. However, both the time and place of admixture are subject to debate. Here, we attempt to characterize the AJ admixture history using a careful application of new and existing methods on a large AJ sample. Our main approach was based on local ancestry inference, in which we first classified each AJ genomic segment as EU or ME, and then compared allele frequencies along the EU segments to those of different EU populations. The contribution of each EU source was also estimated using GLOBETROTTER and haplotype sharing. The time of admixture was inferred based on multiple statistics, including ME segment lengths, the total EU ancestry per chromosome, and the correlation of ancestries along the chromosome. The major source of EU ancestry in AJ was found to be Southern Europe (≈60–80% of EU ancestry), with the rest being likely Eastern European. The inferred admixture time was ≈30 generations ago, but multiple lines of evidence suggest that it represents an average over two or more events, pre- and post-dating the founder event experienced by AJ in late medieval times. The time of the pre-bottleneck admixture event, which was likely Southern European, was estimated to ≈25–50 generations ago., Author summary The Ashkenazi Jewish population has resided in Europe for much of its 1000-year existence. However, its ethnic and geographic origins are controversial, due to the scarcity of reliable historical records. Previous genetic studies have found links to Middle-Eastern and European ancestries, but the admixture history has not been studied in detail yet, partly due to technical difficulties in disentangling signals from multiple admixture events. Here, we present an in-depth analysis of the sources of European gene flow and the time of admixture events by using multiple new and existing methods and extensive simulations. Our results suggest a model of at least two events of European admixture. One event slightly pre-dated a late medieval founder event and was likely from a Southern European source. Another event post-dated the founder event and likely occurred in Eastern Europe. These results, as well as the methods introduced, will be highly valuable for geneticists and other researchers interested in Ashkenazi Jewish origins.

The Ari peoples of Ethiopia are comprised of different occupational groups that can be distinguished genetically, with Ari Cultivators and the socially marginalised Ari Blacksmiths recently shown to have a similar level of genetic differentiation between them (F ST ≈ 0.023 − 0.04) as that observed among multiple ethnic groups sampled throughout Ethiopia. Anthropologists have proposed two competing theories to explain the origins of the Ari Blacksmiths as (i) remnants of a population that inhabited Ethiopia prior to the arrival of agriculturists (e.g. Cultivators), or (ii) relatively recently related to the Cultivators but presently marginalized in the community due to their trade. Two recent studies by different groups analysed genome-wide DNA from samples of Ari Blacksmiths and Cultivators and suggested that genetic patterns between the two groups were more consistent with model (i) and subsequent assimilation of the indigenous peoples into the expanding agriculturalist community. We analysed the same samples using approaches designed to attenuate signals of genetic differentiation that are attributable to allelic drift within a population. By doing so, we provide evidence that the genetic differences between Ari Blacksmiths and Cultivators can be entirely explained by bottleneck effects consistent with hypothesis (ii). This finding serves as both a cautionary tale about interpreting results from unsupervised clustering algorithms, and suggests that social constructions are contributing directly to genetic differentiation over a relatively short time period among previously genetically similar groups., Author Summary While it is widely recognized that DNA patterns vary across world-wide human populations, the primary features that drive these differences are less well understood. As an example, the Ari peoples of Ethiopia are presently socially divided according to occupation, with Ari Blacksmiths marginalised relative to Ari Cultivators. Two competing theories proposed by anthropologists to explain the existence of these occupational groupings suggest very different histories: (i) the Cultivators reflect migrants who moved into the region occupied by ancestors of the Blacksmiths perhaps many thousands of years ago, versus (ii) the Blacksmiths and Cultivators comprised the same ancestral group before the former was marginalised due solely to their trade. Recent genetic studies showed that Blacksmiths and Cultivators are distinguishable by their DNA, and suggested that overall DNA patterns among the two groups were consistent with (i). However, we demonstrate here that interpreting the results of currently popular algorithms that compare DNA is not always straight-forward. Instead we use a variety of analyses to show that (ii) seems a more likely explanation, perhaps illustrating how social marginalisation can lead to groups becoming genetically distinguishable over a relatively short time period.

Gene expression differences between divergent lineages caused by modification of cis regulatory elements are thought to be important in evolution. We assayed genome-wide cis and trans regulatory differences between maize and its wild progenitor, teosinte, using deep RNA sequencing in F1 hybrid and parent inbred lines for three tissue types (ear, leaf and stem). Pervasive regulatory variation was observed with approximately 70% of ∼17,000 genes showing evidence of regulatory divergence between maize and teosinte. However, many fewer genes (1,079 genes) show consistent cis differences with all sampled maize and teosinte lines. For ∼70% of these 1,079 genes, the cis differences are specific to a single tissue. The number of genes with cis regulatory differences is greatest for ear tissue, which underwent a drastic transformation in form during domestication. As expected from the domestication bottleneck, maize possesses less cis regulatory variation than teosinte with this deficit greatest for genes showing maize-teosinte cis regulatory divergence, suggesting selection on cis regulatory differences during domestication. Consistent with selection on cis regulatory elements, genes with cis effects correlated strongly with genes under positive selection during maize domestication and improvement, while genes with trans regulatory effects did not. We observed a directional bias such that genes with cis differences showed higher expression of the maize allele more often than the teosinte allele, suggesting domestication favored up-regulation of gene expression. Finally, this work documents the cis and trans regulatory changes between maize and teosinte in over 17,000 genes for three tissues., Author Summary Modification of cis regulatory elements to produce differences in gene expression level, localization, and timing is an important mechanism by which organisms evolve divergent adaptations. To examine gene regulatory change during the domestication of maize from its wild progenitor, teosinte, we assessed allele-specific expression in a collection of maize and teosinte inbreds and their F1 hybrids using three tissues from different developmental stages. Our use of F1 hybrids represents the first study in a domesticated crop and wild progenitor that dissects cis and trans regulatory effects to examine characteristics of genes under various cis and trans regulatory regimes. We find evidence for consistent cis regulatory divergence that differentiates maize from teosinte in approximately 4% of genes. These genes are significantly correlated with genes under selection during domestication and crop improvement, suggesting an important role for cis regulatory elements in maize evolution. This work provides valuable insight into the evolution of gene regulatory elements during the domestication of an important crop plant.

Since the unexpected discovery that mitochondria contain their own distinct DNA molecules, studies of the mitochondrial DNA (mtDNA) have yielded many surprises. In animals, transmission of the mtDNA genome is explicitly non-Mendelian, with a very high number of genome copies being inherited from the mother after a drastic bottleneck. Recent work has begun to uncover the molecular details of this unusual mode of transmission. Many surprising variations in animal mitochondrial biology are known; however, a series of recent studies have identified a core of evolutionarily conserved mechanisms relating to mtDNA inheritance, e.g., mtDNA bottlenecks during germ cell development, selection against specific mtDNA mutation types during maternal transmission, and targeted destruction of sperm mitochondria. In this review, we outline recent literature on the transmission of mtDNA in animals and highlight the implications for human health and ageing.

Human ageing has been predicted to be caused by the accumulation of molecular damage in cells and tissues. Somatic mitochondrial DNA (mtDNA) mutations have been documented in a number of ageing tissues and have been shown to be associated with cellular mitochondrial dysfunction. It is unknown whether there are selective constraints, which have been shown to occur in the germline, on the occurrence and expansion of these mtDNA mutations within individual somatic cells. Here we compared the pattern and spectrum of mutations observed in ageing human colon to those observed in the general population (germline variants) and those associated with primary mtDNA disease. The pathogenicity of the protein encoding mutations was predicted using a computational programme, MutPred, and the scores obtained for the three groups compared. We show that the mutations associated with ageing are randomly distributed throughout the genome, are more frequently non-synonymous or frameshift mutations than the general population, and are significantly more pathogenic than population variants. Mutations associated with primary mtDNA disease were significantly more pathogenic than ageing or population mutations. These data provide little evidence for any selective constraints on the occurrence and expansion of mtDNA mutations in somatic cells of the human colon during human ageing in contrast to germline mutations seen in the general population., Author Summary Mitochondrial DNA encodes essential components of the mitochondrial respiratory chain and is strictly maternally inherited, making it vulnerable to the accumulation of deleterious mutations. To avoid this, mtDNA is subjected to a bottleneck phenomenon whereby only a small number of mtDNA molecules are passed on to the oocyte precursor. These are then amplified to the required number of mtDNA molecules in the mature oocyte, meaning that any mutations may be either lost or rapidly fixed. Purifying selection is thought to be an important protective mechanism against pathogenic mtDNA mutations in the germline, as this is essential for mtDNA stability. It is unknown whether there are any such protective mechanisms in the somatic tissues. To investigate this we have compared the spectrum of mutations present in ageing human colonocytes with those population variants passed through the maternal germline and mtDNA mutations responsible for primary mtDNA disease. We show that pathogenic mtDNA mutations are present at a significantly higher frequency in the somatic cells of the human colon in contrast to variants that have passed though the germline, showing little evidence for purifying selection in the somatic tissues studied here, but strong evidence of this selective mechanism in the germline.

Populations of human cytomegalovirus (HCMV), a large DNA virus, are highly polymorphic in patient samples, which may allow for rapid evolution within human hosts. To understand HCMV evolution, longitudinally sampled genomic populations from the urine and plasma of 5 infants with symptomatic congenital HCMV infection were analyzed. Temporal and compartmental variability of viral populations were quantified using high throughput sequencing and population genetics approaches. HCMV populations were generally stable over time, with ∼88% of SNPs displaying similar frequencies. However, samples collected from plasma and urine of the same patient at the same time were highly differentiated with approximately 1700 consensus sequence SNPs (1.2% of the genome) identified between compartments. This inter-compartment differentiation was comparable to the differentiation observed in unrelated hosts. Models of demography (i.e., changes in population size and structure) and positive selection were evaluated to explain the observed patterns of variation. Evidence for strong bottlenecks (>90% reduction in viral population size) was consistent among all patients. From the timing of the bottlenecks, we conclude that fetal infection occurred between 13–18 weeks gestational age in patients analyzed, while colonization of the urine compartment followed roughly 2 months later. The timing of these bottlenecks is consistent with the clinical histories of congenital HCMV infections. We next inferred that positive selection plays a small but measurable role in viral evolution within a single compartment. However, positive selection appears to be a strong and pervasive driver of evolution associated with compartmentalization, affecting ≥34 of the 167 open reading frames (∼20%) of the genome. This work offers the most detailed map of HCMV in vivo evolution to date and provides evidence that viral populations can be stable or rapidly differentiate, depending on host environment. The application of population genetic methods to these data provides clinically useful information, such as the timing of infection and compartment colonization., Author Summary The large, dsDNA virus Human cytomegalovirus (HCMV) is the most genetically complex viral pathogen of humans. HCMV populations are highly variable, which may allow the virus to evolve in human hosts on short timescales. We tested this hypothesis by longitudinally sampling HCMV populations from the urine and/or plasma of congenitally infected infants. We found that HCMV is generally stable within a compartment, but rapidly evolves when crossing host compartments. In fact, HCMV sampled from two compartments of the same host is as different as HCMV collected from unrelated hosts. We used mathematical modeling and population genetic analysis to show that both a bottleneck (i.e., a reduction in population size) associated with compartment colonization as well as positive selection are necessary to explain the observed differences between compartments. We also conclude from these data that fetal infection in these patients occurred between 13–18 weeks gestational age, consistent with the timing of symptomatic congenital HCMV infections. This study is the most detailed investigation of DNA virus evolution in human hosts to date, provides a framework for the study of other viral infections using similar techniques, and will aid in the development of new antiviral therapies and vaccines.

The strengths of association mapping lie in its resolution and allelic richness, but spurious associations arising from historical relationships and selection patterns need to be accounted for in statistical analyses. Here we reanalyze one of the first generation structured association mapping studies of the Dwarf8 (d8) locus with flowering time in maize using the full range of new mapping populations, statistical approaches, and haplotype maps. Because this trait was highly correlated with population structure, we found that basic structured association methods overestimate phenotypic effects in the region, while mixed model approaches perform substantially better. Combined with analysis of the maize nested association mapping population (a multi-family crossing design), it is concluded that most, if not all, of the QTL effects at the general location of the d8 locus are from rare extended haplotypes that include other linked QTLs and that d8 is unlikely to be involved in controlling flowering time in maize. Previous independent studies have shown evidence for selection at the d8 locus. Based on the evidence of population bottleneck, selection patterns, and haplotype structure observed in the region, we suggest that multiple traits may be strongly correlated with population structure and that selection on these traits has influenced segregation patterns in the region. Overall, this study provides insight into how modern association and linkage mapping, combined with haplotype analysis, can produce results that are more robust., Author Summary Eleven years ago, association mapping was a cutting-edge tool used to identify regions of a genome associated with phenotypic variation. One of the first association studies performed in plants was reported in Thornsberry, et al. (2001). Since then, researchers continued to develop new and improved genotyping, phenotyping, and statistical methods to examine the relationship between genotype and phenotype. Reanalysis of the old data for the d8 locus and flowering time, as well as new and improved data sets, gives us a unique opportunity to examine the strengths and weaknesses of association studies. These new analyses reveal that the results reported in 2001 significantly overestimated the association between genotype and phenotype, in particular the estimated effect size. The key issues with the Thornsberry et al. (2001) study were lack of control for population structure and relatedness between individuals, as well as a potential confounding between the phenotype and the population structure examined. The new analysis demonstrates a marginal association between d8 and flowering time, and a minimal effect (if any).

Recent reports of strong selection of mitochondrial DNA (mtDNA) during transmission in animal models of mtDNA disease, and of nuclear transfer in both animal models and humans, have important scientific implications. These are directly applicable to the genetic management of mtDNA disease. The risk that a mitochondrial disorder will be transmitted is difficult to estimate due to heteroplasmy - the existence of normal and mutant mtDNA in the same individual, tissue, or cell. In addition, the mtDNA bottleneck during oogenesis frequently results in dramatic and unpredictable intergenerational fluctuations in the proportions of mutant and wild-type mtDNA. Pre-implantation genetic diagnosis (PGD) for mtDNA disease enables embryos produced by in vitro fertilization (IVF) to be screened for mtDNA mutations. Embryos determined to be at low risk (i.e., those having low mutant mtDNA load) can be preferentially transferred to the uterus with the aim of initiating unaffected pregnancies. New evidence that some types of deleterious mtDNA mutations are eliminated within a few generations suggests that women undergoing PGD have a reasonable chance of generating embryos with a lower mutant load than their own. While nuclear transfer may become an alternative approach in future, there might be more difficulties, ethical as well as technical. This Review outlines the implications of recent advances for genetic management of these potentially devastating disorders.

An important goal of population genetics is to determine the forces that have shaped the pattern of genetic variation in natural populations. We developed a maximum likelihood method that allows us to infer demographic changes and detect recent positive selection (selective sweeps) in populations of varying size from DNA polymorphism data. Applying this approach to single nucleotide polymorphism data at more than 250 noncoding loci on the X chromosome of Drosophila melanogaster from an (ancestral) African population and a (derived) European, we found that the African population expanded about 60,000 y ago and that the European population split off from the African lineage about 15,800 y ago, thereby suffering a severe population size bottleneck. We estimated that about 160 beneficial mutations (with selection coefficients s between 0.05% and 0.5%) were fixed in the euchromatic portion of the X in the African population since population size expansion, and about 60 mutations (with s around 0.5%) in the diverging European lineage., Synopsis The authors provide evidence for the recent action of positive selection in the fruit fly Drosophila melanogaster. They describe a new statistical method to detect footprints of selection in the genome of this species and apply it to a large set of DNA polymorphism data from the X chromosome. They find that numerous selective events occurred in the past 60,000 y, while D. melanogaster expanded its ancestral range in Africa and subsequently colonized temperate zones in the rest of the world after the last ice age. The findings of this paper are important as they indicate where in the genome the genes are located that have been involved in the adaptation of D. melanogaster to environmental changes in the recent past. The approach developed here for the model species D. melanogaster can be readily extended to study adaptation in humans and other species.

Through the local selection of landraces, humans have guided the adaptation of crops to a vast range of climatic and ecological conditions. This is particularly true of maize, which was domesticated in a restricted area of Mexico but now displays one of the broadest cultivated ranges worldwide. Here, we sequenced 67 genomes with an average sequencing depth of 18x to document routes of introduction, admixture and selective history of European maize and its American counterparts. To avoid the confounding effects of recent breeding, we targeted germplasm (lines) directly derived from landraces. Among our lines, we discovered 22,294,769 SNPs and between 0.9% to 4.1% residual heterozygosity. Using a segmentation method, we identified 6,978 segments of unexpectedly high rate of heterozygosity. These segments point to genes potentially involved in inbreeding depression, and to a lesser extent to the presence of structural variants. Genetic structuring and inferences of historical splits revealed 5 genetic groups and two independent European introductions, with modest bottleneck signatures. Our results further revealed admixtures between distinct sources that have contributed to the establishment of 3 groups at intermediate latitudes in North America and Europe. We combined differentiation- and diversity-based statistics to identify both genes and gene networks displaying strong signals of selection. These include genes/gene networks involved in flowering time, drought and cold tolerance, plant defense and starch properties. Overall, our results provide novel insights into the evolutionary history of European maize and highlight a major role of admixture in environmental adaptation, paralleling recent findings in humans.