On the stability of the Bayenv method in assessing human SNP-environment associations

Genotype-environment associations reveal genes potentially linked to avian malaria infection in populations of an endemic island bird

Patterns of pathogen prevalence are, at least partially, the result of coevolutionary host-pathogen interactions. Thus, exploring the distribution of host genetic variation in relation to infection by a pathogen within and across populations can provide important insights into mechanisms of host defence and adaptation. Here, we use a landscape genomics approach (Bayenv) in conjunction with genome-wide data (ddRADseq) to test for associations between avian malaria (Plasmodium) prevalence and host genetic variation across 13 populations of the island endemic Berthelot's pipit (Anthus berthelotii). Considerable and consistent spatial heterogeneity in malaria prevalence was observed among populations over a period of 15 years. The prevalence of malaria infection was also strongly positively correlated with pox (Avipoxvirus) prevalence. Multiple host loci showed significant associations with malaria prevalence after controlling for genome-wide neutral genetic structure. These sites were located near to or within genes linked to metabolism, stress response, transcriptional regulation, complement activity and the inflammatory response, many previously implicated in vertebrate responses to malarial infection. Our findings identify diverse genes - not just limited to the immune system - that may be involved in host protection against malaria and suggest that spatially variable pathogen pressure may be an important evolutionary driver of genetic divergence among wild animal populations, such as Berthelot's pipit. Furthermore, our data indicate that spatio-temporal variation in multiple different pathogens (e.g. malaria and pox in this case) may have to be studied together to develop a more holistic understanding of host pathogen-mediated evolution.

In silico profiling of nonsynonymous SNPs of fat mass and obesity-associated gene: possible impacts on the treatment of non-alcoholic fatty liver disease

BACKGROUND

Nonalcoholic fatty liver, or NAFLD, is the most common chronic liver ailment. It is characterized by excessive fat deposition in hepatocytes of individuals who consume little or no alcohol and are unaffected by specific liver damaging factors. It is also associated with extrahepatic manifestations such as chronic kidney disease, cardiovascular disease, and sleep apnea. The global burden of NAFLD is increasing at an alarming rate. However, no pharmacologically approved drugs against NAFLD are available owing to their complex pathophysiology. Genome-wide association studies have uncovered SNPs in the fat mass and obesity-associated gene (FTO) that are robustly associated with obesity and higher BMI. The prevalence of NAFLD increases in parallel with the increasing prevalence of obesity. Since FTO might play a crucial role in NAFLD development, the current study identified five potentially deleterious mutations from 383 ns-SNPs in the human FTO gene using various in silico tools.

METHODS

This study aims to identify potentially deleterious nonsynonymous SNPs (ns-SNPs) employing various in silico tools. Additionally, molecular modeling approaches further studied the structural changes caused by identified SNPs. Moreover, molecular dynamics studies finally investigated the binding potentials of the phytochemicals resveratrol, rosmarinic acid, and capsaicin with different mutant forms of FTO.

RESULTS

The current investigation has five potentially deleterious mutations from 383 ns-SNPs in the human FTO gene using various in silico tools. The present study identified five nsSNPs of the human gene FTO, Gly103Asp, Arg96Pro, Tyr295Cys, and Arg322Gln, with an apparent connection to the disease condition. Modulation of demethylation activity by phytomolecule scanning explains the hepatoprotective action of molecules. The current investigation also suggested that predicted mutations did not affect the binding ability of three polyphenols: rosamarinic acid, resveratrol, and capsaicin.

CONCLUSION

This study showed that the predicted mutations in FTO did not affect the binding of three polyphenols. Thus, these three molecules can significantly aid drug development against FTO and NAFLD.

LPInsider: a webserver for lncRNA–protein interaction extraction from the literature

Background

Long non-coding RNA (LncRNA) plays important roles in physiological and pathological processes. Identifying LncRNA–protein interactions (LPIs) is essential to understand the molecular mechanism and infer the functions of lncRNAs. With the overwhelming size of the biomedical literature, extracting LPIs directly from the biomedical literature is essential, promising and challenging. However, there is no webserver of LPIs relationship extraction from literature.

Results

LPInsider is developed as the first webserver for extracting LPIs from biomedical literature texts based on multiple text features (semantic word vectors, syntactic structure vectors, distance vectors, and part of speech vectors) and logistic regression. LPInsider allows researchers to extract LPIs by uploading PMID, PMCID, PMID List, or biomedical text. A manually filtered and highly reliable LPI corpus is integrated in LPInsider. The performance of LPInsider is optimal by comprehensive experiment on different combinations of different feature and machine learning models.

Conclusions

LPInsider is an efficient analytical tool for LPIs that helps researchers to enhance their comprehension of lncRNAs from text mining, and also saving their time. In addition, LPInsider is freely accessible from http://www.csbg-jlu.info/LPInsider/ with no login requirement. The source code and LPIs corpus can be downloaded from https://github.com/qiufengdiewu/LPInsider.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04665-3.

Genomic associations with poxvirus across divergent island populations in Berthelot's pipit

Understanding the mechanisms and genes that enable animal populations to adapt to pathogens is important from an evolutionary, health and conservation perspective. Berthelot's pipit (Anthus berthelotii) experiences extensive and consistent spatial heterogeneity in avian pox infection pressure across its range of island populations, thus providing an excellent system with which to examine how pathogen-mediated selection drives spatial variation in immunogenetic diversity. Here we test for evidence of genetic variation associated with avian pox at both an individual and population-level. At the individual level, we find no evidence that variation in MHC class I and TLR4 (both known to be important in recognising viral infection) was associated with pox infection within two separate populations. However, using genotype-environment association (Bayenv) in conjunction with genome-wide (ddRAD-seq) data, we detected strong associations between population-level avian pox prevalence and allele frequencies of single nucleotide polymorphisms (SNPs) at a number of sites across the genome. These sites were located within genes involved in cellular stress signalling and immune responses, many of which have previously been associated with responses to viral infection in humans and other animals. Consequently, our analyses indicates that pathogen-mediated selection may play a role in shaping genomic variation among relatively recently colonised island bird populations and highlights the utility of genotype-environment associations for identifying candidate genes potentially involved in host-pathogen interactions.

Evaluation of exosomal non-coding RNAs in cancer using high-throughput sequencing

Clinical oncologists need more reliable and non-invasive diagnostic and prognostic biomarkers to follow-up cancer patients. However, the existing biomarkers are often invasive and costly, emphasizing the need for the development of biomarkers to provide convenient and precise detection. Extracellular vesicles especially exosomes have recently been the focus of translational research to develop non-invasive and reliable biomarkers for several diseases such as cancers, suggesting as a valuable source of tumor markers. Exosomes are nano-sized extracellular vesicles secreted by various living cells that can be found in all body fluids including serum, urine, saliva, cerebrospinal fluid, and ascites. Different molecular and genetic contents of their origin such as nucleic acids, proteins, lipids, and glycans in a stable form make exosomes a promising approach for various cancers' diagnoses, prediction, and follow-up in a minimally invasive manner. Since exosomes are used by cancer cells for intercellular communication, they play a critical role in the disease process, highlighting the importance of their use as clinically relevant biomarkers. However, regardless of the advantages that exosome-based diagnostics have, they suffer from problems regarding their isolation, detection, and characterization of their contents. This study reviews the history and biogenesis of exosomes and discusses non-coding RNAs (ncRNAs) and their potential as tumor markers in different types of cancer, with a focus on next generation sequencing (NGS) as a detection method. Moreover, the advantages and challenges associated with exosome-based diagnostics are also presented.

Large-scale genome-wide study reveals climate adaptive variability in a cosmopolitan pest

Understanding the genetic basis of climatic adaptation is essential for predicting species' responses to climate change. However, intraspecific variation of these responses arising from local adaptation remains ambiguous for most species. Here, we analyze genomic data from diamondback moth (Plutella xylostella) collected from 75 sites spanning six continents to reveal that climate-associated adaptive variation exhibits a roughly latitudinal pattern. By developing an eco-genetic index that combines genetic variation and physiological responses, we predict that most P. xylostella populations have high tolerance to projected future climates. Using genome editing, a key gene, PxCad, emerged from our analysis as functionally temperature responsive. Our results demonstrate that P. xylostella is largely capable of tolerating future climates in most of the world and will remain a global pest beyond 2050. This work improves our understanding of adaptive variation along environmental gradients, and advances pest forecasting by highlighting the genetic basis for local climate adaptation.

Disentangling adaptation from drift in bottlenecked and reintroduced populations of Alpine ibex

Identifying local adaptation in bottlenecked species is essential for conservation management. Selection detection methods have an important role in species management plans, assessments of adaptive capacity, and looking for responses to climate change. Yet, the allele frequency changes exploited in selection detection methods are similar to those caused by the strong neutral genetic drift expected during a bottleneck. Consequently, it is often unclear what accuracy selection detection methods have across bottlenecked populations. In this study, simulations were used to explore if signals of selection could be confidently distinguished from genetic drift across 23 bottlenecked and reintroduced populations of Alpine ibex (Capra ibex). The meticulously recorded demographic history of the Alpine ibex was used to generate comprehensive simulated SNP data. The simulated SNPs were then used to benchmark the confidence we could place in outliers identified in empirical Alpine ibex RADseq derived SNP data. Within the simulated data set, the false positive rates were high for all selection detection methods (F_ST outlier scans and Genetic‐Environment Association analyses) but fell substantially when two or more methods were combined. True positive rates were consistently low and became negligible with increased stringency. Despite finding many outlier loci in the empirical Alpine ibex SNPs, none could be distinguished from genetic drift‐driven false positives. Unfortunately, the low true positive rate also prevents the exclusion of recent local adaptation within the Alpine ibex. The baselines and stringent approach outlined here should be applied to other bottlenecked species to ensure the risk of false positive, or negative, signals of selection are accounted for in conservation management plans.

Population structure, diversifying selection, and local adaptation in Pinus patula

PREMISE

Climate change is predicted to affect natural and plantation forests. The responses of conifers to overcome changing environments will depend on their adaptation to local conditions; however, intraspecific adaptive genetic variation is unknown for most gymnosperms. Studying genetic diversity associated with phenotypic variability along environmental gradients will enhance our understanding of adaptation and may reveal genetic pools important for conservation and management.

METHODS

We used target enrichment and genome skimming to obtain single nucleotide polymorphisms (SNPs) from 61 individuals of Pinus patula, a pine tree native to Mexico widely used in plantation forestry. We investigated the adaptive genetic variation of two varieties with morphological and distributional differences potentially related to genetic and adaptive divergence.

RESULTS

Population structure and haplotype network analyses revealed that genetic diversity between P. patula var. patula and P. patula var. longipedunculata was structured, even within populations of P. patula var. longipedunculata. We observed high genetic diversity, low inbreeding rate, and rapid linkage disequilibrium (LD) decay in the varieties. Based on outlier tests, loci showing signatures of natural selection were detected in geographically distant P. patula var. longipedunculata populations. For both varieties, we found significant correlations between climate-related environmental variation and SNP diversity at loci involved in abiotic stress, cell transport, defense, and cell wall biogenesis, pointing to local adaptation.

CONCLUSIONS

Overall, significant intraspecific adaptive genetic variation in P. patula was detected, highlighting the presence of different genetic pools and signs of local adaptation that should be considered in forestry and conservation.

Population Genomic Analysis of Two Endemic Schizothoracins Reveals Their Genetic Differences and Underlying Selection Associated with Altitude and Temperature

Simple Summary

Diptychus maculates and Gymnodiptychus dybowskii are two rare aboriginal fishes in the Xinjiang Uygur Autonomous Region. In recent years, due to overfishing and habitat fragmentation caused by construction of water conservancy and hydropower projects, the fishery resources have decreased sharply. Understanding the genetic background is of great significance for resource protection. In this study, we revealed the similar trends of population genetic diversities in these two species collected from the Tarim River and the Yili River. In addition, outlier SNPs associated with temperature and altitude were detected in both of them, indicating that Schizothoracinae fishes represented by D. maculates and G. dybowskii were still under the selection pressure of plateau environments.

Abstract

Schizothoracins are a group of cyprinid fishes distributed throughout the Qinghai–Tibet Plateau, which can be classified in three grades: primitive, specialised and highly specialised according to adaptation ability to plateau environments. As the only specialised schizothoracins in Xinjiang, China, Diptychus maculates and Gymnodiptychus dybowskii are ideal materials for adaptive evolution research. Based on single-nucleotide polymorphism (SNP) loci detected by specific-locus amplified fragment (SLAF) technology, the genome-wide genetic diversities of these two species from nine sites in Xinjiang were evaluated. D.maculates in the Muzat River (BM) and G. dybowskii in the Kaidu River (LKG) presented the lowest genetic diversity levels, whereas D. maculates in the Kumarik River (BK) and G.dybowskii in the Kashi River (LK) were just the opposite. Cluster and principal component analysis demonstrated a distant genetic affinity between D. maculates in the Tashkurgan River (BT) and other populations. Outlier SNP loci were discovered both in D. maculates and G. dybowskii. The coalescent Bayenv and latent factor mixed model (LFMM) methods showed that a total of thirteen and eighteen SNPs in D. maculates were associated with altitude and temperature gradient, respectively. No intersection was revealed in G. dybowskii. The results indicated that D. maculates was subject to much greater divergent selection pressure. A strong signal of isolation-by-distance (IBD) was detected across D. maculates (Mantel test, rs = 0.65; p = 0.05), indicating an evident geographical isolation in the Tarim River. Isolation-by-environment (IBE) analysis implied that temperature and altitude selections were more intensive in D. maculates, with greater environmental variation resulting in weak gene flow.

Long noncoding RNA TANCR promotes γδ T cells activation by regulating TRAIL expression in cis

Background

γδ T cells are an important subset of T lymphocytes that play important roles in innate and adaptive immunity via the secretion of various cytokines. Previous studies have found that long noncoding RNAs (lncRNAs) are critical regulators that contribute to the development of immune cells. However, the functions of lncRNAs in the γδ T cells remains poorly studied.

Results

Here, we identified the novel function of lncRNA NONHSAT196558.1 in isopentenyl pyrophosphate (IPP)-activated and -expanded γδ T cells using RNA-seq. As it functioned as an activating noncoding RNA of tumor necrosis factor related apoptosis-inducing ligand (TRAIL), an important cytotoxic cytokine that expressed by γδ T cells in responding to various infectious agents, we named this lncRNA as TANCR. Secondly, the expression of TANCR was found to be positively correlated with TRAIL expression in IPP activated γδ T cells. In addition, TANCR was confirmed to localized both in nucleus and cytoplasm. Finally, a loss-of-function was conducted by using siRNA/ASO or CRISPR/Cas9 system to knockdown or knockout TANCR, and confirmed that silencing of TANCR inhibits TRAIL expression in several kinds of cells, including HEK293T cells, Jurkat cells, and primary γδ T cells.

Conclusion

These evidences demonstrate that TANCR play important roles in γδ T cell activation. Furthermore, TANCR may be involved in the cytotoxicity of γδ T cells. This study aims to further our understanding of the molecular mechanisms underlying lncRNA-mediated immune responses.

Genomic assessment of local adaptation in dwarf birch to inform assisted gene flow

When populations of a rare species are small, isolated and declining under climate change, some populations may become locally maladapted. Detecting this maladaptation may allow effective rapid conservation interventions, even if based on incomplete knowledge. Population maladaptation may be estimated by finding genome-environment associations (GEA) between allele frequencies and environmental variables across a local species range, and identifying populations whose allele frequencies do not fit with these trends. We can then design assisted gene flow strategies for maladapted populations, to adjust their allele frequencies, entailing lower levels of intervention than with undirected conservation action. Here, we investigate this strategy in Scottish populations of the montane plant dwarf birch (Betula nana). In genome-wide restriction site-associated single nucleotide polymorphism (SNP) data, we found 267 significant associations between SNP loci and environmental variables. We ranked populations by maladaptation estimated using allele frequency deviation from the general trends at these loci; this gave a different prioritization for conservation action than the Shapely Index, which seeks to preserve rare neutral variation. Populations estimated to be maladapted in their allele frequencies at loci associated with annual mean temperature were found to have reduced catkin production. Using an environmental niche modelling (ENM) approach, we found annual mean temperature (35%), and mean diurnal range (15%), to be important predictors of the dwarf birch distribution. Intriguingly, there was a significant correlation between the number of loci associated with each environmental variable in the GEA and the importance of that variable in the ENM. Together, these results suggest that the same environmental variables determine both adaptive genetic variation and species range in Scottish dwarf birch. We suggest an assisted gene flow strategy that aims to maximize the local adaptation of dwarf birch populations under climate change by matching allele frequencies to current and future environments.

Looking for Local Adaptation: Convergent Microevolution in Aleppo Pine (Pinus halepensis)

Finding outlier loci underlying local adaptation is challenging and is best approached by suitable sampling design and rigorous method selection. In this study, we aimed to detect outlier loci (single nucleotide polymorphisms, SNPs) at the local scale by using Aleppo pine (Pinus halepensis), a drought resistant conifer that has colonized many habitats in the Mediterranean Basin, as the model species. We used a nested sampling approach that considered replicated altitudinal gradients for three contrasting sites. We genotyped samples at 294 SNPs located in genomic regions selected to maximize outlier detection. We then applied three different statistical methodologies-Two Bayesian outlier methods and one latent factor principal component method-To identify outlier loci. No SNP was an outlier for all three methods, while eight SNPs were detected by at least two methods and 17 were detected only by one method. From the intersection of outlier SNPs, only one presented an allelic frequency pattern associated with the elevational gradient across the three sites. In a context of multiple populations under similar selective pressures, our results underline the need for careful examination of outliers detected in genomic scans before considering them as candidates for convergent adaptation.

Ecological factors and morphological traits are associated with repeated genomic differentiation between lake and stream stickleback

The repeated evolution of similar phenotypes in independent populations (i.e. parallel or convergent evolution) provides an opportunity to identify genetic and ecological factors that influence the process of adaptation. Threespine stickleback fish ( Gasterosteus aculeatus) are an excellent model for such studies, as they have repeatedly adapted to divergent habitats across the Northern hemisphere. Here, we use genomic, ecological and morphological data from 16 independent pairs of stickleback populations adapted to divergent lake and stream habitats. We combine a population genomic approach to identify regions of the genome that are likely under selection in these divergent habitats with an association mapping approach to identify regions of the genome that underlie variation in ecological factors and morphological traits. Over 37% of genomic windows are repeatedly differentiated across lake-stream pairs. Similarly, many genomic windows are associated with variation in abiotic factors, diet items and morphological phenotypes. Both the highly differentiated windows and candidate trait windows are non-randomly distributed across the genome and show some overlap. However, the overlap is not significant on a genome-wide scale. Together, our data suggest that adaptation to divergent food resources and predation regimes are drivers of differentiation in lake-stream stickleback, but that additional ecological factors are also important. This article is part of the theme issue 'Convergent evolution in the genomics era: new insights and directions'.

Phenotypic and genome-wide association with the local environment of Arabidopsis

The environment imposes critical selective forces on all living organisms, and the sessile nature of plants makes them particularly useful for investigating the relationship between genetic variation and environmental adaptation. In the model plant Arabidopsis thaliana, extensive information on phenotypic and genotypic variation is available, but comparable information on environmental variation within the native range of the species is lacking. Here, we compile 204 geoclimatic variables to describe the local environments of Arabidopsis accessions with known collection sites encompassing a wide geo-environmental range, and fully sequenced genomes from the 1001 Genomes Project. We identify candidate adaptive genetic variation associated with these environmental variables, and validate this approach through comparison with previous experimental studies, and by targeted confirmation of a role of the heterotrimeric G-protein γ subunit, AGG3, in cold tolerance, as newly predicted from our environmental genome wide association study (GWAS). To facilitate identification of adaptive variation, we created Arabidopsis CLIMtools : interactive web-based databases of the environment × genome associations and correlations between the local environments and 131 phenotypes compiled from previous experimental GWASs. Our study presents an extensive analysis of the local environments, landscape genomics and phenotypic variation of Arabidopsis, and illustrates how 'in silico GWAS' approaches can inform and complement experimental phenomics studies.

RAD-Seq Reveals Patterns of Additive Polygenic Variation Caused by Spatially-Varying Selection in the American Eel (Anguilla rostrata)

The American Eel (Anguilla rostrata) has an exceptional life cycle characterized by panmictic reproduction at the species scale, random dispersal, and selection in a highly heterogeneous habitat extending from subtropical to subarctic latitudes. The genetic consequences of spatially-varying selection in this species have been investigated for decades, revealing subtle clines in allele frequency at a few loci that contrast with complete panmixia on the vast majority of the genome. Because reproduction homogenizes allele frequencies every generation, sampling size, and genomic coverage are critical to reach sufficient power to detect selected loci in this context. Here, we used a total of 710 individuals from 12 sites and 12,098 high-quality single nucleotide polymorphisms to re-evaluate the extent to which local selection affects the spatial distribution of genetic diversity in this species. We used environmental association methods to identify markers under spatially-varying selection, which indicated that selection affects ∼1.5% of the genome. We then evaluated the extent to which candidate markers collectively vary with environmental factors using additive polygenic scores. We found significant correlations between polygenic scores and latitude, longitude and temperature which are consistent with polygenic selection acting against maladapted genotypes in different habitats occupied by eels throughout their range of distribution. Gene functions associated with outlier markers were significantly enriched for the insulin signaling pathway, indicating that the trade-offs inherent to occupying such a large distribution range involve the regulation of metabolism. Overall, this study highlights the potential of the additive polygenic scores approach in detecting selective effects in a complex environment.

Modularity of genes involved in local adaptation to climate despite physical linkage

BACKGROUND

Linkage among genes experiencing different selection pressures can make natural selection less efficient. Theory predicts that when local adaptation is driven by complex and non-covarying stresses, increased linkage is favored for alleles with similar pleiotropic effects, with increased recombination favored among alleles with contrasting pleiotropic effects. Here, we introduce a framework to test these predictions with a co-association network analysis, which clusters loci based on differing associations. We use this framework to study the genetic architecture of local adaptation to climate in lodgepole pine, Pinus contorta, based on associations with environments.

RESULTS

We identify many clusters of candidate genes and SNPs associated with distinct environments, including aspects of aridity and freezing, and discover low recombination rates among some candidate genes in different clusters. Only a few genes contain SNPs with effects on more than one distinct aspect of climate. There is limited correspondence between co-association networks and gene regulatory networks. We further show how associations with environmental principal components can lead to misinterpretation. Finally, simulations illustrate both benefits and caveats of co-association networks.

CONCLUSIONS

Our results support the prediction that different selection pressures favor the evolution of distinct groups of genes, each associating with a different aspect of climate. But our results went against the prediction that loci experiencing different sources of selection would have high recombination among them. These results give new insight into evolutionary debates about the extent of modularity, pleiotropy, and linkage in the evolution of genetic architectures.

Genomic signatures of environmental selection despite near-panmixia in summer flounder

Rapid environmental change is altering the selective pressures experienced by marine species. While adaptation to local environmental conditions depends on a balance between dispersal and natural selection across the seascape, the spatial scale of adaptation and the relative importance of mechanisms maintaining adaptation in the ocean are not well understood. Here, using population assignment tests, Approximate Bayesian Computation (ABC), and genome scans with double-digest restriction-site associated DNA sequencing data, we evaluated population structure and locus-environment associations in a commercially important species, summer flounder (Paralichthys dentatus), along the U.S. east coast. Based on 1,137 single nucleotide polymorphisms across 232 individuals spanning nearly 1,900 km, we found no indication of population structure across Cape Hatteras, North Carolina (F ST = 0.0014) or of isolation by distance along the coast using individual relatedness. ABC estimated the probability of dispersal across the biogeographic break at Cape Hatteras to be high (95% credible interval: 7%-50% migration). However, we found 15 loci whose allele frequencies were associated with at least one of four environmental variables. Of those, 11 were correlated with bottom temperature. For summer flounder, our results suggest continued fisheries management as a single population and identify likely response mechanisms to climate change. Broadly speaking, our findings suggest that spatial balancing selection can manifest in adaptive divergence on regional scales in marine fish despite high dispersal, and that these conditions likely result in the widespread distribution of adaptive alleles and a high potential for future genetic adaptation in response to changing environmental conditions. In the context of a rapidly changing world, a landscape genomics perspective offers a useful approach for understanding the causes and consequences of genetic differentiation.

Inferring selection in instances of long-range colonization: The Aleppo pine (Pinus halepensis) in the Mediterranean Basin

Teasing apart the effects of natural selection and demography on current allele frequencies is challenging, due to both processes leaving a similar molecular footprint. In particular, when attempting to identify selection in species that have undergone a recent range expansion, the increase in genetic drift at the edges of range expansions ("allele surfing") can be a confounding factor. To address this potential issue, we first assess the long-range colonization history of the Aleppo pine across the Mediterranean Basin, using molecular markers. We then look for single nucleotide polymorphisms (SNPs) involved in local adaptation using: (a) environmental correlation methods (bayenv2), focusing on bioclimatic variables important for the species' adaptation (i.e., temperature, precipitation and water availability); and (b) FST -related methods (pcadapt). To assess the rate of false positives caused by the allele surfing effect, these results are compared with results from simulated SNP data that mimics the species' past range expansions and the effect of genetic drift, but with no selection. We find that the Aleppo pine shows a previously unsuspected complex genetic structure across its range, as well as evidence of selection acting on SNPs involved with the response to bioclimatic variables such as drought. This study uses an original approach to disentangle the confounding effects of drift and selection in range margin populations. It also contributes to the increased evidence that plant populations are able to adapt to new environments despite the expected accumulation of deleterious mutations that takes place during long-range colonizations.

Improved VCF normalization for accurate VCF comparison

Motivation

The Variant Call Format (VCF) is widely used to store data about genetic variation. Variant calling workflows detect potential variants in large numbers of short sequence reads generated by DNA sequencing and report them in VCF format. To evaluate the accuracy of variant callers, it is critical to correctly compare their output against a reference VCF file containing a gold standard set of variants. However, comparing VCF files is a complicated task as an individual genomic variant can be represented in several different ways and is therefore not necessarily reported in a unique way by different software.

Results

We introduce a VCF normalization method called Best Alignment Normalisation (BAN) that results in more accurate VCF file comparison. BAN applies all the variations in a VCF file to the reference genome to create a sample genome, and then recalls the variants by aligning this sample genome back with the reference genome. Since the purpose of BAN is to get an accurate result at the time of VCF comparison, we define a better normalization method as the one resulting in less disagreement between the outputs of different VCF comparators.

Availability and Implementation

The BAN Linux bash script along with required software are publicly available on https://sites.google.com/site/banadf16.

Contact

A.Bayat@unsw.edu.au.

Supplementary information

Supplementary data are available at Bioinformatics online.

Local Adaptation of Sun-Exposure-Dependent Gene Expression Regulation in Human Skin

Sun-exposure is a key environmental variable in the study of human evolution. Several skin-pigmentation genes serve as classical examples of positive selection, suggesting that sun-exposure has significantly shaped worldwide genomic variation. Here we investigate the interaction between genetic variation and sun-exposure, and how this impacts gene expression regulation. Using RNA-Seq data from 607 human skin samples, we identified thousands of transcripts that are differentially expressed between sun-exposed skin and non-sun-exposed skin. We then tested whether genetic variants may influence each individual’s gene expression response to sun-exposure. Our analysis revealed 10 sun-exposure-dependent gene expression quantitative trait loci (se-eQTLs), including genes involved in skin pigmentation (SLC45A2) and epidermal differentiation (RASSF9). The allele frequencies of the RASSF9 se-eQTL across diverse populations correlate with the magnitude of solar radiation experienced by these populations, suggesting local adaptation to varying levels of sunlight. These results provide the first examples of sun-exposure-dependent regulatory variation and suggest that this variation has contributed to recent human adaptation.

Varying levels of sun-exposure across the world have significantly shaped human evolution. Previous analyses have found several skin pigmentation genes with evidence of strong evolutionary pressures throughout human history, manifesting as large differences in the frequency of genomic variants across populations. But even within populations, individuals respond differently to sun-exposure, suggesting variation in addition to the major differences in skin pigmentation across populations. Here we investigated whether genetic variants associate with response to sun-exposure within Europeans. To measure the response we analyzed gene expression in sun-exposed and non-sun-exposed skin, and identified ten genetic variants that associated with the sun-exposure response of nearby genes. One of these genetic variants, which associated with the sun-exposure response of the gene RASSF9, showed evidence of adaptation in humans in response to solar radiation. Together this evidence suggests that the regulation of gene expression is influenced by sun-exposure and that the sun-exposure dependent effect on RASSF9 expression may have had an effect on human fitness. To our knowledge, this is the first example of an environment-dependent regulatory variant with evidence of adaptation in humans.

Worldwide genetic and cultural change in human evolution

Both genetic variation and certain culturally transmitted phenotypes show geographic signatures of human demographic history. As a result of the human cultural predisposition to migrate to new areas, humans have adapted to a large number of different environments. Migration to new environments alters genetic selection pressures, and comparative genetic studies have pinpointed numerous likely targets of this selection. However, humans also exhibit many cultural adaptations to new environments, such as practices related to clothing, shelter, and food. Human culture interacts with genes and the environment in complex ways, and studying genes and culture together can deepen our understanding of human evolution.

Population genetic evidence for cold adaptation in European Drosophila melanogaster populations

We studied Drosophila melanogaster populations from Europe (the Netherlands and France) and Africa (Rwanda and Zambia) to uncover genetic evidence of adaptation to cold. We present here four lines of evidence for genes involved in cold adaptation from four perspectives: (i) the frequency of SNPs at genes previously known to be associated with chill-coma recovery time (CCRT), startle reflex (SR) and resistance to starvation stress (RSS) vary along environmental gradients and therefore among populations; (ii) SNPs of genes that correlate significantly with latitude and altitude in African and European populations overlap with SNPs that correlate with a latitudinal cline from North America; (iii) at the genomewide level, the top candidate genes are enriched in gene ontology (GO) terms that are related to cold tolerance; (iv) GO enriched terms from North American clinal genes overlap significantly with those from Africa and Europe. Each SNP was tested in 10 independent runs of Bayenv2, using the median Bayes factors to ascertain candidate genes. None of the candidate genes were found close to the breakpoints of cosmopolitan inversions, and only four candidate genes were linked to QTLs related to CCRT. To overcome the limitation that we used only four populations to test correlations with environmental gradients, we performed simulations to estimate the power of our approach for detecting selection. Based on our results, we propose a novel network of genes that is involved in cold adaptation.

Genetic subdivision and candidate genes under selection in North American grey wolves

Previous genetic studies of the highly mobile grey wolf (Canis lupus) found population structure that coincides with habitat and phenotype differences. We hypothesized that these ecologically distinct populations (ecotypes) should exhibit signatures of selection in genes related to morphology, coat colour and metabolism. To test these predictions, we quantified population structure related to habitat using a genotyping array to assess variation in 42 036 single-nucleotide polymorphisms (SNPs) in 111 North American grey wolves. Using these SNP data and individual-level measurements of 12 environmental variables, we identified six ecotypes: West Forest, Boreal Forest, Arctic, High Arctic, British Columbia and Atlantic Forest. Next, we explored signals of selection across these wolf ecotypes through the use of three complementary methods to detect selection: FST /haplotype homozygosity bivariate percentilae, bayescan, and environmentally correlated directional selection with bayenv. Across all methods, we found consistent signals of selection on genes related to morphology, coat coloration, metabolism, as predicted, as well as vision and hearing. In several high-ranking candidate genes, including LEPR, TYR and SLC14A2, we found variation in allele frequencies that follow environmental changes in temperature and precipitation, a result that is consistent with local adaptation rather than genetic drift. Our findings show that local adaptation can occur despite gene flow in a highly mobile species and can be detected through a moderately dense genomic scan. These patterns of local adaptation revealed by SNP genotyping likely reflect high fidelity to natal habitats of dispersing wolves, strong ecological divergence among habitats, and moderate levels of linkage in the wolf genome.

Landscape genomics reveal signatures of local adaptation in barley (Hordeum vulgare L.)

Land plants are sessile organisms that cannot escape the adverse climatic conditions of a given environment. Hence, adaptation is one of the solutions to surviving in a challenging environment. This study was aimed at detecting adaptive loci in barley landraces that are affected by selection. To that end, a diverse population of barley landraces was analyzed using the genotyping by sequencing approach. Climatic data for altitude, rainfall and temperature were collected from 61 weather sites near the origin of selected landraces across Ethiopia. Population structure analysis revealed three groups whereas spatial analysis accounted significant similarities at shorter geographic distances (< 40 Km) among barley landraces. Partitioning the variance between climate variables and geographic distances indicated that climate variables accounted for most of the explainable genetic variation. Markers by climatic variables association analysis resulted in altogether 18 and 62 putative adaptive loci using Bayenv and latent factor mixed model (LFMM), respectively. Subsequent analysis of the associated SNPs revealed putative candidate genes for plant adaptation. This study highlights the presence of putative adaptive loci among barley landraces representing original gene pool of the farming communities.

The role of climate and out-of-Africa migration in the frequencies of risk alleles for 21 human diseases

BACKGROUND

Demography and environmental adaptation can affect the global distribution of genetic variants and possibly the distribution of disease. Population heterozygosity of single nucleotide polymorphisms has been shown to decrease strongly with distance from Africa and this has been attributed to the effect of serial founding events during the migration of humans out of Africa. Additionally, population allele frequencies have been shown to change due to environmental adaptation. Here, we investigate the relationship of Out-of-Africa migration and climatic variables to the distribution of risk alleles for 21 diseases.

RESULTS

For each disease, we computed the regression of average heterozygosity and average allele frequency of the risk alleles with distance from Africa and 9 environmental variables. We compared these regressions to a null distribution created by regressing statistics for SNPs not associated with disease on distance from Africa and these environmental variables. Additionally, we used Bayenv 2.0 to assess the signal of environmental adaptation associated with individual risk SNPs. For those SNPs in HGDP and HapMap that are risk alleles for type 2 diabetes, we cannot reject that their distribution is as expected from Out-of-Africa migration. However, the allelic statistics for many other diseases correlate more closely with environmental variables than would be expected from the serial founder effect and show signals of environmental adaptation. We report strong environmental interactions with several autoimmune diseases, and note a particularly strong interaction between asthma and summer humidity. Additionally, we identified several risk genes with strong environmental associations.

CONCLUSIONS

For most diseases, migration does not explain the distribution of risk alleles and the worldwide pattern of allele frequencies for some diseases may be better explained by environmental associations, which suggests that some selection has acted on these diseases.

Detecting adaptive evolution based on association with ecological gradients: orientation matters!

Population genetic signatures of local adaptation are frequently investigated by identifying loci with allele frequencies that exhibit high correlation with ecological variables. One difficulty with this approach is that ecological associations might be confounded by geographic variation at selectively neutral loci. Here, we consider populations that underwent spatial expansion from their original range, and for which geographical variation of adaptive allele frequency coincides with habitat gradients. Using range expansion simulations, we asked whether our ability to detect genomic regions involved in adaptation could be impacted by the orientation of the ecological gradients. For three ecological association methods tested, we found, counter-intuitively, fewer false-positive associations when ecological gradients aligned along the main axis of expansion than when they aligned along any other direction. This result has important consequences for the analysis of genomic data under non-equilibrium population genetic models. Alignment of gradients with expansion axes is likely to be common in scenarios in which expanding species track their ecological niche during climate change while adapting to changing environments at their rear edge.

Adaptation to Low Salinity Promotes Genomic Divergence in Atlantic Cod (Gadus morhua L.)

How genomic selection enables species to adapt to divergent environments is a fundamental question in ecology and evolution. We investigated the genomic signatures of local adaptation in Atlantic cod (Gadus morhua L.) along a natural salinity gradient, ranging from 35‰ in the North Sea to 7‰ within the Baltic Sea. By utilizing a 12 K SNPchip, we simultaneously assessed neutral and adaptive genetic divergence across the Atlantic cod genome. Combining outlier analyses with a landscape genomic approach, we identified a set of directionally selected loci that are strongly correlated with habitat differences in salinity, oxygen, and temperature. Our results show that discrete regions within the Atlantic cod genome are subject to directional selection and associated with adaptation to the local environmental conditions in the Baltic- and the North Sea, indicating divergence hitchhiking and the presence of genomic islands of divergence. We report a suite of outlier single nucleotide polymorphisms within or closely located to genes associated with osmoregulation, as well as genes known to play important roles in the hydration and development of oocytes. These genes are likely to have key functions within a general osmoregulatory framework and are important for the survival of eggs and larvae, contributing to the buildup of reproductive isolation between the low-salinity adapted Baltic cod and the adjacent cod populations. Hence, our data suggest that adaptive responses to the environmental conditions in the Baltic Sea may contribute to a strong and effective reproductive barrier, and that Baltic cod can be viewed as an example of ongoing speciation.

Ecotypes of an ecologically dominant prairie grass (Andropogon gerardii) exhibit genetic divergence across the U.S. Midwest grasslands' environmental gradient

Big bluestem (Andropogon gerardii) is an ecologically dominant grass with wide distribution across the environmental gradient of U.S. Midwest grasslands. This system offers an ideal natural laboratory to study population divergence and adaptation in spatially varying climates. Objectives were to: (i) characterize neutral genetic diversity and structure within and among three regional ecotypes derived from 11 prairies across the U.S. Midwest environmental gradient, (ii) distinguish between the relative roles of isolation by distance (IBD) vs. isolation by environment (IBE) on ecotype divergence, (iii) identify outlier loci under selection and (iv) assess the association between outlier loci and climate. Using two primer sets, we genotyped 378 plants at 384 polymorphic AFLP loci across regional ecotypes from central and eastern Kansas and Illinois. Neighbour-joining tree and PCoA revealed strong genetic differentiation between Kansas and Illinois ecotypes, which was better explained by IBE than IBD. We found high genetic variability within prairies (80%) and even fragmented Illinois prairies, surprisingly, contained high within-prairie genetic diversity (92%). Using Bayenv2, 14 top-ranked outlier loci among ecotypes were associated with temperature and precipitation variables. Six of seven BayeScanFST outliers were in common with Bayenv2 outliers. High genetic diversity may enable big bluestem populations to better withstand changing climates; however, population divergence supports the use of local ecotypes in grassland restoration. Knowledge of genetic variation in this ecological dominant and other grassland species will be critical to understanding grassland response and restoration challenges in the face of a changing climate.