Spatial patterns of variation due to natural selection in humans

Deep learning insights into distinct patterns of polygenic adaptation across human populations

Response to spatiotemporal variation in selection gradients resulted in signatures of polygenic adaptation in human genomes. We introduce RAISING, a two-stage deep learning framework that optimizes neural network architecture through hyperparameter tuning before performing feature selection and prediction tasks. We tested RAISING on published and newly designed simulations that incorporate the complex interplay between demographic history and selection gradients. RAISING outperformed Phylogenetic Generalized Least Squares (PGLS), ridge regression and DeepGenomeScan, with significantly higher true positive rates (TPR) in detecting genetic adaptation. It reduced computational time by 60-fold and increased TPR by up to 28% compared to DeepGenomeScan on published data. In more complex demographic simulations, RAISING showed lower false discoveries and significantly higher TPR, up to 17-fold, compared to other methods. RAISING demonstrated robustness with least sensitivity to demographic history, selection gradient and their interactions. We developed a sliding window method for genome-wide implementation of RAISING to overcome the computational challenges of high-dimensional genomic data. Applied to African, European, South Asian and East Asian populations, we identified multiple genomic regions undergoing polygenic selection. Notably, ∼70% of the regions identified in Africans are unique, with broad patterns distinguishing them from non-Africans, corroborating the Out of Africa dispersal model.

Demographic History and Adaptive Evolution of Indo-Pacific Bottlenose Dolphins (Tursiops aduncus) in Western Australia

Demographic processes can substantially affect a species' response to changing ecological conditions, necessitating the combined consideration of genetic responses to environmental variables and neutral genetic variation. Using a seascape genomics approach combined with population demographic modelling, we explored the interplay of demographic and environmental factors that shaped the current population structure in Indo-Pacific bottlenose dolphins (Tursiops aduncus) along the Western Australian coastline. We combined large-scale environmental data gathered via remote sensing with RADseq genomic data from 133 individuals at 19 sampling sites. Using population genetic and outlier detection analyses, we identified three distinct genetic clusters, coinciding with tropical, subtropical and temperate provincial bioregions. In contrast to previous studies, our demographic models indicated that populations occupying the paleo-shoreline split into two demographically independent lineages before the last glacial maximum (LGM). A subsequent split after the LGM 12-15 kya gave rise to the Shark Bay population, thereby creating the three currently observed clusters. Although multi-locus heterozygosity declined from north to south, dolphins from the southernmost cluster inhabiting temperate waters had higher heterozygosity in potentially adaptive loci compared to dolphins from subtropical and tropical waters. These findings suggest ongoing adaptation to cold-temperate waters in the southernmost cluster, possibly linked to distinct selective pressures between the different bioregions. Our study demonstrated that in the marine realm, without apparent physical boundaries, only a combined approach can fully elucidate the intricate environmental and genetic interactions shaping the evolutionary trajectory of marine mammals.

Population structure and natural selection across a flower color polymorphism in the desert plant Encelia farinosa

PREMISE

Clines-or the geographic sorting of phenotypes across continual space-provide an opportunity to understand the interaction of dispersal, selection, and history in structuring polymorphisms.

METHODS

In this study, we combine field-sampling, genetics, climatic analyses, and machine learning to understand a flower color polymorphism in the wide-ranging desert annual Encelia farinosa.

RESULTS

We find evidence for replicated transitions in disk floret color from brown to yellow across spatial scales, with the most prominent cline stretching ~100 km from southwestern United States into México. Because population structure across the cline is minimal, selection is more likely than drift to have an important role in determining cline width.

CONCLUSIONS

Given that the cline aligns with a climatic transition but there is no evidence for pollinator preference for flower color, we hypothesize that floret color likely varies as a function of climatic conditions.

Multiple genomic solutions for local adaptation in two closely related species (sheep and goats) facing the same climatic constraints

The question of how local adaptation takes place remains a fundamental question in evolutionary biology. The variation of allele frequencies in genes under selection over environmental gradients remains mainly theoretical and its empirical assessment would help understanding how adaptation happens over environmental clines. To bring new insights to this issue we set up a broad framework which aimed to compare the adaptive trajectories over environmental clines in two domesticated mammal species co-distributed in diversified landscapes. We sequenced the genomes of 160 sheep and 161 goats extensively managed along environmental gradients, including temperature, rainfall, seasonality and altitude, to identify genes and biological processes shaping local adaptation. Allele frequencies at putatively adaptive loci were rarely found to vary gradually along environmental gradients, but rather displayed a discontinuous shift at the extremities of environmental clines. Of the 430 candidate adaptive genes identified, only 6 were orthologous between sheep and goats and those responded differently to environmental pressures, suggesting different putative mechanisms involved in local adaptation in these two closely related species. Interestingly, the genomes of the 2 species were impacted differently by the environment, genes related to signatures of selection were most related to altitude, slope and rainfall seasonality for sheep, and summer temperature and spring rainfall for goats. The diversity of candidate adaptive pathways may result from a high number of biological functions involved in the adaptations to multiple eco-climatic gradients, and a differential role of climatic drivers on the two species, despite their co-distribution along the same environmental gradients. This study describes empirical examples of clinal variation in putatively adaptive alleles with different patterns in allele frequency distributions over continuous environmental gradients, thus showing the diversity of genetic responses in adaptive landscapes and opening new horizons for understanding genomics of adaptation in mammalian species and beyond.

Modulation of multiple sclerosis risk and pathogenesis by the gut microbiota: Complex interactions between host genetics, bacterial metabolism, and diet

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system, affecting nearly 2 million people worldwide. The etiology of MS is multifactorial: Approximately 30% of the MS risk is genetic, which implies that the remaining ~70% is environmental, with a number of factors proposed. One recently implicated risk factor for MS is the composition of the gut microbiome. Numerous case-control studies have identified changes in gut microbiota composition of people with MS (pwMS) compared with healthy control individuals, and more recent studies in animal models have begun to identify the causative microbes and underlying mechanisms. Here, we review some of these mechanisms, with a specific focus on the role of host genetic variation, dietary inputs, and gut microbial metabolism, with a particular emphasis on short-chain fatty acid and tryptophan metabolism. We put forward a model where, in an individual genetically susceptible to MS, the gut microbiota and diet can synergize as potent environmental modifiers of disease risk and possibly progression, with diet-dependent gut microbial metabolites serving as a key mechanism. We also propose that specific microbial taxa may have divergent effects in individuals carrying distinct variants of MS risk alleles or other polymorphisms, as a consequence of host gene-by-gut microbiota interactions. Finally, we also propose that the effects of specific microbial taxa, especially those that exert their effects through metabolites, are highly dependent on the host dietary intake. What emerges is a complex multifaceted interaction that has been challenging to disentangle in human studies, contributing to the divergence of findings across heterogeneous cohorts with differing geography, dietary preferences, and genetics. Nonetheless, this provides a complex and individualized, yet tractable, model of how the gut microbiota regulate susceptibility to MS, and potentially progression of this disease. Thus, we conclude that prophylactic or therapeutic modulation of the gut microbiome to prevent or treat MS will require a careful and personalized consideration of host genetics, baseline gut microbiota composition, and dietary inputs.

The WZA: A window-based method for characterizing genotype-environment associations

Genotype-environment association (GEA) studies have the potential to identify the genetic basis of local adaptation in natural populations. Specifically, GEA approaches look for a correlation between allele frequencies and putatively selective features of the environment. Genetic markers with extreme evidence of correlation with the environment are presumed to be tagging the location of alleles that contribute to local adaptation. In this study, we propose a new method for GEA studies called the Weighted-Z Analysis (WZA) that combines information from closely linked sites into analysis windows in a way that was inspired by methods for calculating FST . Performing GEA methods in analysis windows has the advantage that it takes advantage of the increased linkage disequilibrium expected surrounding sites subject to local adaptation. We analyse simulations modelling local adaptation to heterogeneous environments to compare the WZA with existing methods. In the majority of cases we tested, the WZA either outperformed single-SNP (single nucleotide polymorphism)-based approaches or performed similarly. In particular, the WZA outperformed individual SNP approaches when a small number of individuals or demes were sampled. Particularly troubling, we found that some GEA methods exhibit very high false positive rates. We applied the WZA to previously published data from lodgepole pine and identified candidate loci that were identified in the original study alongside numerous loci that were not found in the original study.

Ecology, the pace-of-life, epistatic selection and the maintenance of genetic variation in life-history genes

Evolutionary genetics has long struggled with understanding how functional genes under selection remain polymorphic in natural populations. Taking as a starting point that natural selection is ultimately a manifestation of ecological processes, we spotlight an underemphasized and potentially ubiquitous ecological effect that may have fundamental effects on the maintenance of genetic variation. Negative frequency dependency is a well-established emergent property of density dependence in ecology, because the relative profitability of different modes of exploiting or utilizing limiting resources tends to be inversely proportional to their frequency in a population. We suggest that this may often generate negative frequency-dependent selection (NFDS) on major effect loci that affect rate-dependent physiological processes, such as metabolic rate, that are phenotypically manifested as polymorphism in pace-of-life syndromes. When such a locus under NFDS shows stable intermediate frequency polymorphism, this should generate epistatic selection potentially involving large numbers of loci with more minor effects on life-history (LH) traits. When alternative alleles at such loci show sign epistasis with a major effect locus, this associative NFDS will promote the maintenance of polygenic variation in LH genes. We provide examples of the kind of major effect loci that could be involved and suggest empirical avenues that may better inform us on the importance and reach of this process.

Global phylogeographical distribution of Gloeoporus dichrous

Phylogeographic analyses are efficient in ecological and evolutionary studies to discover the origin of a lineage, its dispersal routes, and the divergence of ancestral traits. Studies on widespread wood-decay fungi have revealed the phylogenetic division of several polypores based on geographical distribution. In this study, specimens of Gloeoporus dichrous, a cosmopolitan polypore species, were collected globally and analyzed for their geographic distribution. Multi-marker Bayesian molecular clock and haplotype analyses revealed a clear division of G. dichrous populations by continent. The species diverged from its neighboring clades 10.3 (16.0-5.6) million years ago, with Asian and North American populations at the center of divergence. Possible dispersal mechanisms and pathways are predicted and discussed based on the evaluated transfer routes. The biogeography of G. dichrous analyzed in this study represents a fraction of the polypore evolution and may advance the understanding of the overall evolution of wood-decay fungi.

Uncovering Footprints of Natural Selection Through Spectral Analysis of Genomic Summary Statistics

Natural selection leaves a spatial pattern along the genome, with a haplotype distribution distortion near the selected locus that fades with distance. Evaluating the spatial signal of a population-genetic summary statistic across the genome allows for patterns of natural selection to be distinguished from neutrality. Considering the genomic spatial distribution of multiple summary statistics is expected to aid in uncovering subtle signatures of selection. In recent years, numerous methods have been devised that consider genomic spatial distributions across summary statistics, utilizing both classical machine learning and deep learning architectures. However, better predictions may be attainable by improving the way in which features are extracted from these summary statistics. We apply wavelet transform, multitaper spectral analysis, and S-transform to summary statistic arrays to achieve this goal. Each analysis method converts one-dimensional summary statistic arrays to two-dimensional images of spectral analysis, allowing simultaneous temporal and spectral assessment. We feed these images into convolutional neural networks and consider combining models using ensemble stacking. Our modeling framework achieves high accuracy and power across a diverse set of evolutionary settings, including population size changes and test sets of varying sweep strength, softness, and timing. A scan of central European whole-genome sequences recapitulated well-established sweep candidates and predicted novel cancer-associated genes as sweeps with high support. Given that this modeling framework is also robust to missing genomic segments, we believe that it will represent a welcome addition to the population-genomic toolkit for learning about adaptive processes from genomic data.

Population Genomics for Insect Conservation

Insects constitute vital components of ecosystems. There is alarming evidence for global declines in insect species diversity, abundance, and biomass caused by anthropogenic drivers such as habitat degradation or loss, agricultural practices, climate change, and environmental pollution. This raises important concerns about human food security and ecosystem functionality and calls for more research to assess insect population trends and identify threatened species and the causes of declines to inform conservation strategies. Analysis of genetic diversity is a powerful tool to address these goals, but so far animal conservation genetics research has focused strongly on endangered vertebrates, devoting less attention to invertebrates, such as insects, that constitute most biodiversity. Insects' shorter generation times and larger population sizes likely necessitate different analytical methods and management strategies. The availability of high-quality reference genome assemblies enables population genomics to address several key issues. These include precise inference of past demographic fluctuations and recent declines, measurement of genetic load levels, delineation of evolutionarily significant units and cryptic species, and analysis of genetic adaptation to stressors. This enables identification of populations that are particularly vulnerable to future threats, considering their potential to adapt and evolve. We review the application of population genomics to insect conservation and the outlook for averting insect declines.

Characterization of DNA Polymerase Genes in Amazonian Amerindian Populations

Due to their continuing geographic isolation, the Amerindian populations of the Brazilian Amazon present a different genetic profile when compared to other continental populations. Few studies have investigated genetic variants present in these populations, especially in the context of next-generation sequencing. Knowledge of the molecular profile of a population is one of the bases for inferences about human evolutionary history, in addition, it has the ability to assist in the validation of molecular biomarkers of susceptibility to complex and rare diseases, and in the improvement of specific precision medicine protocols applied to these populations and to populations with high Amerindian ancestry, such as Brazilians. DNA polymerases play essential roles in DNA replication, repair, recombination, or damage repair, and their influence on various clinical phenotypes has been demonstrated in the specialized literature. Thus, the aim of this study is to characterize the molecular profile of POLA1, POLE, POLG, POLQ, and REV3L genes in Amerindian populations from the Brazilian Amazon, comparing these findings with genomic data from five continental populations described in the gnomAD database, and with data from the Brazilian population described in ABraOM. We performed the whole exome sequencing (WES) of 63 Indigenous individuals. Our study described for the first time the allele frequency of 45 variants already described in the other continental populations, but never before described in the investigated Amerindian populations. Our results also describe eight unique variants of the investigated Amerindians populations, with predictions of moderate, modifier and high clinical impact. Our findings demonstrate the unique genetic profile of the Indigenous population of the Brazilian Amazon, reinforcing the need for further studies on these populations, and may contribute to the creation of public policies that optimize not only the quality of life of this population, but also of the Brazilian population.

Continent-wide patterns of song variation predicted by classical rules of biogeography

Physiological constraints related to atmospheric temperature pose a limit to body and appendage size in endothermic animals. This relationship has been summarised by two classical principles of biogeography: Bergmann's and Allen's rules. Body size may also constrain other phenotypic traits important in ecology, evolution and behaviour, and such effects have seldom been investigated at a continental scale. Through a multilevel-modelling approach, we demonstrate that continent-wide morphology of related African barbets follows predictions of Bergmann's rule, and that body size mirrors variation in song pitch, an acoustic trait important in species recognition and sexual selection. Specifically, effects on song frequency in accordance with Bergmann's rule dwarf those of acoustic adaptation at a continental scale. Our findings suggest that macroecological patterns of body size can influence phenotypic traits important in ecology and evolution, and provide a baseline for further studies on the effects of environmental change on bird song.

Molecular Epidemiology in Amerindians of the Brazilian Amazon Reveals New Genetic Variants in DNA Repair Genes

Native American populations from the Brazilian Amazon have a low genetic diversity and a different genetic profile when compared to people from other continents. Despite this, few studies have been conducted in this group, and there is no description of their genetic data in the various currently existent international databases. The characterization of the genomic profile of a population not only has an impact in studies of population genetics, but also helps to advance diagnostic and therapeutic response studies, leading to the optimization of clinical applicability. Genetic variations in DNA repair genes have been associated with the modulation of susceptibility to various pathologies, as well as in their prognosis and therapy. This is the first study to investigate DNA repair genes in Amerindians from the Brazilian Amazon region. We investigated 13 important DNA repair genes in the exome of 63 Native Americans, comparing our results with those found in 5 continental populations, whose data are available in the Genome Aggregation Database. Our results showed that 57 variants already described in literature were differentially distributed in the Amerindian populations in relation to the continental populations, 7 of which have significant clinical relevance. In addition, 9 new variants were described, suggesting that they are unique to these populations. Our study reinforces the understanding that the Amazonian Native American population presents a unique genetic profile, and our findings may collaborate with the creation of public policies that optimize the quality of life of these groups as well as the Brazilian population, which presents a high degree of interethnic mixing with Amerindian groups.

Octopaminergic/tyraminergic Tdc2 neurons regulate biased sperm usage in female Drosophila melanogaster

In polyandrous internally fertilizing species, a multiply-mated female can use stored sperm from different males in a biased manner to fertilize her eggs. The female's ability to assess sperm quality and compatibility is essential for her reproductive success, and represents an important aspect of postcopulatory sexual selection. In Drosophila melanogaster, previous studies demonstrated that the female nervous system plays an active role in influencing progeny paternity proportion, and suggested a role for octopaminergic/tyraminergic Tdc2 neurons in this process. Here, we report that inhibiting Tdc2 neuronal activity causes females to produce a higher-than-normal proportion of first-male progeny. This difference is not due to differences in sperm storage or release, but instead is attributable to the suppression of second-male sperm usage bias that normally occurs in control females. We further show that a subset of Tdc2 neurons innervating the female reproductive tract is largely responsible for the progeny proportion phenotype that is observed when Tdc2 neurons are inhibited globally. On the contrary, overactivation of Tdc2 neurons does not further affect sperm storage and release or progeny proportion. These results suggest that octopaminergic/tyraminergic signaling allows a multiply-mated female to bias sperm usage, and identify a new role for the female nervous system in postcopulatory sexual selection.

How HLA diversity is apportioned: influence of selection and relevance to transplantation

In his 1972 paper ‘The apportionment of human diversity’, Lewontin showed that, when averaged over loci, genetic diversity is predominantly attributable to differences among individuals within populations. However, selection can alter the apportionment of diversity of specific genes or genomic regions. We examine genetic diversity at the human leucocyte antigen (HLA) loci, located within the major histocompatibility complex (MHC) region. HLA genes code for proteins that are critical to adaptive immunity and are well-documented targets of balancing selection. The single-nucleotide polymorphisms (SNPs) within HLA genes show strong signatures of balancing selection on large timescales and are broadly shared among populations, displaying low F_ST values. However, when we analyse haplotypes defined by these SNPs (which define ‘HLA alleles’), we find marked differences in frequencies between geographic regions. These differences are not reflected in the F_ST values because of the extreme polymorphism at HLA loci, illustrating challenges in interpreting F_ST. Differences in the frequency of HLA alleles among geographic regions are relevant to bone-marrow transplantation, which requires genetic identity at HLA loci between patient and donor. We discuss the case of Brazil's bone marrow registry, where a deficit of enrolled volunteers with African ancestry reduces the chance of finding donors for individuals with an MHC region of African ancestry.

This article is part of the theme issue ‘Celebrating 50 years since Lewontin's apportionment of human diversity’.

The genomic signatures of natural selection in admixed human populations

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

Landscape genomics of the streamside salamander: Implications for species management in the face of environmental change

Understanding spatial patterns of genetic differentiation and local adaptation is critical in a period of rapid environmental change. Climate change and anthropogenic development have led to population declines and shifting geographic distributions in numerous species. The streamside salamander, Ambystoma barbouri, is an endemic amphibian with a small geographic range that predominantly inhabits small, ephemeral streams. As A. barbouri is listed as near-threatened by the IUCN, we describe range-wide patterns of genetic differentiation and adaptation to assess the species' potential to respond to environmental change. We use outlier scans and genetic-environment association analyses to identify genomic variation putatively underlying local adaptation across the species' geographic range. We find evidence for adaptation with a polygenic architecture and a set of candidate SNPs that identify genes putatively contributing to local adaptation. Our results build on earlier work that suggests that some A. barbouri populations are locally adapted despite evidence for asymmetric gene flow between the range core and periphery. Taken together, the body of work describing the evolutionary genetics of range limits in A. barbouri suggests that the species may be unlikely to respond naturally to environmental challenges through a range shift or in situ adaptation. We suggest that management efforts such as assisted migration may be necessary in future.

Stable inversion clines in a grasshopper species group despite complex geographical history

Chromosomal inversions are known to play roles in adaptation and differentiation in many species. They involve clusters of correlated genes (i.e., loci in linkage disequilibrium, LD) possibly associated with environmental variables. The grasshopper "species complex" Trimerotropis pallidipennis comprises several genetic lineages distributed from North to South America in arid and semi-arid high-altitude environments. The southernmost lineage, Trimerotropis sp., segregates for four to seven putative inversions that display clinal variation, possibly through adaptation to temperate environments. We analysed chromosomal, mitochondrial and genome-wide single nucleotide polymorphism data in 19 Trimerotropis sp. populations mainly distributed along two altitudinal gradients (MS and Ju). Populations across Argentina comprise two main chromosomally and genetically differentiated lineages: one distributed across the southernmost border of the "Andes Centrales," adding evidence for a differentiation hotspot in this area; and the other widely distributed in Argentina. Within the latter, network analytical approaches to LD found three clusters of correlated loci (LD-clusters), with inversion karyotypes explaining >79% of the genetic variation. Outlier loci associated with environmental variables mapped to two of these LD-clusters. Furthermore, despite the complex geographical history indicated by population genetic analyses, the clines in inversion karyotypes have remained stable for more than 20 generations, implicating their role in adaptation and differentiation within this lineage. We hypothesize that these clines could be the consequence of a coupling between extrinsic postzygotic barriers and spatially varying selection along environmental gradients resulting in a hybrid zone. These results provide a framework for future investigations about candidate genes implicated in rapid adaptation to new environments.

Populations, Traits, and Their Spatial Structure in Humans

The spatial distribution of genetic variants is jointly determined by geography, past demographic processes, natural selection, and its interplay with environmental variation. A fraction of these genetic variants are "causal alleles" that affect the manifestation of a complex trait. The effect exerted by these causal alleles on complex traits can be independent or dependent on the environment. Understanding the evolutionary processes that shape the spatial structure of causal alleles is key to comprehend the spatial distribution of complex traits. Natural selection, past population size changes, range expansions, consanguinity, assortative mating, archaic introgression, admixture, and the environment can alter the frequencies, effect sizes, and heterozygosities of causal alleles. This provides a genetic axis along which complex traits can vary. However, complex traits also vary along biogeographical and sociocultural axes which are often correlated with genetic axes in complex ways. The purpose of this review is to consider these genetic and environmental axes in concert and examine the ways they can help us decipher the variation in complex traits that is visible in humans today. This initiative necessarily implies a discussion of populations, traits, the ability to infer and interpret "genetic" components of complex traits, and how these have been impacted by adaptive events. In this review, we provide a history-aware discussion on these topics using both the recent and more distant past of our academic discipline and its relevant contexts.

Common host variation drives malaria parasite fitness in healthy human red cells

The replication of Plasmodium falciparum parasites within red blood cells (RBCs) causes severe disease in humans, especially in Africa. Deleterious alleles like hemoglobin S are well-known to confer strong resistance to malaria, but the effects of common RBC variation are largely undetermined. Here, we collected fresh blood samples from 121 healthy donors, most with African ancestry, and performed exome sequencing, detailed RBC phenotyping, and parasite fitness assays. Over one-third of healthy donors unknowingly carried alleles for G6PD deficiency or hemoglobinopathies, which were associated with characteristic RBC phenotypes. Among non-carriers alone, variation in RBC hydration, membrane deformability, and volume was strongly associated with P. falciparum growth rate. Common genetic variants in PIEZO1, SPTA1/SPTB, and several P. falciparum invasion receptors were also associated with parasite growth rate. Interestingly, we observed little or negative evidence for divergent selection on non-pathogenic RBC variation between Africans and Europeans. These findings suggest a model in which globally widespread variation in a moderate number of genes and phenotypes modulates P. falciparum fitness in RBCs.

EST-SSR-based landscape genetics of Pseudotaxus chienii, a tertiary relict conifer endemic to China

Pseudotaxus chienii, belonging to the monotypic genus Pseudotaxus (Taxaceae), is a relict conifer endemic to China. Its populations are usually small and patchily distributed, having a low capacity of natural regeneration. To gain a clearer understanding of how landscape variables affect the local adaptation of P. chienii, we applied EST-SSR markers in conjunction with landscape genetics methods: (a) to examine the population genetic pattern and spatial genetic structure; (b) to perform genome scan and selection scan to identify outlier loci and the associated landscape variables; and (c) to model the ecological niche under climate change. As a result, P. chienii was found to have a moderate level of genetic variation and a high level of genetic differentiation. Its populations displayed a significant positive relationship between the genetic and geographical distance (i.e., "isolation by distance" pattern) and a strong fine-scale spatial genetic structure within 2 km. A putatively adaptive locus EMS6 (functionally annotated to cellulose synthase A catalytic subunit 7) was identified, which was found significantly associated with soil Cu, K, and Pb content and the combined effects of temperature and precipitation. Moreover, P. chienii was predicted to experience significant range contractions in future climate change scenarios. Our results highlight the potential of specific soil metal content and climate variables as the driving force of adaptive genetic differentiation in P. chienii. The data would also be useful to develop a conservation action plan for P. chienii.

Leveraging genetic ancestry to study health disparities

Research to understand human genomic variation and its implications in health has great potential to contribute in the reduction of health disparities. Biological anthropology can play important roles in genomics and health disparities research using a biocultural approach. This paper argues that racial/ethnic categories should not be used as a surrogate for sociocultural factors or global genomic clusters in biomedical research or clinical settings, because of the high genetic heterogeneity that exists within traditional racial/ethnic groups. Genetic ancestry is used to show variation in ancestral genomic contributions to recently admixed populations in the United States, such as African Americans and Hispanic/Latino Americans. Genetic ancestry estimates are also used to examine the relationship between ancestry-related biological and sociocultural factors affecting health disparities. To localize areas of genomes that contribute to health disparities, admixture mapping and genome-wide association studies (GWAS) are often used. Recent GWAS have identified many genetic variants that are highly differentiated among human populations that are associated with disease risk. Some of these are population-specific variants. Many of these variants may impact disease risk and help explain a portion of the difference in disease burden among racial/ethnic groups. Genetic ancestry is also of particular interest in precision medicine and disparities in drug efficacy and outcomes. By using genetic ancestry, we can learn about potential biological differences that may contribute to the heterogeneity observed across self-reported racial groups.

Analysis of Evolution and Ethnic Diversity at Glucose-Associated SNPs of Circadian Clock-Related Loci with Cryptochrome 1, Cryptochrome 2, and Melatonin receptor 1B

Diabetes shows high heritability and, worldwide, causes significant health problems including cardiovascular disease and stroke. There is significant variation in the frequency of diabetes between different populations. Both Cryptochromes and Melatonin have a major role to regulate the circadian clock. Circadian clock failure causes metabolic dysfunctions including diabetes and obesity. Variations in the Cryptochrome 1, the Cryptochrome 2, and the Melatonin receptor 1B (MTNR1B) genes show associations with fasting glucose, and are also related to circadian clock. Here, we analyzed evidence for genetic selection and ethnic diversity at circadian clock- and glucose-related gene loci associated with Cryptochrome 1, Cryptochrome 2, and MTNR1B. We carried out a 3-step genetic method to investigate genetic selection at the Cryptochrome 1, Cryptochrome 2, and MTNR1B on four populations from the 1000 Genomes Project and HapMap. First we used F-statistics to quantify genetic population differences and find ethnic diversity. Then we applied a long-range haplotype test to detect significant extreme long haplotypes, and then the integrated haplotype score (iHS) to find genetic selection at Cryptochrome 1, Cryptochrome 2, and MTNR1B. We observed genetic population differences and ethnic diversity at one glucose-associated Cryptochrome 1 single-nucleotide polymorphism (SNP) (rs8192440), one glucose-associated Cryptochrome 2 SNP (rs11605924), and one glucose-associated MTNR1B SNP (rs10830963) by F-statistics. Both Cryptochrome 1 and MTNR1B also showed selection by the iHS. These observations show new evidence for evolution at Cryptochrome 1, Cryptochrome 2 and MTNR1B. Further investigation should continue to examine the evolution of circadian clock- and glucose-related genes.

Population-specific causal disease effect sizes in functionally important regions impacted by selection

Many diseases exhibit population-specific causal effect sizes with trans-ethnic genetic correlations significantly less than 1, limiting trans-ethnic polygenic risk prediction. We develop a new method, S-LDXR, for stratifying squared trans-ethnic genetic correlation across genomic annotations, and apply S-LDXR to genome-wide summary statistics for 31 diseases and complex traits in East Asians (average N = 90K) and Europeans (average N = 267K) with an average trans-ethnic genetic correlation of 0.85. We determine that squared trans-ethnic genetic correlation is 0.82× (s.e. 0.01) depleted in the top quintile of background selection statistic, implying more population-specific causal effect sizes. Accordingly, causal effect sizes are more population-specific in functionally important regions, including conserved and regulatory regions. In regions surrounding specifically expressed genes, causal effect sizes are most population-specific for skin and immune genes, and least population-specific for brain genes. Our results could potentially be explained by stronger gene-environment interaction at loci impacted by selection, particularly positive selection.

A comprehensive analysis comparing linear and generalized linear models in detecting adaptive SNPs

To understand how organisms adapt to their environment, a gene-environmental association (GEA) analysis is commonly conducted. GEA methods based on mixed models, such as linear latent factor mixed models (LFMM) and LFMM2, have grown in popularity for their robust performance in terms of power and computational speed. However, it is unclear how the assumption of a Gaussian distribution for the response variables influences model performance. In this paper, we develop a generalized linear model (GLM) that allows for non-Gaussian distribution in the genotypic response variables, and treatment of multiallelic nucleotide polymorphisms. Moreover, this multinomial logistic regression model (MLR) is combined with an admixture-based model or principal components analysis to correct for population structure (MLR-ADM and MLR-PC). Using simulations, we evaluate the type 1 error, false discovery rates (FDR), and power to detect selected SNPs, to guide model choice and best practices. With genomic control, MLR-PC and LFMM2 have similar type 1 error, FDRs, and power when analysing biallelic SNPs, while dramatically outperforming models not accounting for population structure. Differences in performance occur under continuous population structure where MLR-PC outperforms LFMM/LFMM2, especially when a larger number of clusters or triallelic SNPs are analysed. The Human Genome Diversity Project (HGDP) data set shows that both MLR-PC and LFMM2 control the inflation of P -values. Analysis of the 1,000 Genome Project Phase 3 data set illustrates that MLR-PC and LFMM2 produce consistent results for most significant SNPs, while MLR-PC discovered additional SNPs corresponding to certain genes, suggesting MLR-PC may be a useful alternative to GEA inference.

Analysis of genetic selection at insulin receptor substrate-2 gene loci

Purpose

Type 2 diabetes mellitus (T2DM) is highly heritable and exhibits significant variability in prevalence between different populations. Prevalence of T2DM is higher in Asian and African relative to European populations. During evolution, traditional feast-famine cycles likely led to significant natural selection impacting metabolic genes. Human adaptation to environmental changes (food supply, lifestyle, climate, and geography) likely influenced differential selection of T2DM-associated genes. Together, insulin receptor substrate-1 and -2 (IRS1 and IRS2) genes encode the major ligands of insulin and IGF1 receptors. Irs2-deficient mice exhibit a T2DM phenotype with severe insulin resistance, and a common IRS2 polymorphism is associated with T2DM. Therefore, the present study sought evidence of natural selection at IRS2 loci.

Methods

Data were sourced from the HapMap and 1000 Genomes projects, comprising four different populations with distinct ancestries: European, Yoruba, Han Chinese, and Japanese. A three-step method was applied to detect IRS2 locus selection. The long-range haplotype (LRH) test detected unusual extended haplotypes, the integrated haplotype score (iHS) detected selection, and Wright's F-statistics (particularly Wright's fixation index: F_ST) were calculated as a measure of population differentiation.

Results

The African population exhibited highly significant LRH findings (percentile >99.9, p = 0.005-0.0009), while both the European and African populations exhibited extreme positive iHS test scores ([iHS] >2.5).

Conclusion

These findings indicate that genetic selection has occurred at the IRS2 locus, warranting further research into the adaptive evolution of metabolic disorder-associated genes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-021-00745-y.

Cultural neuroscience and the research domain criteria: Implications for global mental health

A comprehensive understanding of the basic molecular and cellular mechanisms of the brain is important for the scientific discovery of root causes, risk and protective factors for mental disorders in global mental health. Systematic research in cultural neuroscience within the research domain criteria (RDoC) framework investigates the fundamental biobehavioral dimensions and observable behavior across cultures. Cultural dimensions are characterized in elements of circuit-based mechanisms and behavior across a range of analysis. Research approaches in cultural neuroscience within the RDoC framework advance the evidence-based resources for the development and implementation of cures, preventions and interventions to mental disorders in global mental health. This review presents a novel synthesis of foundations in cultural neuroscience within the research domain criteria framework to advance integrative, translational efforts in discovery and delivery science of mental disorders across cultural contexts in global mental health.

Nutrition Transition and Cancer

Urbanization, population aging, and climatic changes have mostly contributed to nutrition transition and, consequently, to effects of food habits on the epidemic of chronic non-communicable diseases (NCDs), especially cancer. Climatic changes are negatively affecting crop production, particularly biodiversity, leading to reduced food choices and, consequently, nutritional value and the protection conferred from consumption of a variety of nutrients essential in a healthy diet. This brief review analyzes the possible link between rapid demographic changes, climatic and environmental crises, and the current food system as possible factors contributing to the role of nutrition transition in the onset of cancer.

Direct Evidence of an Increasing Mutational Load in Humans

The extent to which selection has shaped present-day human populations has attracted intense scrutiny, and examples of local adaptations abound. However, the evolutionary trajectory of alleles that, today, are deleterious has received much less attention. To address this question, the genomes of 2,062 individuals, including 1,179 ancient humans, were reanalyzed to assess how frequencies of risk alleles and their homozygosity changed through space and time in Europe over the past 45,000 years. Although the overall deleterious homozygosity has consistently decreased, risk alleles have steadily increased in frequency over that period of time. Those that increased most are associated with diseases such as asthma, Crohn disease, diabetes, and obesity, which are highly prevalent in present-day populations. These findings may not run against the existence of local adaptations but highlight the limitations imposed by drift and population dynamics on the strength of selection in purging deleterious mutations from human populations.

Loss of genetic diversity, recovery and allele surfing in a colonizing parasite, Geomydoecus aurei

Understanding the genetic consequences of changes in species distributions has wide-ranging implications for predicting future outcomes of climate change, for protecting threatened or endangered populations and for understanding the history that has led to current genetic patterns within species. Herein, we examine the genetic consequences of range expansion over a 25-year period in a parasite (Geomydoecus aurei) that is in the process of expanding its geographic range via invasion of a novel host. By sampling the genetics of 1,935 G. aurei lice taken from 64 host individuals collected over this time period using 12 microsatellite markers, we test hypotheses concerning linear spatial expansion, genetic recovery time and allele surfing. We find evidence of decreasing allelic richness (AR) with increasing distance from the source population, supporting a linear, stepping stone model of spatial expansion that emphasizes the effects of repeated bottleneck events during colonization. We provide evidence of post-bottleneck genetic recovery, with average AR of infrapopulations increasing about 30% over the 225-generation span of time observed directly in this study. Our estimates of recovery rate suggest, however, that recovery has plateaued and that this population may not reach genetic diversity levels of the source population without further immigration from the source population. Finally, we employ a grid-based sampling scheme in the region of ongoing population expansion and provide empirical evidence for the power of allele surfing to impart genetic structure on a population, even under conditions of selective neutrality and in a place that lacks strong barriers to gene flow.

Interpreting polygenic scores, polygenic adaptation, and human phenotypic differences

Recent analyses of polygenic scores have opened new discussions concerning the genetic basis and evolutionary significance of differences among populations in distributions of phenotypes. Here, we highlight limitations in research on polygenic scores, polygenic adaptation and population differences. We show how genetic contributions to traits, as estimated by polygenic scores, combine with environmental contributions so that differences among populations in trait distributions need not reflect corresponding differences in genetic propensity. Under a null model in which phenotypes are selectively neutral, genetic propensity differences contributing to phenotypic differences among populations are predicted to be small. We illustrate this null hypothesis in relation to health disparities between African Americans and European Americans, discussing alternative hypotheses with selective and environmental effects. Close attention to the limitations of research on polygenic phenomena is important for the interpretation of their relationship to human population differences.

Playing Hide-and-Seek in Beta-Globin Genes: Gene Conversion Transferring a Beneficial Mutation between Differentially Expressed Gene Duplicates

Increasing evidence suggests that adaptation to diverse environments often involves selection on existing variation rather than new mutations. A previous study identified a nonsynonymous single nucleotide polymorphism (SNP) in exon 2 of two paralogous β-globin genes of the bank vole (Clethrionomys glareolus) in Britain in which the ancestral serine (Ser) and the derived cysteine (Cys) allele represent geographically partitioned functional variation affecting the erythrocyte antioxidative capacity. Here we studied the geographical pattern of the two-locus Ser/Cys polymorphism throughout Europe and tested for the geographic correlation between environmental variables and allele frequency, expected if the polymorphism was under spatially heterogeneous environment-related selection. Although bank vole population history clearly is important in shaping the dispersal of the oxidative stress protective Cys allele, analyses correcting for population structure suggest the Europe-wide pattern is affected by geographical variation in environmental conditions. The β-globin phenotype is encoded by the major paralog HBB-T1 but we found evidence of bidirectional gene conversion of exon 2 with the low-expression paralog HBB-T2. Our data support the model where gene conversion reshuffling genotypes between high- and low- expressed paralogs enables tuning of erythrocyte thiol levels, which may help maintain intracellular redox balance under fluctuating environmental conditions. Therefore, our study suggests a possible role for gene conversion between differentially expressed gene duplicates as a mechanism of physiological adaptation of populations to new or changing environments.

Genomic Signatures of Adaptation to a Precipitation Gradient in Nigerian Sorghum

Evolution of plants under climatic gradients may lead to clinal adaptation. Understanding the genomic basis of clinal adaptation in crops species could facilitate breeding for climate resilience. We investigated signatures of clinal adaptation in the cereal crop sorghum (Sorghum bicolor L. [Moench]) to the precipitation gradient in West Africa using a panel (n = 607) of sorghum accessions from diverse agroclimatic zones of Nigeria. Significant correlations were observed between common-garden phenotypes of three putative climate-adaptive traits (flowering time, plant height, and panicle length) and climatic variables. The panel was characterized at >400,000 single nucleotide polymorphisms (SNPs) using genotyping-by-sequencing (GBS). Redundancy analysis indicated that a small proportion of SNP variation can be explained by climate (1%), space (1%), and climate collinear with space (3%). Discriminant analysis of principal components identified three genetic groups that are distributed differently along the precipitation gradient. Genome-wide association studies were conducted with phenotypes and three climatic variables (annual mean precipitation, precipitation in the driest quarter, and annual mean temperature). There was no overall enrichment of associations near a priori candidate genes implicated in flowering time, height, and inflorescence architecture in cereals, but several significant associations were found near a priori candidates including photoperiodic flowering regulators SbCN12 and Ma6 Together, the findings suggest that a small (3%) but significant proportion of nucleotide variation in Nigerian sorghum landraces reflects clinal adaptation along the West African precipitation gradient.

Spatial analyzes of HLA data in Rio Grande do Sul, south Brazil: genetic structure and possible correlation with autoimmune diseases

Background

HLA genes are the most polymorphic of the human genome and have distinct allelic frequencies in populations of different geographical regions of the world, serving as genetic markers in ancestry studies. In addition, specific HLA alleles may be associated with various autoimmune and infectious diseases. The bone marrow donor registry in Brazil is the third largest in the world, and it counts with genetic typing of HLA-A, -B, and -DRB1. Since 1991 Brazil has maintained the DATASUS database, a system fed with epidemiological and health data from compulsory registration throughout the country.

Methods

In this work, we perform spatial analysis and georeferencing of HLA genetic data from more than 86,000 bone marrow donors from Rio Grande do Sul (RS) and data of hospitalization for rheumatoid arthritis, multiple sclerosis and Crohn’s disease in RS, comprising the period from 1995 to 2016 obtained through the DATASUS system. The allele frequencies were georeferenced using Empirical Bayesian Kriging; the diseases prevalence were georeferenced using Inverse Distance Weighted and cluster analysis for both allele and disease were performed using Getis-Ord Gi* method. Spearman’s test was used to test the correlation between each allele and disease.

Results

The results indicate a HLA genetic structure compatible with the history of RS colonization, where it is possible to observe differentiation between regions that underwent different colonization processes. Spatial analyzes of autoimmune disease hospitalization data were performed revealing clusters for different regions of the state for each disease analyzed. The correlation test between allelic frequency and the occurrence of autoimmune diseases indicated a significant correlation between the HLA-B*08 allele and rheumatoid arthritis.

Conclusions

Genetic mapping of populations and the spatial analyzes such as those performed in this work have great economic relevance and can be very useful in the formulation of public health campaigns and policies, contributing to the planning and adjustment of clinical actions, as well as informing and educating professionals and the population.

Electronic supplementary material

The online version of this article (10.1186/s12942-018-0154-8) contains supplementary material, which is available to authorized users.

Leveraging GWAS for complex traits to detect signatures of natural selection in humans

Natural selection can shape the genetic architecture of complex traits. In human populations, signals of positive selection at genetic loci have been detected through a variety of genome-wide scanning approaches without the knowledge of how genes affect traits or fitness. In the past decade, genome-wide association studies (GWAS) have provided unprecedented insights into the genetic basis of quantitative variation in complex traits. Summary statistics generated from these GWAS have been shown to be an extraordinary data source that can be utilized to detect and quantify natural selection in the genetic architecture of complex traits. In this review, we focus on recent discoveries about selection on genetic variants associated with human complex traits based on GWAS-facilitated methods.

Global genetic differentiation of complex traits shaped by natural selection in humans

There are mean differences in complex traits among global human populations. We hypothesize that part of the phenotypic differentiation is due to natural selection. To address this hypothesis, we assess the differentiation in allele frequencies of trait-associated SNPs among African, Eastern Asian, and European populations for ten complex traits using data of large sample size (up to ~405,000). We show that SNPs associated with height ([Formula: see text]), waist-to-hip ratio ([Formula: see text]), and schizophrenia ([Formula: see text]) are significantly more differentiated among populations than matched "control" SNPs, suggesting that these trait-associated SNPs have undergone natural selection. We further find that SNPs associated with height ([Formula: see text]) and schizophrenia ([Formula: see text]) show significantly higher variance in linkage disequilibrium (LD) scores across populations than control SNPs. Our results support the hypothesis that natural selection has shaped the genetic differentiation of complex traits, such as height and schizophrenia, among worldwide populations.

Genetic Hitchhiking and Population Bottlenecks Contribute to Prostate Cancer Disparities in Men of African Descent

Prostate cancer incidence and mortality rates in African and African American men are greatly elevated compared with other ethnicities. This disparity is likely explained by a combination of social, environmental, and genetic factors. A large number of susceptibility loci have been reported by genome-wide association studies (GWAS), but the contribution of these loci to prostate cancer disparities is unclear. Here, we investigated the population structure of 68 previously reported GWAS loci and calculated genetic disparity contribution statistics to identify SNPs that contribute the most to differences in prostate cancer risk across populations. By integrating GWAS results with allele frequency data, we generated genetic risk scores for 45 African and 19 non-African populations. Tests of natural selection were used to assess why some SNPs have large allele frequency differences across populations. We report that genetic predictions of prostate cancer risks are highest for West African men and lowest for East Asian men. These differences may be explained by the out-of-Africa bottleneck and natural selection. A small number of loci appear to drive elevated prostate cancer risks in men of African descent, including rs9623117, rs6983267, rs10896449, rs10993994, and rs817826. Although most prostate cancer-associated loci are evolving neutrally, there are multiple instances where alleles have hitchhiked to high frequencies with linked adaptive alleles. For example, a protective allele at 2q37 appears to have risen to high frequency in Europe due to selection acting on pigmentation. Our results suggest that evolutionary history contributes to the high rates of prostate cancer in African and African American men.Significance: A small number of genetic variants cause an elevated risk of prostate cancer in men of West African descent. Cancer Res; 78(9); 2432-43. ©2018 AACR.

Multiple Modes of Positive Selection Shaping the Patterns of Incomplete Selective Sweeps over African Populations of Drosophila melanogaster

It remains a challenge in evolutionary genetics to elucidate how beneficial mutations arise and propagate in a population and how selective pressures on mutant alleles are structured over space and time. By identifying "sweeping haplotypes (SHs)" that putatively carry beneficial alleles and are increasing (or have increased) rapidly in frequency, and surveying the geographic distribution of SH frequencies, we can indirectly infer how selective sweeps unfold in time and thus which modes of positive selection underlie those sweeps. Using population genomic data from African Drosophila melanogaster, we identified SHs from 37 candidate loci under selection. At more than half of loci, we identify single SHs. However, many other loci harbor multiple independent SHs, namely soft selective sweeps, either due to parallel evolution across space or a high beneficial mutation rate. At about a quarter of the loci, intermediate SH frequencies are found across multiple populations, which cannot be explained unless a certain form of frequency-dependent positive selection, such as heterozygote advantage, is invoked given the reasonable range of migration rates between African populations. At one locus, many independent SHs are observed over multiple populations but always together with ancestral haplotypes. This complex pattern is compatible with a large number of mutational targets in a gene and frequency-dependent selection on new variants. We conclude that very diverse modes of positive selection are operating at different sets of loci in D. melanogaster populations.

FineMAV: prioritizing candidate genetic variants driving local adaptations in human populations

We present a new method, Fine-Mapping of Adaptive Variation (FineMAV), which combines population differentiation, derived allele frequency, and molecular functionality to prioritize positively selected candidate variants for functional follow-up. We calibrate and test FineMAV using eight experimentally validated "gold standard" positively selected variants and simulations. FineMAV has good sensitivity and a low false discovery rate. Applying FineMAV to the 1000 Genomes Project Phase 3 SNP dataset, we report many novel selected variants, including ones in TGM3 and PRSS53 associated with hair phenotypes that we validate using available independent data. FineMAV is widely applicable to sequence data from both human and other species.

Reticulation, divergence, and the phylogeography-phylogenetics continuum

Phylogeography, and its extensions into comparative phylogeography, have their roots in the layering of gene trees across geography, a paradigm that was greatly facilitated by the nonrecombining, fast evolution provided by animal mtDNA. As phylogeography moves into the era of next-generation sequencing, the specter of reticulation at several levels-within loci and genomes in the form of recombination and across populations and species in the form of introgression-has raised its head with a prominence even greater than glimpsed during the nuclear gene PCR era. Here we explore the theme of reticulation in comparative phylogeography, speciation analysis, and phylogenomics, and ask how the centrality of gene trees has fared in the next-generation era. To frame these issues, we first provide a snapshot of multilocus phylogeographic studies across the Carpentarian Barrier, a prominent biogeographic barrier dividing faunas spanning the monsoon tropics in northern Australia. We find that divergence across this barrier is evident in most species, but is heterogeneous in time and demographic history, often reflecting the taxonomic distinctness of lineages spanning it. We then discuss a variety of forces generating reticulate patterns in phylogeography, including introgression, contact zones, and the potential selection-driven outliers on next-generation molecular markers. We emphasize the continued need for demographic models incorporating reticulation at the level of genomes and populations, and conclude that gene trees, whether explicit or implicit, should continue to play a role in the future of phylogeography.

Visualizing the geography of genetic variants

Summary

One of the key characteristics of any genetic variant is its geographic distribution. The geographic distribution can shed light on where an allele first arose, what populations it has spread to, and in turn on how migration, genetic drift, and natural selection have acted. The geographic distribution of a genetic variant can also be of great utility for medical/clinical geneticists and collectively many genetic variants can reveal population structure. Here we develop an interactive visualization tool for rapidly displaying the geographic distribution of genetic variants. Through a REST API and dynamic front-end, the Geography of Genetic Variants (GGV) browser ( http://popgen.uchicago.edu/ggv/ ) provides maps of allele frequencies in populations distributed across the globe.

Availability and Implementation

GGV is implemented as a website ( http://popgen.uchicago.edu/ggv/ ) which employs an API to access frequency data ( http://popgen.uchicago.edu/freq_api/ ). Python and javascript source code for the website and the API are available at: http://github.com/NovembreLab/ggv/ and http://github.com/NovembreLab/ggv-api/ .

Contact

jnovembre@uchicago.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

The colonization and divergence patterns of Brandt's vole (Lasiopodomys brandtii) populations reveal evidence of genetic surfing

Background

The colonial habit of Brandt’s vole (Lasiopodomys brandtii) differs from that of most other species of the genus Microtus. The demographic history of this species and the patterns shaping its current genetic structure remain unknown. Here, we explored patterns of genetic differentiation and infered the demographic history of Brandt’s vole populations through analyses of nuclear microsatellite and D-loop sequences.

Results

Phylogenetic analyses divided the sampled populations into three main clusters, which represent the southeastern, northeastern and western parts of the total range in Mongolia and China. Molecular data revealed an ancestral area located in the southeast of the extant range, in the Xilinguole District, Inner Mongolia, China, from where Brandt’s vole populations began expanding. A gene flow analysis suggested that the most likely colonization route was from the ancestral area and was followed by subsequent northeastward and westward range expansions. We identified decreases in genetic diversity with increasing distance from the founder population within the newly occupied regions (northeastern and western regions), clinal patterns in the allele frequencies, alleles that were rare in the original area that have become common in the newly occupied regions, and higher genetic differentiation in the expanded range compared with the original one.

Conclusion

Our results indicate that L. brandtii most likely originated from the southeastern part of its current geographic range, and subsequently colonized into the northeastern and western parts by expansion. The genetic patterns among the derived populations and with respect to the original population are consistent with that expected under genetic surfing models, which indicated that genetic drift, rather than gene flow, is the predominant factor underlying the genetic structure of expanding Brandt’s vole populations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-017-0995-y) contains supplementary material, which is available to authorized users.

Continental-level population differentiation and environmental adaptation in the mushroom Suillus brevipes

Recent advancements in sequencing technology allowed researchers to better address the patterns and mechanisms involved in microbial environmental adaptation at large spatial scales. Here we investigated the genomic basis of adaptation to climate at the continental scale in Suillus brevipes, an ectomycorrhizal fungus symbiotically associated with the roots of pine trees. We used genomic data from 55 individuals in seven locations across North America to perform genome scans to detect signatures of positive selection and assess whether temperature and precipitation were associated with genetic differentiation. We found that S. brevipes exhibited overall strong population differentiation, with potential admixture in Canadian populations. This species also displayed genomic signatures of positive selection as well as genomic sites significantly associated with distinct climatic regimes and abiotic environmental parameters. These genomic regions included genes involved in transmembrane transport of substances and helicase activity potentially involved in cold stress response. Our study sheds light on large-scale environmental adaptation in fungi by identifying putative adaptive genes and providing a framework to further investigate the genetic basis of fungal adaptation.

Population Structure of UK Biobank and Ancient Eurasians Reveals Adaptation at Genes Influencing Blood Pressure

Analyzing genetic differences between closely related populations can be a powerful way to detect recent adaptation. The very large sample size of the UK Biobank is ideal for using population differentiation to detect selection and enables an analysis of the UK population structure at fine resolution. In this study, analyses of 113,851 UK Biobank samples showed that population structure in the UK is dominated by five principal components (PCs) spanning six clusters: Northern Ireland, Scotland, northern England, southern England, and two Welsh clusters. Analyses of ancient Eurasians revealed that populations in the northern UK have higher levels of Steppe ancestry and that UK population structure cannot be explained as a simple mixture of Celts and Saxons. A scan for unusual population differentiation along the top PCs identified a genome-wide-significant signal of selection at the coding variant rs601338 in FUT2 (p = 9.16 × 10-9). In addition, by combining evidence of unusual differentiation within the UK with evidence from ancient Eurasians, we identified genome-wide-significant (p = 5 × 10-8) signals of recent selection at two additional loci: CYP1A2-CSK and F12. We detected strong associations between diastolic blood pressure in the UK Biobank and both the variants with selection signals at CYP1A2-CSK (p = 1.10 × 10-19) and the variants with ancient Eurasian selection signals at the ATXN2-SH2B3 locus (p = 8.00 × 10-33), implicating recent adaptation related to blood pressure.