Recent selective sweeps in North American Drosophila melanogaster show signatures of soft sweeps

Ancient RNA virus epidemics through the lens of recent adaptation in human genomes

Over the course of the last several million years of evolution, humans probably have been plagued by hundreds or perhaps thousands of epidemics. Little is known about such ancient epidemics and a deep evolutionary perspective on current pathogenic threats is lacking. The study of past epidemics has typically been limited in temporal scope to recorded history, and in physical scope to pathogens that left sufficient DNA behind, such as Yersinia pestis during the Great Plague. Host genomes, however, offer an indirect way to detect ancient epidemics beyond the current temporal and physical limits. Arms races with pathogens have shaped the genomes of the hosts by driving a large number of adaptations at many genes, and these signals can be used to detect and further characterize ancient epidemics. Here, we detect the genomic footprints left by ancient viral epidemics that took place in the past approximately 50 000 years in the 26 human populations represented in the 1000 Genomes Project. By using the enrichment in signals of adaptation at approximately 4500 host loci that interact with specific types of viruses, we provide evidence that RNA viruses have driven a particularly large number of adaptive events across diverse human populations. These results suggest that different types of viruses may have exerted different selective pressures during human evolution. Knowledge of these past selective pressures will provide a deeper evolutionary perspective on current pathogenic threats.

This article is part of the theme issue ‘Insights into health and disease from ancient biomolecules’.

Background Selection Does Not Mimic the Patterns of Genetic Diversity Produced by Selective Sweeps

It is increasingly evident that natural selection plays a prominent role in shaping patterns of diversity across the genome. The most commonly studied modes of natural selection are positive selection and negative selection, which refer to directional selection for and against derived mutations, respectively. Positive selection can result in hitchhiking events, in which a beneficial allele rapidly replaces all others in the population, creating a valley of diversity around the selected site along with characteristic skews in allele frequencies and linkage disequilibrium among linked neutral polymorphisms. Similarly, negative selection reduces variation not only at selected sites but also at linked sites, a phenomenon called background selection (BGS). Thus, discriminating between these two forces may be difficult, and one might expect efforts to detect hitchhiking to produce an excess of false positives in regions affected by BGS. Here, we examine the similarity between BGS and hitchhiking models via simulation. First, we show that BGS may somewhat resemble hitchhiking in simplistic scenarios in which a region constrained by negative selection is flanked by large stretches of unconstrained sites, echoing previous results. However, this scenario does not mirror the actual spatial arrangement of selected sites across the genome. By performing forward simulations under more realistic scenarios of BGS, modeling the locations of protein-coding and conserved noncoding DNA in real genomes, we show that the spatial patterns of variation produced by BGS rarely mimic those of hitchhiking events. Indeed, BGS is not substantially more likely than neutrality to produce false signatures of hitchhiking. This holds for simulations modeled after both humans and Drosophila, and for several different demographic histories. These results demonstrate that appropriately designed scans for hitchhiking need not consider BGS's impact on false-positive rates. However, we do find evidence that BGS increases the false-negative rate for hitchhiking, an observation that demands further investigation.

Evolution of the Insecticide Target Rdl in African Anopheles Is Driven by Interspecific and Interkaryotypic Introgression

The evolution of insecticide resistance mechanisms in natural populations of Anopheles malaria vectors is a major public health concern across Africa. Using genome sequence data, we study the evolution of resistance mutations in the resistance to dieldrin locus (Rdl), a GABA receptor targeted by several insecticides, but most notably by the long-discontinued cyclodiene, dieldrin. The two Rdl resistance mutations (296G and 296S) spread across West and Central African Anopheles via two independent hard selective sweeps that included likely compensatory nearby mutations, and were followed by a rare combination of introgression across species (from A. gambiae and A. arabiensis to A. coluzzii) and across nonconcordant karyotypes of the 2La chromosomal inversion. Rdl resistance evolved in the 1950s as the first known adaptation to a large-scale insecticide-based intervention, but the evolutionary lessons from this system highlight contemporary and future dangers for management strategies designed to combat development of resistance in malaria vectors.

Signatures of selection reveal candidate genes involved in economic traits and cold acclimation in five Swedish cattle breeds

Background

Thousands of years of natural and artificial selection have resulted in indigenous cattle breeds that are well-adapted to the environmental challenges of their local habitat and thereby are considered as valuable genetic resources. Understanding the genetic background of such adaptation processes can help us design effective breeding objectives to preserve local breeds and improve commercial cattle. To identify regions under putative selection, GGP HD 150 K single nucleotide polymorphism (SNP) arrays were used to genotype 106 individuals representing five Swedish breeds i.e. native to different regions and covering areas with a subarctic cold climate in the north and mountainous west, to those with a continental climate in the more densely populated south regions.

Results

Five statistics were incorporated within a framework, known as de-correlated composite of multiple signals (DCMS) to detect signatures of selection. The obtained p-values were adjusted for multiple testing (FDR < 5%), and significant genomic regions were identified. Annotation of genes in these regions revealed various verified and novel candidate genes that are associated with a diverse range of traits, including e.g. high altitude adaptation and response to hypoxia (DCAF8, PPP1R12A, SLC16A3, UCP2, UCP3, TIGAR), cold acclimation (AQP3, AQP7, HSPB8), body size and stature (PLAG1, KCNA6, NDUFA9, AKAP3, C5H12orf4, RAD51AP1, FGF6, TIGAR, CCND2, CSMD3), resistance to disease and bacterial infection (CHI3L2, GBP6, PPFIBP1, REP15, CYP4F2, TIGD2, PYURF, SLC10A2, FCHSD2, ARHGEF17, RELT, PRDM2, KDM5B), reproduction (PPP1R12A, ZFP36L2, CSPP1), milk yield and components (NPC1L1, NUDCD3, ACSS1, FCHSD2), growth and feed efficiency (TMEM68, TGS1, LYN, XKR4, FOXA2, GBP2, GBP5, FGD6), and polled phenotype (URB1, EVA1C).

Conclusions

We identified genomic regions that may provide background knowledge to understand the mechanisms that are involved in economic traits and adaptation to cold climate in cattle. Incorporating p-values of different statistics in a single DCMS framework may help select and prioritize candidate genes for further analyses.

Sequencing era methods for identifying signatures of selection in the genome

Insights into genetic loci which are under selection and their functional roles contribute to increased understanding of the patterns of phenotypic variation we observe today. The availability of whole-genome sequence data, for humans and other species, provides opportunities to investigate adaptation and evolution at unprecedented resolution. Many analytical methods have been developed to interrogate these large data sets and characterize signatures of selection in the genome. We review here recently developed methods and consider the impact of increased computing power and data availability on the detection of selection signatures. Consideration of demography, recombination and other confounding factors is important, and use of a range of methods in combination is a powerful route to resolving different forms of selection in genome sequence data. Overall, a substantial improvement in methods for application to whole-genome sequencing is evident, although further work is required to develop robust and computationally efficient approaches which may increase reproducibility across studies.

Host-parasite co-evolution and its genomic signature

Studies in diverse biological systems have indicated that host-parasite co-evolution is responsible for the extraordinary genetic diversity seen in some genomic regions, such as major histocompatibility (MHC) genes in jawed vertebrates and resistance genes in plants. This diversity is believed to evolve under balancing selection on hosts by parasites. However, the mechanisms that link the genomic signatures in these regions to the underlying co-evolutionary process are only slowly emerging. We still lack a clear picture of the co-evolutionary concepts and of the genetic basis of the co-evolving phenotypic traits in the interacting antagonists. Emerging genomic tools that provide new options for identifying underlying genes will contribute to a fuller understanding of the co-evolutionary process.

Population genetics of the coral Acropora millepora: Toward genomic prediction of bleaching

Although reef-building corals are declining worldwide, responses to bleaching vary within and across species and are partly heritable. Toward predicting bleaching response from genomic data, we generated a chromosome-scale genome assembly for the coral Acropora millepora We obtained whole-genome sequences for 237 phenotyped samples collected at 12 reefs along the Great Barrier Reef, among which we inferred little population structure. Scanning the genome for evidence of local adaptation, we detected signatures of long-term balancing selection in the heat-shock co-chaperone sacsin We conducted a genome-wide association study of visual bleaching score for 213 samples, incorporating the polygenic score derived from it into a predictive model for bleaching in the wild. These results set the stage for genomics-based approaches in conservation strategies.

Genomic, Transcriptomic and Epigenomic Tools to Study the Domestication of Plants and Animals: A Field Guide for Beginners

In the last decade, genomics and the related fields of transcriptomics and epigenomics have revolutionized the study of the domestication process in plants and animals, leading to new discoveries and new unresolved questions. Given that some domesticated taxa have been more studied than others, the extent of genomic data can range from vast to nonexistent, depending on the domesticated taxon of interest. This review is meant as a rough guide for students and academics that want to start a domestication research project using modern genomic tools, as well as for researchers already conducting domestication studies that are interested in following a genomic approach and looking for alternate strategies (cheaper or more efficient) and future directions. We summarize the theoretical and technical background needed to carry out domestication genomics, starting from the acquisition of a reference genome and genome assembly, to the sampling design for population genomics, paleogenomics, transcriptomics, epigenomics and experimental validation of domestication-related genes. We also describe some examples of the aforementioned approaches and the relevant discoveries they made to understand the domestication of the studied taxa.

Evolutionary History of the Risk of SNPs for Diffuse-Type Gastric Cancer in the Japanese Population

A genome wide association study reported that the T allele of rs2294008 in a cancer-related gene, PSCA, is a risk allele for diffuse-type gastric cancer. This allele has the highest frequency (0.63) in Japanese in Tokyo (JPT) among 26 populations in the 1000 Genomes Project database. F_ST ≈ 0.26 at this single nucleotide polymorphism is one of the highest between JPT and the genetically close Han Chinese in Beijing (CHB). To understand the evolutionary history of the alleles in PSCA, we addressed: (i) whether the C non-risk allele at rs2294008 is under positive selection, and (ii) why the mainland Japanese population has a higher T allele frequency than other populations. We found that haplotypes harboring the C allele are composed of two subhaplotypes. We detected that positive selection on both subhaplotypes has occurred in the East Asian lineage. However, the selection on one of the subhaplotypes in JPT seems to have been relaxed or ceased after divergence from the continental population; this may have caused the elevation of T allele frequency. Based on simulations under the dual structure model (a specific demography for the Japanese) and phylogenetic analysis with ancient DNA, the T allele at rs2294008 might have had high frequency in the Jomon people (one of the ancestral populations of the modern Japanese); this may explain the high T allele frequency in the extant Japanese.

A community-maintained standard library of population genetic models

The explosion in population genomic data demands ever more complex modes of analysis, and increasingly, these analyses depend on sophisticated simulations. Recent advances in population genetic simulation have made it possible to simulate large and complex models, but specifying such models for a particular simulation engine remains a difficult and error-prone task. Computational genetics researchers currently re-implement simulation models independently, leading to inconsistency and duplication of effort. This situation presents a major barrier to empirical researchers seeking to use simulations for power analyses of upcoming studies or sanity checks on existing genomic data. Population genetics, as a field, also lacks standard benchmarks by which new tools for inference might be measured. Here, we describe a new resource, stdpopsim, that attempts to rectify this situation. Stdpopsim is a community-driven open source project, which provides easy access to a growing catalog of published simulation models from a range of organisms and supports multiple simulation engine backends. This resource is available as a well-documented python library with a simple command-line interface. We share some examples demonstrating how stdpopsim can be used to systematically compare demographic inference methods, and we encourage a broader community of developers to contribute to this growing resource.

Genome Diversity and the Origin of the Arabian Horse

The Arabian horse, one of the world’s oldest breeds of any domesticated animal, is characterized by natural beauty, graceful movement, athletic endurance, and, as a result of its development in the arid Middle East, the ability to thrive in a hot, dry environment. Here we studied 378 Arabian horses from 12 countries using equine single nucleotide polymorphism (SNP) arrays and whole-genome re-sequencing to examine hypotheses about genomic diversity, population structure, and the relationship of the Arabian to other horse breeds. We identified a high degree of genetic variation and complex ancestry in Arabian horses from the Middle East region. Also, contrary to popular belief, we could detect no significant genomic contribution of the Arabian breed to the Thoroughbred racehorse, including Y chromosome ancestry. However, we found strong evidence for recent interbreeding of Thoroughbreds with Arabians used for flat-racing competitions. Genetic signatures suggestive of selective sweeps across the Arabian breed contain candidate genes for combating oxidative damage during exercise, and within the “Straight Egyptian” subgroup, for facial morphology. Overall, our data support an origin of the Arabian horse in the Middle East, no evidence for reduced global genetic diversity across the breed, and unique genetic adaptations for both physiology and conformation.

Space is the Place: Effects of Continuous Spatial Structure on Analysis of Population Genetic Data

Real geography is continuous, but standard models in population genetics are based on discrete, well-mixed populations. As a result, many methods of analyzing genetic data assume that samples are a random draw from a well-mixed population, but are applied to clustered samples from populations that are structured clinally over space. Here, we use simulations of populations living in continuous geography to study the impacts of dispersal and sampling strategy on population genetic summary statistics, demographic inference, and genome-wide association studies (GWAS). We find that most common summary statistics have distributions that differ substantially from those seen in well-mixed populations, especially when Wright's neighborhood size is < 100 and sampling is spatially clustered. "Stepping-stone" models reproduce some of these effects, but discretizing the landscape introduces artifacts that in some cases are exacerbated at higher resolutions. The combination of low dispersal and clustered sampling causes demographic inference from the site frequency spectrum to infer more turbulent demographic histories, but averaged results across multiple simulations revealed surprisingly little systematic bias. We also show that the combination of spatially autocorrelated environments and limited dispersal causes GWAS to identify spurious signals of genetic association with purely environmentally determined phenotypes, and that this bias is only partially corrected by regressing out principal components of ancestry. Last, we discuss the relevance of our simulation results for inference from genetic variation in real organisms.

Identifying and Classifying Shared Selective Sweeps from Multilocus Data

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

Genetic Diversity of Persian Arabian Horses and Their Relationship to Other Native Iranian Horse Breeds

The principal aims of this study were to explore genetic diversity and genome-wide selection signatures in Persian Arabian horses and to determine genetic relationship of Persian Arabians with other Iranian horse breeds. We evaluated 71 horses from 8 matrilineal strains tracing to 47 mares from the mid to late 19th century, using the equine 670k single nucleotide polymorphism (SNP) BeadChip. Mean observed and expected heterozygosity were (0.43) and (0.45), respectively, average inbreeding measures (inbreeding estimates based on runs of homozygosity and pedigree information) were low, indicating high genetic diversity in Persian Arabian horses. Analysis of population genetic structure using STRUCTURE and principal component analysis suggested that Persian Arabian horses can be divided into 3 groups, however the groups do not match traditional matrilineal strains. In total, 15 genomic regions were identified by at least 2 of the 3 implemented methods, Tajima's D, H, and H12, as potentially under selection in Persian Arabian horses. Most of these peaks were found on chromosome 9, overlapping with QTLs previously associated with horse temperament. Biological function analysis of identified candidate genes highlighted enrichment of GO term "response to lipopolysaccharide" and KEGG pathway "chemokine-mediated signaling pathway," which are associated with immune responses and may have been targets of selection in Persian Arabian horses. Independent analyses of SNP data from 30 horses of 4 other Iranian breeds suggested distinct population structure between Persian Arabian, and Turkemen and Caspian horse breeds. Overall, the results of this study suggest a rich genetic diversity in the Persian Arabian horses and a clear genetic differentiation with Turkemen and Caspian breeds.

Bioinformatic Detection of Positive Selection Pressure in Plant Pathogens: The Neutral Theory of Molecular Sequence Evolution in Action

The genomes of plant pathogenic fungi and oomycetes are often exposed to strong positive selection pressure. During speciation, shifts in host range and preference can lead to major adaptive changes. Furthermore, evolution of total host resistance to most isolates can force rapid evolutionary changes in host-specific pathogens. Crop pathogens are subjected to particularly intense selective pressures from monocultures and fungicides. Detection of the footprints of positive selection in plant pathogen genomes is a worthwhile endeavor as it aids understanding of the fundamental biology of these important organisms. There are two main classes of test for detection of positively selected alleles. Tests based on the ratio of non-synonymous to synonymous substitutions per site detect the footprints of multiple fixation events between divergent lineages. Thus, they are well-suited to the study of ancient adaptation events spanning speciations. On the other hand, tests that scan genomes for local fluctuations in allelic diversity within populations are suitable for detection of recent positive selection in populations. In this review, I briefly describe some of the more widely used tests of positive selection and the theory underlying them. I then discuss various examples of their application to plant pathogen genomes, emphasizing the types of genes that are associated with signatures of positive selection. I conclude with a discussion of the practicality of such tests for identification of pathogen genes of interest and the important features of pathogen ecology that must be taken into account for accurate interpretation.

Young JP, Andersen SU. Symbiosis genes show a unique pattern of introgression and selection within a Rhizobium leguminosarum species complex

Rhizobia supply legumes with fixed nitrogen using a set of symbiosis genes. These can cross rhizobium species boundaries, but it is unclear how many other genes show similar mobility. Here, we investigate inter-species introgression using de novo assembly of 196 Rhizobium leguminosarum sv. trifolii genomes. The 196 strains constituted a five-species complex, and we calculated introgression scores based on gene-tree traversal to identify 171 genes that frequently cross species boundaries. Rather than relying on the gene order of a single reference strain, we clustered the introgressing genes into four blocks based on population structure-corrected linkage disequilibrium patterns. The two largest blocks comprised 125 genes and included the symbiosis genes, a smaller block contained 43 mainly chromosomal genes, and the last block consisted of three genes with variable genomic location. All introgression events were likely mediated by conjugation, but only the genes in the symbiosis linkage blocks displayed overrepresentation of distinct, high-frequency haplotypes. The three genes in the last block were core genes essential for symbiosis that had, in some cases, been mobilized on symbiosis plasmids. Inter-species introgression is thus not limited to symbiosis genes and plasmids, but other cases are infrequent and show distinct selection signatures.

From Summary Statistics to Gene Trees: Methods for Inferring Positive Selection

Methods to detect signals of natural selection from genomic data have traditionally emphasized the use of simple summary statistics. Here, we review a new generation of methods that consider combinations of conventional summary statistics and/or richer features derived from inferred gene trees and ancestral recombination graphs (ARGs). We also review recent advances in methods for population genetic simulation and ARG reconstruction. Finally, we describe opportunities for future work on a variety of related topics, including the genetics of speciation, estimation of selection coefficients, and inference of selection on polygenic traits. Together, these emerging methods offer promising new directions in the study of natural selection.

Architecture of Parallel Adaptation in Ten Lacustrine Threespine Stickleback Populations from the White Sea Area

Adaptation of threespine stickleback to freshwater involves parallel recruitment of freshwater alleles in clusters of closely linked sites, or divergence islands (DIs). However, it remains unclear to what extent the DIs and the alleles that constitute them coincide between populations that underwent adaptation to freshwater independently. We examine threespine sticklebacks from ten freshwater lakes that emerged 500–1500 years ago in the White Sea basin, with the emphasis on repeatability of genomic patterns of adaptation among the lake populations and the role of local recombination rate in the distribution and structure of DIs. The 65 detected DIs are clustered in the genome, forming 12 aggregations, and this clustering cannot be explained by the variation of the recombination rate. Only 21 of the DIs are present in all the freshwater populations, likely being indispensable for successful colonization of freshwater environment by the ancestral marine population. Within most DIs, the same set of single nucleotide polymorphisms (SNPs) distinguish marine and freshwater haplotypes in all the lake populations; however, in some DIs, freshwater alleles differ between populations, suggesting that they could have been established by recruitment of different haplotypes in different populations.

Selective Sweeps Under Dominance and Inbreeding

A major research goal in evolutionary genetics is to uncover loci experiencing positive selection. One approach involves finding 'selective sweeps' patterns, which can either be 'hard sweeps' formed by de novo mutation, or 'soft sweeps' arising from recurrent mutation or existing standing variation. Existing theory generally assumes outcrossing populations, and it is unclear how dominance affects soft sweeps. We consider how arbitrary dominance and inbreeding via self-fertilization affect hard and soft sweep signatures. With increased self-fertilization, they are maintained over longer map distances due to reduced effective recombination and faster beneficial allele fixation times. Dominance can affect sweep patterns in outcrossers if the derived variant originates from either a single novel allele, or from recurrent mutation. These models highlight the challenges in distinguishing hard and soft sweeps, and propose methods to differentiate between scenarios.

Parallel and nonparallel genomic responses contribute to herbicide resistance in Ipomoea purpurea, a common agricultural weed

The repeated evolution of herbicide resistance has been cited as an example of genetic parallelism, wherein separate species or genetic lineages utilize the same genetic solution in response to selection. However, most studies that investigate the genetic basis of herbicide resistance examine the potential for changes in the protein targeted by the herbicide rather than considering genome-wide changes. We used a population genomics screen and targeted exome re-sequencing to uncover the potential genetic basis of glyphosate resistance in the common morning glory, Ipomoea purpurea, and to determine if genetic parallelism underlies the repeated evolution of resistance across replicate resistant populations. We found no evidence for changes in 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS), glyphosate's target protein, that were associated with resistance, and instead identified five genomic regions that showed evidence of selection. Within these regions, genes involved in herbicide detoxification-cytochrome P450s, ABC transporters, and glycosyltransferases-are enriched and exhibit signs of selective sweeps. One region under selection shows parallel changes across all assayed resistant populations whereas other regions exhibit signs of divergence. Thus, while it appears that the physiological mechanism of resistance in this species is likely the same among resistant populations, we find patterns of both similar and divergent selection across separate resistant populations at particular loci.

Assessing connectivity despite high diversity in island populations of a malaria mosquito

Documenting isolation is notoriously difficult for species with vast polymorphic populations. High proportions of shared variation impede estimation of connectivity, even despite leveraging information from many genetic markers. We overcome these impediments by combining classical analysis of neutral variation with assays of the structure of selected variation, demonstrated using populations of the principal African malaria vector Anopheles gambiae. Accurate estimation of mosquito migration is crucial for efforts to combat malaria. Modeling and cage experiments suggest that mosquito gene drive systems will enable malaria eradication, but establishing safety and efficacy requires identification of isolated populations in which to conduct field testing. We assess Lake Victoria islands as candidate sites, finding one island 30 km offshore is as differentiated from mainland samples as populations from across the continent. Collectively, our results suggest sufficient contemporary isolation of these islands to warrant consideration as field-testing locations and illustrate shared adaptive variation as a useful proxy for connectivity in highly polymorphic species.

Selective sweeps on novel and introgressed variation shape mimicry loci in a butterfly adaptive radiation

Natural selection leaves distinct signatures in the genome that can reveal the targets and history of adaptive evolution. By analysing high-coverage genome sequence data from 4 major colour pattern loci sampled from nearly 600 individuals in 53 populations, we show pervasive selection on wing patterns in the Heliconius adaptive radiation. The strongest signatures correspond to loci with the greatest phenotypic effects, consistent with visual selection by predators, and are found in colour patterns with geographically restricted distributions. These recent sweeps are similar between co-mimics and indicate colour pattern turn-over events despite strong stabilising selection. Using simulations, we compare sweep signatures expected under classic hard sweeps with those resulting from adaptive introgression, an important aspect of mimicry evolution in Heliconius butterflies. Simulated recipient populations show a distinct 'volcano' pattern with peaks of increased genetic diversity around the selected target, characteristic of sweeps of introgressed variation and consistent with diversity patterns found in some populations. Our genomic data reveal a surprisingly dynamic history of colour pattern selection and co-evolution in this adaptive radiation.

Life-History Evolution and the Genetics of Fitness Components in Drosophila melanogaster

Life-history traits or "fitness components"-such as age and size at maturity, fecundity and fertility, age-specific rates of survival, and life span-are the major phenotypic determinants of Darwinian fitness. Analyzing the evolution and genetics of these phenotypic targets of selection is central to our understanding of adaptation. Due to its simple and rapid life cycle, cosmopolitan distribution, ease of maintenance in the laboratory, well-understood evolutionary genetics, and its versatile genetic toolbox, the "vinegar fly" Drosophila melanogaster is one of the most powerful, experimentally tractable model systems for studying "life-history evolution." Here, I review what has been learned about the evolution and genetics of life-history variation in D. melanogaster by drawing on numerous sources spanning population and quantitative genetics, genomics, experimental evolution, evolutionary ecology, and physiology. This body of work has contributed greatly to our knowledge of several fundamental problems in evolutionary biology, including the amount and maintenance of genetic variation, the evolution of body size, clines and climate adaptation, the evolution of senescence, phenotypic plasticity, the nature of life-history trade-offs, and so forth. While major progress has been made, important facets of these and other questions remain open, and the D. melanogaster system will undoubtedly continue to deliver key insights into central issues of life-history evolution and the genetics of adaptation.

Population Genomics of Transitions to Selfing in Brassicaceae Model Systems

Many plants harbor complex mechanisms that promote outcrossing and efficient pollen transfer. These include floral adaptations as well as genetic mechanisms, such as molecular self-incompatibility (SI) systems. The maintenance of such systems over long evolutionary timescales suggests that outcrossing is favorable over a broad range of conditions. Conversely, SI has repeatedly been lost, often in association with transitions to self-fertilization (selfing). This transition is favored when the short-term advantages of selfing outweigh the costs, primarily inbreeding depression. The transition to selfing is expected to have major effects on population genetic variation and adaptive potential, as well as on genome evolution. In the Brassicaceae, many studies on the population genetic, gene regulatory, and genomic effects of selfing have centered on the model plant Arabidopsis thaliana and the crucifer genus Capsella. The accumulation of population genomics datasets have allowed detailed investigation of where, when and how the transition to selfing occurred. Future studies will take advantage of the development of population genetics theory on the impact of selfing, especially regarding positive selection. Furthermore, investigation of systems including recent transitions to selfing, mixed mating populations and/or multiple independent replicates of the same transition will facilitate dissecting the effects of mating system variation from processes driven by demography.

Polygenic Adaptation to an Environmental Shift: Temporal Dynamics of Variation Under Gaussian Stabilizing Selection and Additive Effects on a Single Trait

Predictions about the effect of natural selection on patterns of linked neutral variation are largely based on models involving the rapid fixation of unconditionally beneficial mutations. However, when phenotypes adapt to a new optimum trait value, the strength of selection on individual mutations decreases as the population adapts. Here, I use explicit forward simulations of a single trait with additive-effect mutations adapting to an "optimum shift." Detectable "hitchhiking" patterns are only apparent if (i) the optimum shifts are large with respect to equilibrium variation for the trait, (ii) mutation rates to large-effect mutations are low, and (iii) large-effect mutations rapidly increase in frequency and eventually reach fixation, which typically occurs after the population reaches the new optimum. For the parameters simulated here, partial sweeps do not appreciably affect patterns of linked variation, even when the mutations are strongly selected. The contribution of new mutations vs. standing variation to fixation depends on the mutation rate affecting trait values. Given the fixation of a strongly selected variant, patterns of hitchhiking are similar on average for the two classes of sweeps because sweeps from standing variation involving large-effect mutations are rare when the optimum shifts. The distribution of effect sizes of new mutations has little effect on the time to reach the new optimum, but reducing the mutational variance increases the magnitude of hitchhiking patterns. In general, populations reach the new optimum prior to the completion of any sweeps, and the times to fixation are longer for this model than for standard models of directional selection. The long fixation times are due to a combination of declining selection pressures during adaptation and the possibility of interference among weakly selected sites for traits with high mutation rates.

Comparative genome analyses reveal the unique genetic composition and selection signals underlying the phenotypic characteristics of three Chinese domestic goat breeds

BACKGROUND

As one of the important livestock species around the world, goats provide abundant meat, milk, and fiber to fulfill basic human needs. However, the genetic loci that underlie phenotypic variations in domestic goats are largely unknown, particularly for economically important traits. In this study, we sequenced the whole genome of 38 goats from three Chinese breeds (Chengdu Brown, Jintang Black, and Tibetan Cashmere) and downloaded the genome sequence data of 30 goats from five other breeds (four non-Chinese and one Chinese breed) and 21 Bezoar ibexes to investigate the genetic composition and selection signatures of the Chinese goat breeds after domestication.

RESULTS

Based on population structure analysis and FST values (average FST = 0.22), the genetic composition of Chengdu Brown goats differs considerably from that of Bezoar ibexes as a result of geographic isolation. Strikingly, the genes under selection that we identified in Tibetan Cashmere goats were significantly enriched in the categories hair growth and bone and nervous system development, possibly because they are involved in adaptation to high-altitude. In particular, we found a large difference in allele frequency of one novel SNP (c.-253G>A) in the 5'-UTR of FGF5 between Cashmere goats and goat breeds with short hair. The mutation at this site introduces a start codon that results in the occurrence of a premature FGF5 protein and is likely a natural causal variant that is involved in the long hair phenotype of cashmere goats. The haplotype tagged with the AGG-allele in exon 12 of DSG3, which encodes a cell adhesion molecule that is expressed mainly in the skin, was almost fixed in Tibetan Cashmere goats, whereas this locus still segregates in the lowland goat breeds. The pigmentation gene KITLG showed a strong signature of selection in Tibetan Cashmere goats. The genes ASIP and LCORL were identified as being under positive selection in Jintang Black goats.

CONCLUSIONS

After domestication, geographic isolation of some goat breeds has resulted in distinct genetic structures. Furthermore, our work highlights several positively selected genes that likely contributed to breed-related traits in domestic goats.

Population Genetics in the Human Microbiome

While the human microbiome's structure and function have been extensively studied, its within-species genetic diversity is less well understood. However, genetic mutations in the microbiome can confer biomedically relevant traits, such as the ability to extract nutrients from food, metabolize drugs, evade antibiotics, and communicate with the host immune system. The population genetic processes by which these traits evolve are complex, in part due to interacting ecological and evolutionary forces in the microbiome. Advances in metagenomic sequencing, coupled with bioinformatics tools and population genetic models, facilitate quantification of microbiome genetic variation and inferences about how this diversity arises, evolves, and correlates with traits of both microbes and hosts. In this review, we explore the population genetic forces (mutation, recombination, drift, and selection) that shape microbiome genetic diversity within and between hosts, as well as efforts towards predictive models that leverage microbiome genetics.

Adaptation in structured populations and fuzzy boundaries between hard and soft sweeps

Selective sweeps, the genetic footprint of positive selection, have been extensively studied in the past decades, with dozens of methods developed to identify swept regions. However, these methods suffer from both false positive and false negative reports, and the candidates identified with different methods are often inconsistent with each other. We propose that a biological cause of this problem can be population subdivision, and a technical cause can be incomplete, or inaccurate, modeling of the dynamic process associated with sweeps. Here we used simulations to show how these effects interact and potentially cause bias. In particular, we show that sweeps maybe misclassified as either hard or soft, when the true time stage of a sweep and that implied, or pre-supposed, by the model do not match. We call this "temporal misclassification". Similarly, "spatial misclassification (softening)" can occur when hard sweeps, which are imported by migration into a new subpopulation, are falsely identified as soft. This can easily happen in case of local adaptation, i.e. when the sweeping allele is not under positive selection in the new subpopulation, and the underlying model assumes panmixis instead of substructure. The claim that most sweeps in the evolutionary history of humans were soft, may have to be reconsidered in the light of these findings.

Selective Sweep at a QTL in a Randomly Fluctuating Environment

Adaptation is mediated by phenotypic traits that are often near continuous, and undergo selective pressures that may change with the environment. The dynamics of allelic frequencies at underlying quantitative trait loci (QTL) depend on their own phenotypic effects, but also possibly on other polymorphic loci affecting the same trait, and on environmental change driving phenotypic selection. Most environments include a substantial component of random noise, characterized both by its magnitude and its temporal autocorrelation, which sets the timescale of environmental predictability. I investigate the dynamics of a mutation affecting a quantitative trait in an autocorrelated stochastic environment that causes random fluctuations of an optimum phenotype. The trait under selection may also exhibit background polygenic variance caused by many polymorphic loci of small effects elsewhere in the genome. In addition, the mutation at the QTL may affect phenotypic plasticity, the phenotypic response of given genotype to its environment of development or expression. Stochastic environmental fluctuations increase the variance of the evolutionary process, with consequences for the probability of a complete sweep at the QTL. Background polygenic variation critically alters this process, by setting an upper limit to stochastic variance of population genetics at the QTL. For a plasticity QTL, stochastic fluctuations also influences the expected selection coefficient, and alleles with the same expected trajectory can have very different stochastic variances. Finally, a mutation may be favored through its effect on plasticity despite causing a systematic mismatch with optimum, which is compensated by evolution of the mean background phenotype.

Exome-wide association of deltamethrin resistance in Aedes aegypti from Mexico

Aedes aegypti is the major vector of a number of arboviruses that cause disease in humans. Without vaccines or pharmaceuticals, pyrethroid insecticides remain the major tool for public health protection. Pyrethroid resistance is now widespread. Replacement substitutions in the voltage-gated sodium channel (vgsc) that reduce the stability of pyrethroid binding account for most of the resistance, but metabolic mechanisms also inactivate pyrethroids. High-throughput sequencing and the A. aegypti L5 annotated physical map has allowed interrogation of the exome for genes and single-nucleotide polymorphisms associated with pyrethroid resistance. We exposed females of A. aegypti from Mexico to a deltamethrin discriminating dose to designate them as resistant (active after 1 h) or susceptible (knocked down with no recovery after 4 h). The vgsc on chromosome 3 had the highest association, followed by genes proximal to vgsc. We identified potential detoxification genes located singly (eg HPX8C) or within clusters in chromosome 2 [three esterase clusters, two of cytochrome P450 monooxygenases (CYP)] and chromosome 3 (one cluster of 16 CYP325 and seven CYP9 genes). Deltamethrin resistance in A. aegypti is associated with mutations in the vgsc gene and a large assortment of genes.

The Impact of Natural Selection on the Evolution and Function of Placentally Expressed Galectins

Immunity genes have repeatedly experienced natural selection during mammalian evolution. Galectins are carbohydrate-binding proteins that regulate diverse immune responses, including maternal-fetal immune tolerance in placental pregnancy. Seven human galectins, four conserved across vertebrates and three specific to primates, are involved in placental development. To comprehensively study the molecular evolution of these galectins, both across mammals and within humans, we conducted a series of between- and within-species evolutionary analyses. By examining patterns of sequence evolution between species, we found that primate-specific galectins showed uniformly high substitution rates, whereas two of the four other galectins experienced accelerated evolution in primates. By examining human population genomic variation, we found that galectin genes and variants, including variants previously linked to immune diseases, showed signatures of recent positive selection in specific human populations. By examining one nonsynonymous variant in Galectin-8 previously associated with autoimmune diseases, we further discovered that it is tightly linked to three other nonsynonymous variants; surprisingly, the global frequency of this four-variant haplotype is ∼50%. To begin understanding the impact of this major haplotype on Galectin-8 protein structure, we modeled its 3D protein structure and found that it differed substantially from the reference protein structure. These results suggest that placentally expressed galectins experienced both ancient and more recent selection in a lineage- and population-specific manner. Furthermore, our discovery that the major Galectin-8 haplotype is structurally distinct from and more commonly found than the reference haplotype illustrates the significance of understanding the evolutionary processes that sculpted variants associated with human genetic disease.

An approximate full-likelihood method for inferring selection and allele frequency trajectories from DNA sequence data

Most current methods for detecting natural selection from DNA sequence data are limited in that they are either based on summary statistics or a composite likelihood, and as a consequence, do not make full use of the information available in DNA sequence data. We here present a new importance sampling approach for approximating the full likelihood function for the selection coefficient. Our method CLUES treats the ancestral recombination graph (ARG) as a latent variable that is integrated out using previously published Markov Chain Monte Carlo (MCMC) methods. The method can be used for detecting selection, estimating selection coefficients, testing models of changes in the strength of selection, estimating the time of the start of a selective sweep, and for inferring the allele frequency trajectory of a selected or neutral allele. We perform extensive simulations to evaluate the method and show that it uniformly improves power to detect selection compared to current popular methods such as nSL and SDS, and can provide reliable inferences of allele frequency trajectories under many conditions. We also explore the potential of our method to detect extremely recent changes in the strength of selection. We use the method to infer the past allele frequency trajectory for a lactase persistence SNP (MCM6) in Europeans. We also infer the trajectory of a SNP (EDAR) in Han Chinese, finding evidence that this allele's age is much older than previously claimed. We also study a set of 11 pigmentation-associated variants. Several genes show evidence of strong selection particularly within the last 5,000 years, including ASIP, KITLG, and TYR. However, selection on OCA2/HERC2 seems to be much older and, in contrast to previous claims, we find no evidence of selection on TYRP1.

Signatures of Recent Positive Selection in Enhancers Across 41 Human Tissues

Evolutionary changes in enhancers are widely associated with variation in human traits and diseases. However, studies comprehensively quantifying levels of selection on enhancers at multiple evolutionary periods during recent human evolution and how enhancer evolution varies across human tissues are lacking. To address these questions, we integrated a dataset of 41,561 transcribed enhancers active in 41 different human tissues (FANTOM Consortium) with whole genome sequences of 1,668 individuals from the African, Asian, and European populations (1000 Genomes Project). Our analyses based on four different metrics (Tajima’s D, F_ST, H12, nS_L) showed that ∼5.90% of enhancers showed evidence of recent positive selection and that genes associated with enhancers under very recent positive selection are enriched for diverse immune-related functions. The distributions of these metrics for brain and testis enhancers were often statistically significantly different and in the direction suggestive of less positive selection compared to those of other tissues; the same was true for brain and testis enhancers that are tissue-specific compared to those that are tissue-broad and for testis enhancers associated with tissue-enriched and non-tissue-enriched genes. These differences varied considerably across metrics and tissues and were generally in the form of changes in distributions’ shapes rather than shifts in their values. Collectively, these results suggest that many human enhancers experienced recent positive selection throughout multiple time periods in human evolutionary history, that this selection occurred in a tissue-dependent and immune-related functional context, and that much like the evolution of their protein-coding gene counterparts, the evolution of brain and testis enhancers has been markedly different from that of enhancers in other tissues.

Genetic Variation in Human Gene Regulatory Factors Uncovers Regulatory Roles in Local Adaptation and Disease

Differences in gene regulation have been suggested to play essential roles in the evolution of phenotypic changes. Although DNA changes in cis-regulatory elements affect only the regulation of its corresponding gene, variations in gene regulatory factors (trans) can have a broader effect, because the expression of many target genes might be affected. Aiming to better understand how natural selection may have shaped the diversity of gene regulatory factors in human, we assembled a catalog of all proteins involved in controlling gene expression. We found that at least five DNA-binding transcription factor classes are enriched among genes located in candidate regions for selection, suggesting that they might be relevant for understanding regulatory mechanisms involved in human local adaptation. The class of KRAB-ZNFs, zinc-finger (ZNF) genes with a Krüppel-associated box, stands out by first, having the most genes located on candidate regions for positive selection. Second, displaying most nonsynonymous single nucleotide polymorphisms (SNPs) with high genetic differentiation between populations within these regions. Third, having 27 KRAB-ZNF gene clusters with high extended haplotype homozygosity. Our further characterization of nonsynonymous SNPs in ZNF genes located within candidate regions for selection, suggests regulatory modifications that might influence the expression of target genes at population level. Our detailed investigation of three candidate regions revealed possible explanations for how SNPs may influence the prevalence of schizophrenia, eye development, and fertility in humans, among other phenotypes. The genetic variation we characterized here may be responsible for subtle to rough regulatory changes that could be important for understanding human adaptation.

Selection at behavioural, developmental and metabolic genes is associated with the northward expansion of a successful tropical colonizer

What makes a species able to colonize novel environments? This question is key to understand the dynamics of adaptive radiations and ecological niche shifts, but the mechanisms that underlie expansion into novel habitats remain poorly understood at a genomic scale. Lizards from the genus Anolis are typically tropical, and the green anole (Anolis carolinensis) constitutes an exception since it expanded into temperate North America from subtropical Florida. Thus, we used the green anole as a model to investigate signatures of selection associated with colonization of a new environment, namely temperate North America. To this end, we analysed 29 whole-genome sequences, covering the entire native range of the species. We used a combination of recent methods to quantify both positive and balancing selection in northern populations, including F_ST outlier methods, machine learning and ancestral recombination graphs. We naively scanned for genes of interest and assessed the overlap between multiple tests. Strikingly, we identified many genes involved in behaviour, suggesting that the recent successful colonization of northern environments may have been linked to behavioural shifts as well as physiological adaptation. Using a candidate genes strategy, we determined that genes involved in response to cold or behaviour displayed more frequently signals of selection, while controlling for local recombination rate, gene clustering and gene length. In addition, we found signatures of balancing selection at immune genes in all investigated genetic groups, but also at genes involved in neuronal and anatomical development.

Understanding the Factors That Shape Patterns of Nucleotide Diversity in the House Mouse Genome

A major goal of population genetics has been to determine the extent by which selection at linked sites influences patterns of neutral nucleotide diversity in the genome. Multiple lines of evidence suggest that diversity is influenced by both positive and negative selection. For example, in many species there are troughs in diversity surrounding functional genomic elements, consistent with the action of either background selection (BGS) or selective sweeps. In this study, we investigated the causes of the diversity troughs that are observed in the wild house mouse genome. Using the unfolded site frequency spectrum, we estimated the strength and frequencies of deleterious and advantageous mutations occurring in different functional elements in the genome. We then used these estimates to parameterize forward-in-time simulations of chromosomes, using realistic distributions of functional elements and recombination rate variation in order to determine whether selection at linked sites can explain the observed patterns of nucleotide diversity. The simulations suggest that BGS alone cannot explain the dips in diversity around either exons or conserved noncoding elements. A combination of BGS and selective sweeps produces deeper dips in diversity than BGS alone, but the inferred parameters of selection cannot fully explain the patterns observed in the genome. Our results provide evidence of sweeps shaping patterns of nucleotide diversity across the mouse genome and also suggest that infrequent, strongly advantageous mutations play an important role in this. The limitations of using the unfolded site frequency spectrum for inferring the frequency and effects of advantageous mutations are discussed.

The Effect of Neutral Recombination Variation on Genome Scans for Selection

Recently, there has been an increasing interest in identifying the role that regions of low recombination or inversion play in adaptation of species to local environments. Many examples of groups of adapted genes located within inversions are arising in the literature, in part inspired by theory that predicts the evolution of these so-called “supergenes.” We still, however, have a poor understanding of how genomic heterogeneity, such as varying rates of recombination, may confound signals of selection. Here, I evaluate the effect of neutral inversions and recombination variation on genome scans for selection, including tests for selective sweeps, differentiation outlier tests, and association tests. There is considerable variation among methods in their performance, with some methods being unaffected and some showing elevated false positive signals within a neutral inversion or region of low recombination. In some cases the false positive signal can be dampened or removed, if it is possible to use a quasi-independent set of SNPs to parameterize the model before performing the test. These results will be helpful to those seeking to understand the importance of regions of low recombination in adaptation.

Genetic diversity of CHC22 clathrin impacts its function in glucose metabolism

CHC22 clathrin plays a key role in intracellular membrane traffic of the insulin-responsive glucose transporter GLUT4 in humans. We performed population genetic and phylogenetic analyses of the CHC22-encoding CLTCL1 gene, revealing independent gene loss in at least two vertebrate lineages, after arising from gene duplication. All vertebrates retained the paralogous CLTC gene encoding CHC17 clathrin, which mediates endocytosis. For vertebrates retaining CLTCL1, strong evidence for purifying selection supports CHC22 functionality. All human populations maintained two high frequency CLTCL1 allelic variants, encoding either methionine or valine at position 1316. Functional studies indicated that CHC22-V1316, which is more frequent in farming populations than in hunter-gatherers, has different cellular dynamics than M1316-CHC22 and is less effective at controlling GLUT4 membrane traffic, altering its insulin-regulated response. These analyses suggest that ancestral human dietary change influenced selection of allotypes that affect CHC22's role in metabolism and have potential to differentially influence the human insulin response.

On the Population Dynamics of Junk: A Review on the Population Genomics of Transposable Elements

Transposable elements (TEs) play an important role in shaping genomic organization and structure, and may cause dramatic changes in phenotypes. Despite the genetic load they may impose on their host and their importance in microevolutionary processes such as adaptation and speciation, the number of population genetics studies focused on TEs has been rather limited so far compared to single nucleotide polymorphisms (SNPs). Here, we review the current knowledge about the dynamics of transposable elements at recent evolutionary time scales, and discuss the mechanisms that condition their abundance and frequency. We first discuss non-adaptive mechanisms such as purifying selection and the variable rates of transposition and elimination, and then focus on positive and balancing selection, to finally conclude on the potential role of TEs in causing genomic incompatibilities and eventually speciation. We also suggest possible ways to better model TEs dynamics in a population genomics context by incorporating recent advances in TEs into the rich information provided by SNPs about the demography, selection, and intrinsic properties of genomes.

High-density genotyping reveals signatures of selection related to acclimation and economically important traits in 15 local sheep breeds from Russia

Background

Domestication and centuries of selective breeding have changed genomes of sheep breeds to respond to environmental challenges and human needs. The genomes of local breeds, therefore, are valuable sources of genomic variants to be used to understand mechanisms of response to adaptation and artificial selection. As a step toward this we performed a high-density genotyping and comprehensive scans for signatures of selection in the genomes from 15 local sheep breeds reared across Russia.

Results

Results demonstrated that the genomes of Russian sheep breeds contain multiple regions under putative selection. More than 50% of these regions matched with intervals identified in previous scans for selective sweeps in sheep genomes. These regions contain well-known candidate genes related to morphology, adaptation, and domestication (e.g., KITLG, KIT, MITF, and MC1R), wool quality and quantity (e.g., DSG@, DSC@, and KRT@), growth and feed intake (e.g., HOXA@, HOXC@, LCORL, NCAPG, LAP3, and CCSER1), reproduction (e.g., CMTM6, HTRA1, GNAQ, UBQLN1, and IFT88), and milk-related traits (e.g., ABCG2, SPP1, ACSS1, and ACSS2). In addition, multiple genes that are putatively related to environmental adaptations were top-ranked in selected intervals (e.g., EGFR, HSPH1, NMUR1, EDNRB, PRL, TSHR, and ADAMTS5). Moreover, we observed that multiple key genes involved in human hereditary sensory and autonomic neuropathies, and genetic disorders accompanied with an inability to feel pain and environmental temperatures, were top-ranked in multiple or individual sheep breeds from Russia pointing to a possible mechanism of adaptation to harsh climatic conditions.

Conclusions

Our work represents the first comprehensive scan for signatures of selection in genomes of local sheep breeds from the Russian Federation of both European and Asian origins. We confirmed that the genomes of Russian sheep contain previously identified signatures of selection, demonstrating the robustness of our integrative approach. Multiple novel signatures of selection were found near genes which could be related to adaptation to the harsh environments of Russia. Our study forms a basis for future work on using Russian sheep genomes to spot specific genetic variants or haplotypes to be used in efforts on developing next-generation highly productive breeds, better suited to diverse Eurasian environments.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5537-0) contains supplementary material, which is available to authorized users.

Cis- and trans-acting variants contribute to survivorship in a naïve Drosophila melanogaster population exposed to ryanoid insecticides

Around the world insecticides are being deregistered and banned, as their environmental costs are deemed too great or their efficacy against pest insects is reduced through the evolution of insecticide resistance. With the introduction of replacement insecticides comes the responsibility to assess the way new insecticides perturb various levels of biological systems, from insect physiology to ecosystems. We used a systems genetics approach to identify genetic variants affecting survivorship of Drosophila melanogaster exposed to chlorantraniliprole. The study population was completely naïve to this insecticide chemistry and yet we find associations with variants in neuromuscular genes and coregulated detoxification genes. We predict that these variants will increase in populations of this “sentinel species” as these insecticides are applied in the environment.

Insecticide resistance is a paradigm of microevolution, and insecticides are responsible for the strongest cases of recent selection in the genome of Drosophila melanogaster. Here we use a naïve population and a novel insecticide class to examine the ab initio genetic architecture of a potential selective response. Genome-wide association studies (GWAS) of chlorantraniliprole susceptibility reveal variation in a gene of major effect, Stretchin Myosin light chain kinase (Strn-Mlck), which we validate with linkage mapping and transgenic manipulation of gene expression. We propose that allelic variation in Strn-Mlck alters sensitivity to the calcium depletion attributable to chlorantraniliprole’s mode of action. GWAS also reveal a network of genes involved in neuromuscular biology. In contrast, phenotype to transcriptome associations identify differences in constitutive levels of multiple transcripts regulated by cnc, the homolog of mammalian Nrf2. This suggests that genetic variation acts in trans to regulate multiple metabolic enzymes in this pathway. The most outstanding association is with the transcription level of Cyp12d1 which is also affected in cis by copy number variation. Transgenic overexpression of Cyp12d1 reduces susceptibility to both chlorantraniliprole and the closely related insecticide cyantraniliprole. This systems genetics study reveals multiple allelic variants segregating at intermediate frequency in a population that is completely naïve to this new insecticide chemistry and it foreshadows a selective response among natural populations to these chemicals.

Bidirectional Selection for Body Weight on Standing Genetic Variation in a Chicken Model

Experimental populations of model organisms provide valuable opportunities to unravel the genomic impact of selection in a controlled system. The Virginia body weight chicken lines represent a unique resource to investigate signatures of selection in a system where long-term, single-trait, bidirectional selection has been carried out for more than 60 generations. At 55 generations of divergent selection, earlier analyses of pooled genome resequencing data from these lines revealed that 14.2% of the genome showed extreme differentiation between the selected lines, contained within 395 genomic regions. Here, we report more detailed analyses of these data exploring the regions displaying within- and between-line genomic signatures of the bidirectional selection applied in these lines. Despite the strict selection regime for opposite extremes in body weight, this did not result in opposite genomic signatures between the lines. The lines often displayed a duality of the sweep signatures, where an extended region of homozygosity in one line, in contrast to mosaic pattern of heterozygosity in the other line. These haplotype mosaics consisted of short, distinct haploblocks of variable between-line divergence, likely the results of a complex demographic history involving bottlenecks, introgressions and moderate inbreeding. We demonstrate this using the example of complex haplotype mosaicism in the growth1 QTL. These mosaics represent the standing genetic variation available at the onset of selection in the founder population. Selection on standing genetic variation can thus result in different signatures depending on the intensity and direction of selection.

Detecting Signatures of Positive Selection along Defined Branches of a Population Tree Using LSD

Identifying the genomic basis underlying local adaptation is paramount to evolutionary biology, and bears many applications in the fields of conservation biology, crop, and animal breeding, as well as personalized medicine. Although many approaches have been developed to detect signatures of positive selection within single populations and population pairs, the increasing wealth of high-throughput sequencing data requires improved methods capable of handling multiple, and ideally large number of, populations in a single analysis. In this study, we introduce LSD (levels of exclusively shared differences), a fast and flexible framework to perform genome-wide selection scans, along the internal and external branches of a given population tree. We use forward simulations to demonstrate that LSD can identify branches targeted by positive selection with remarkable sensitivity and specificity. We illustrate a range of potential applications by analyzing data from the 1000 Genomes Project and uncover a list of adaptive candidates accompanying the expansion of anatomically modern humans out of Africa and their spread to Europe.

The Neutral Theory in Light of Natural Selection

In this perspective, we evaluate the explanatory power of the neutral theory of molecular evolution, 50 years after its introduction by Kimura. We argue that the neutral theory was supported by unreliable theoretical and empirical evidence from the beginning, and that in light of modern, genome-scale data, we can firmly reject its universality. The ubiquity of adaptive variation both within and between species means that a more comprehensive theory of molecular evolution must be sought.

Genome-wide association study and scan for signatures of selection point to candidate genes for body temperature maintenance under the cold stress in Siberian cattle populations

Background

Design of new highly productive livestock breeds, well-adapted to local climatic conditions is one of the aims of modern agriculture and breeding. The genetics underlying economically important traits in cattle are widely studied, whereas our knowledge of the genetic mechanisms of adaptation to local environments is still scarce. To address this issue for cold climates we used an integrated approach for detecting genomic intervals related to body temperature maintenance under acute cold stress. Our approach combined genome-wide association studies (GWAS) and scans for signatures of selection applied to a cattle population (Hereford and Kazakh Whiteheaded beef breeds) bred in Siberia. We utilized the GGP HD150K DNA chip containing 139,376 single nucleotide polymorphism markers.

Results

We detected a single candidate region on cattle chromosome (BTA)15 overlapping between the GWAS results and the results of scans for selective sweeps. This region contains two genes, MSANTD4 and GRIA4. Both genes are functional candidates to contribute to the cold-stress resistance phenotype, due to their indirect involvement in the cold shock response (MSANTD4) and body thermoregulation (GRIA4).

Conclusions

Our results point to a novel region on BTA15 which is a candidate region associated with the body temperature maintenance phenotype in Siberian cattle. The results of our research and the follow up studies might be used for the development of cattle breeds better adapted to cold climates of the Russian Federation and other Northern countries with similar climates.

Electronic supplementary material

The online version of this article (10.1186/s12863-019-0725-0) contains supplementary material, which is available to authorized users.