Detecting signatures of selection through haplotype differentiation among hierarchically structured populations

Scans for signatures of selection in Russian cattle breed genomes reveal new candidate genes for environmental adaptation and acclimation

Domestication and selective breeding has resulted in over 1000 extant cattle breeds. Many of these breeds do not excel in important traits but are adapted to local environments. These adaptations are a valuable source of genetic material for efforts to improve commercial breeds. As a step toward this goal we identified candidate regions to be under selection in genomes of nine Russian native cattle breeds adapted to survive in harsh climates. After comparing our data to other breeds of European and Asian origins we found known and novel candidate genes that could potentially be related to domestication, economically important traits and environmental adaptations in cattle. The Russian cattle breed genomes contained regions under putative selection with genes that may be related to adaptations to harsh environments (e.g., AQP5, RAD50, and RETREG1). We found genomic signatures of selective sweeps near key genes related to economically important traits, such as the milk production (e.g., DGAT1, ABCG2), growth (e.g., XKR4), and reproduction (e.g., CSF2). Our data point to candidate genes which should be included in future studies attempting to identify genes to improve the extant breeds and facilitate generation of commercial breeds that fit better into the environments of Russia and other countries with similar climates.

Genome-Wide Characterization of Selection Signatures and Runs of Homozygosity in Ugandan Goat Breeds

Both natural and artificial selection are among the main driving forces shaping genetic variation across the genome of livestock species. Selection typically leaves signatures in the genome, which are often characterized by high genetic differentiation across breeds and/or a strong reduction in genetic diversity in regions associated with traits under intense selection pressure. In this study, we evaluated selection signatures and genomic inbreeding coefficients, FROH, based on runs of homozygosity (ROH), in six Ugandan goat breeds: Boer (n = 13), and the indigenous breeds Karamojong (n = 15), Kigezi (n = 29), Mubende (n = 29), Small East African (n = 29), and Sebei (n = 29). After genotyping quality control, 45,294 autosomal single nucleotide polymorphisms (SNPs) remained for further analyses. A total of 394 and 6 breed-specific putative selection signatures were identified across all breeds, based on marker-specific fixation index (FST-values) and haplotype differentiation (hapFLK), respectively. These regions were enriched with genes involved in signaling pathways associated directly or indirectly with environmental adaptation, such as immune response (e.g., IL10RB and IL23A), growth and fatty acid composition (e.g., FGF9 and IGF1), and thermo-tolerance (e.g., MTOR and MAPK3). The study revealed little overlap between breeds in genomic regions under selection and generally did not display the typical classic selection signatures as expected due to the complex nature of the traits. In the Boer breed, candidate genes associated with production traits, such as body size and growth (e.g., GJB2 and GJA3) were also identified. Furthermore, analysis of ROH in indigenous goat breeds showed very low levels of genomic inbreeding (with the mean FROH per breed ranging from 0.8% to 2.4%), as compared to higher inbreeding in Boer (mean FROH = 13.8%). Short ROH were more frequent than long ROH, except in Karamojong, providing insight in the developmental history of these goat breeds. This study provides insights into the effects of long-term selection in Boer and indigenous Ugandan goat breeds, which are relevant for implementation of breeding programs and conservation of genetic resources, as well as their sustainable use and management.

Conservation Genomics of the Declining North American Bumblebee Bombus terricola Reveals Inbreeding and Selection on Immune Genes

The yellow-banded bumblebee Bombus terricola was common in North America but has recently declined and is now on the IUCN Red List of threatened species. The causes of B. terricola's decline are not well understood. Our objectives were to create a partial genome and then use this to estimate population data of conservation interest, and to determine whether genes showing signs of recent selection suggest a specific cause of decline. First, we generated a draft partial genome (contig set) for B. terricola, sequenced using Pacific Biosciences RS II at an average depth of 35×. Second, we sequenced the individual genomes of 22 bumblebee gynes from Ontario and Quebec using Illumina HiSeq 2500, each at an average depth of 20×, which were used to improve the PacBio genome calls and for population genetic analyses. The latter revealed that several samples had long runs of homozygosity, and individuals had high inbreeding coefficient F, consistent with low effective population size. Our data suggest that B. terricola's effective population size has decreased orders of magnitude from pre-Holocene levels. We carried out tests of selection to identify genes that may have played a role in ameliorating environmental stressors underlying B. terricola's decline. Several immune-related genes have signatures of recent positive selection, which is consistent with the pathogen-spillover hypothesis for B. terricola's decline. The new B. terricola contig set can help solve the mystery of bumblebee decline by enabling functional genomics research to directly assess the health of pollinators and identify the stressors causing declines.

Genome-Wide Signatures of Selection Reveal Genes Associated With Performance in American Quarter Horse Subpopulations

Selective breeding for athletic performance in various disciplines has resulted in population stratification within the American Quarter Horse (QH) breed. The goals of this study were to utilize high density genotype data to: (1) identify genomic regions undergoing positive selection within and among QH subpopulations; (2) investigate haplotype structure within each QH subpopulation; and (3) identify candidate genes within genomic regions of interest (ROI), as well as biological pathways, predicted to play a role in elite performance in each group. For that, 65K SNP genotyping data on 143 elite individuals from 6 QH subpopulations (cutting, halter, racing, reining, western pleasure, and working cow) were imputed to 2M SNPs. Signatures of selection were identified using F_ST-based (d_i ) and haplotype-based (hapFLK) analyses, accompanied by identification of local haplotype structure and sharing within subpopulations (hapQTL). Regions undergoing positive selection were identified on all 31 autosomes, and ROI on 2 chromosomes were identified by all 3 methods combined. Genes within each ROI were retrieved and used to identify pathways and genes that might contribute to performance in each subpopulation. These included, among others, candidate genes associated with skeletal muscle development, metabolism, and central nervous system development. This work improves our understanding of equine breed development, and provides breeders with a better understanding of how selective breeding impacts the performance of QH populations.

Consistent signatures of selection from genomic analysis of pairs of temporal and spatial Plasmodium falciparum populations from The Gambia

Genome sequences of 247 Plasmodium falciparum isolates collected in The Gambia in 2008 and 2014 were analysed to identify changes possibly related to the scale-up of antimalarial interventions that occurred during this period. Overall, there were 15 regions across the genomes with signatures of positive selection. Five of these were sweeps around known drug resistance and antigenic loci. Signatures at antigenic loci such as thrombospodin related adhesive protein (Pftrap) were most frequent in eastern Gambia, where parasite prevalence and transmission remain high. There was a strong temporal differentiation at a non-synonymous SNP in a cysteine desulfarase (Pfnfs) involved in iron-sulphur complex biogenesis. During the 7-year period, the frequency of the lysine variant at codon 65 (Pfnfs-Q65K) increased by 22% (10% to 32%) in the Greater Banjul area. Between 2014 and 2015, the frequency of this variant increased by 6% (20% to 26%) in eastern Gambia. IC₅₀ for lumefantrine was significantly higher in Pfnfs-65K isolates. This is probably the first evidence of directional selection on Pfnfs or linked loci by lumefantrine. Given the declining malaria transmission, the consequent loss of population immunity, and sustained drug pressure, it is important to monitor Gambian P. falciparum populations for further signs of adaptation.

The evolution of a series of behavioral traits is associated with autism-risk genes in cavefish

Background

An essential question in evolutionary biology is whether shifts in a set of polygenic behaviors share a genetic basis across species. Such a behavioral shift is seen in the cave-dwelling Mexican tetra, Astyanax mexicanus. Relative to surface-dwelling conspecifics, cavefish do not school (asocial), are hyperactive and sleepless, adhere to a particular vibration stimulus (imbalanced attention), behave repetitively, and show elevated stress hormone levels. Interestingly, these traits largely overlap with the core symptoms of human autism spectrum disorder (ASD), raising the possibility that these behavioral traits are underpinned by a similar set of genes (i.e. a repeatedly used suite of genes).

Result

Here, we explored whether modification of ASD-risk genes underlies cavefish evolution. Transcriptomic analyses revealed that > 58.5% of 3152 cavefish orthologs to ASD-risk genes are significantly up- or down-regulated in the same direction as genes in postmortem brains from ASD patients. Enrichment tests suggest that ASD-risk gene orthologs in A. mexicanus have experienced more positive selection than other genes across the genome. Notably, these positively selected cavefish ASD-risk genes are enriched for pathways involved in gut function, inflammatory diseases, and lipid/energy metabolism, similar to symptoms that frequently coexist in ASD patients. Lastly, ASD drugs mitigated cavefish’s ASD-like behaviors, implying shared aspects of neural processing.

Conclusion

Overall, our study indicates that ASD-risk genes and associated pathways (especially digestive, immune and metabolic pathways) may be repeatedly used for shifts in polygenic behaviors across evolutionary time.

Electronic supplementary material

The online version of this article (10.1186/s12862-018-1199-9) contains supplementary material, which is available to authorized users.

The Genetic Architecture Underlying the Evolution of a Rare Piscivorous Life History Form in Brown Trout after Secondary Contact and Strong Introgression

Identifying the genetic basis underlying phenotypic divergence and reproductive isolation is a longstanding problem in evolutionary biology. Genetic signals of adaptation and reproductive isolation are often confounded by a wide range of factors, such as variation in demographic history or genomic features. Brown trout (Salmo trutta) in the Loch Maree catchment, Scotland, exhibit reproductively isolated divergent life history morphs, including a rare piscivorous (ferox) life history form displaying larger body size, greater longevity and delayed maturation compared to sympatric benthivorous brown trout. Using a dataset of 16,066 SNPs, we analyzed the evolutionary history and genetic architecture underlying this divergence. We found that ferox trout and benthivorous brown trout most likely evolved after recent secondary contact of two distinct glacial lineages, and identified 33 genomic outlier windows across the genome, of which several have most likely formed through selection. We further identified twelve candidate genes and biological pathways related to growth, development and immune response potentially underpinning the observed phenotypic differences. The identification of clear genomic signals divergent between life history phenotypes and potentially linked to reproductive isolation, through size assortative mating, as well as the identification of the underlying demographic history, highlights the power of genomic studies of young species pairs for understanding the factors shaping genetic differentiation.

Identification of genomic regions and candidate genes for chicken meat ultimate pH by combined detection of selection signatures and QTL

BACKGROUND

The understanding of the biological determinism of meat ultimate pH, which is strongly related to muscle glycogen content, is a key point for the control of muscle integrity and meat quality in poultry. In the present study, we took advantage of a unique model of two broiler lines divergently selected for the ultimate pH of the pectoralis major muscle (PM-pHu) in order to decipher the genetic control of this trait. Two complementary approaches were used: detection of selection signatures generated during the first five generations and genome-wide association study for PM-pHu and Sartorius muscle pHu (SART-pHu) at the sixth generation of selection.

RESULTS

Sixty-three genomic regions showed significant signatures of positive selection. Out of the 10 most significant regions (detected by HapFLK or FLK method with a p-value below 1e-6), 4 were detected as soon as the first generation (G1) and were recovered at each of the four following ones (G2-G5). Another four corresponded to a later onset of selection as they were detected only at G5. In total, 33 SNPs, located in 24 QTL regions, were significantly associated with PM-pHu. For SART-pHu, we detected 18 SNPs located in 10 different regions. These results confirmed a polygenic determinism for these traits and highlighted two major QTL: one for PM-pHu on GGA1 (with a Bayes Factor (BF) of 300) and one for SART-pHu on GGA4 (with a BF of 257). Although selection signatures were enriched in QTL for PM-pHu, several QTL with strong effect haven't yet responded to selection, suggesting that the divergence between lines might be further increased.

CONCLUSIONS

A few regions of major interest with significant selection signatures and/or strong association with PM-pHu or SART-pHu were evidenced for the first time in chicken. Their gene content suggests several candidates associated with diseases of glycogen storage in humans. The impact of these candidate genes on meat quality and muscle integrity should be further investigated in chicken.

Insulin resistance in cavefish as an adaptation to a nutrient-limited environment

Periodic food shortages are a major challenge faced by organisms in natural habitats. Cave-dwelling animals must withstand long periods of nutrient deprivation, as-in the absence of photosynthesis-caves depend on external energy sources such as seasonal floods. Here we show that cave-adapted populations of the Mexican tetra, Astyanax mexicanus, have dysregulated blood glucose homeostasis and are insulin-resistant compared to river-adapted populations. We found that multiple cave populations carry a mutation in the insulin receptor that leads to decreased insulin binding in vitro and contributes to hyperglycaemia. Hybrid fish from surface-cave crosses carrying this mutation weigh more than non-carriers, and zebrafish genetically engineered to carry the mutation have increased body weight and insulin resistance. Higher body weight may be advantageous in caves as a strategy to cope with an infrequent food supply. In humans, the identical mutation in the insulin receptor leads to a severe form of insulin resistance and reduced lifespan. However, cavefish have a similar lifespan to surface fish and do not accumulate the advanced glycation end-products in the blood that are typically associated with the progression of diabetes-associated pathologies. Our findings suggest that diminished insulin signalling is beneficial in a nutrient-limited environment and that cavefish may have acquired compensatory mechanisms that enable them to circumvent the typical negative effects associated with failure to regulate blood glucose levels.

Convergent genomic signatures of domestication in sheep and goats

The evolutionary basis of domestication has been a longstanding question and its genetic architecture is becoming more tractable as more domestic species become genome-enabled. Before becoming established worldwide, sheep and goats were domesticated in the fertile crescent 10,500 years before present (YBP) where their wild relatives remain. Here we sequence the genomes of wild Asiatic mouflon and Bezoar ibex in the sheep and goat domestication center and compare their genomes with that of domestics from local, traditional, and improved breeds. Among the genomic regions carrying selective sweeps differentiating domestic breeds from wild populations, which are associated among others to genes involved in nervous system, immunity and productivity traits, 20 are common to Capra and Ovis. The patterns of selection vary between species, suggesting that while common targets of selection related to domestication and improvement exist, different solutions have arisen to achieve similar phenotypic end-points within these closely related livestock species.

The sheep and goat were domesticated ~10,500 years ago in the same region of the Middle-East. Here, Alberto et al compare the genomes of wild Asiatic mouflon and Bezoar ibex with that of domestics from local, traditional and improved breeds and find common targets of selection related to domestication and improvement in sheep and goats.

Uncovering Genomic Regions Associated with Trypanosoma Infections in Wild Populations of the Tsetse Fly Glossina fuscipes

Vector-borne diseases are responsible for > 1 million deaths every year but genomic resources for most species responsible for their transmission are limited. This is true for neglected diseases such as sleeping sickness (Human African Trypanosomiasis), a disease caused by Trypanosoma parasites vectored by several species of tseste flies within the genus Glossina. We describe an integrative approach that identifies statistical associations between trypanosome infection status of Glossina fuscipes fuscipes (Gff) flies from Uganda, for which functional studies are complicated because the species cannot be easily maintained in laboratory colonies, and ∼73,000 polymorphic sites distributed across the genome. Then, we identify candidate genes involved in Gff trypanosome susceptibility by taking advantage of genomic resources from a closely related species, G. morsitans morsitans (Gmm). We compiled a comprehensive transcript library from 72 published and unpublished RNAseq experiments of trypanosome-infected and uninfected Gmm flies, and improved the current Gmm transcriptome assembly. This new assembly was then used to enhance the functional annotations on the Gff genome. As a consequence, we identified 56 candidate genes in the vicinity of the 18 regions associated with Trypanosoma infection status in Gff. Twenty-nine of these genes were differentially expressed (DE) among parasite-infected and uninfected Gmm, suggesting that their orthologs in Gff may correlate with disease transmission. These genes were involved in DNA regulation, neurophysiological functions, and immune responses. We highlight the power of integrating population and functional genomics from related species to enhance our understanding of the genetic basis of physiological traits, particularly in nonmodel organisms.

Meta-analysis of genome-wide association studies for cattle stature identifies common genes that regulate body size in mammals

Stature is affected by many polymorphisms of small effect in humans ¹ . In contrast, variation in dogs, even within breeds, has been suggested to be largely due to variants in a small number of genes^2,3. Here we use data from cattle to compare the genetic architecture of stature to those in humans and dogs. We conducted a meta-analysis for stature using 58,265 cattle from 17 populations with 25.4 million imputed whole-genome sequence variants. Results showed that the genetic architecture of stature in cattle is similar to that in humans, as the lead variants in 163 significantly associated genomic regions (P < 5 × 10^-8) explained at most 13.8% of the phenotypic variance. Most of these variants were noncoding, including variants that were also expression quantitative trait loci (eQTLs) and in ChIP-seq peaks. There was significant overlap in loci for stature with humans and dogs, suggesting that a set of common genes regulates body size in mammals.

Revealing the selection history of adaptive loci using genome-wide scans for selection: an example from domestic sheep

Background

One of the approaches to detect genetics variants affecting fitness traits is to identify their surrounding genomic signatures of past selection. With established methods for detecting selection signatures and the current and future availability of large datasets, such studies should have the power to not only detect these signatures but also to infer their selective histories. Domesticated animals offer a powerful model for these approaches as they adapted rapidly to environmental and human-mediated constraints in a relatively short time. We investigated this question by studying a large dataset of 542 individuals from 27 domestic sheep populations raised in France, genotyped for more than 500,000 SNPs.

Results

Population structure analysis revealed that this set of populations harbour a large part of European sheep diversity in a small geographical area, offering a powerful model for the study of adaptation. Identification of extreme SNP and haplotype frequency differences between populations listed 126 genomic regions likely affected by selection. These signatures revealed selection at loci commonly identified as selection targets in many species (“selection hotspots”) including ABCG2, LCORL/NCAPG, MSTN, and coat colour genes such as ASIP, MC1R, MITF, and TYRP1. For one of these regions (ABCG2, LCORL/NCAPG), we could propose a historical scenario leading to the introgression of an adaptive allele into a new genetic background. Among selection signatures, we found clear evidence for parallel selection events in different genetic backgrounds, most likely for different mutations. We confirmed this allelic heterogeneity in one case by resequencing the MC1R gene in three black-faced breeds.

Conclusions

Our study illustrates how dense genetic data in multiple populations allows the deciphering of evolutionary history of populations and of their adaptive mutations.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4447-x) contains supplementary material, which is available to authorized users.

High-resolution analysis of selection sweeps identified between fine-wool Merino and coarse-wool Churra sheep breeds

BACKGROUND

With the aim of identifying selection signals in three Merino sheep lines that are highly specialized for fine wool production (Australian Industry Merino, Australian Merino and Australian Poll Merino) and considering that these lines have been subjected to selection not only for wool traits but also for growth and carcass traits and parasite resistance, we contrasted the OvineSNP50 BeadChip (50 K-chip) pooled genotypes of these Merino lines with the genotypes of a coarse-wool breed, phylogenetically related breed, Spanish Churra dairy sheep. Genome re-sequencing datasets of the two breeds were analyzed to further explore the genetic variation of the regions initially identified as putative selection signals.

RESULTS

Based on the 50 K-chip genotypes, we used the overlapping selection signals (SS) identified by four selection sweep mapping analyses (that detect genetic differentiation, reduced heterozygosity and patterns of haplotype diversity) to define 18 convergence candidate regions (CCR), five associated with positive selection in Australian Merino and the remainder indicating positive selection in Churra. Subsequent analysis of whole-genome sequences from 15 Churra and 13 Merino samples identified 142,400 genetic variants (139,745 bi-allelic SNPs and 2655 indels) within the 18 defined CCR. Annotation of 1291 variants that were significantly associated with breed identity between Churra and Merino samples identified 257 intragenic variants that caused 296 functional annotation variants, 275 of which were located across 31 coding genes. Among these, four synonymous and four missense variants (NPR2_His847Arg, NCAPG_Ser585Phe, LCORL_Asp1214Glu and LCORL_Ile1441Leu) were included.

CONCLUSIONS

Here, we report the mapping and genetic variation of 18 selection signatures that were identified between Australian Merino and Spanish Churra sheep breeds, which were validated by an additional contrast between Spanish Merino and Churra genotypes. Analysis of whole-genome sequencing datasets allowed us to identify divergent variants that may be viewed as candidates involved in the phenotypic differences for wool, growth and meat production/quality traits between the breeds analyzed. The four missense variants located in the NPR2, NCAPG and LCORL genes may be related to selection sweep regions previously identified and various QTL reported in sheep in relation to growth traits and carcass composition.

Immunogenomics of gastrointestinal nematode infection in ruminants - breeding for resistance to produce food sustainably and safely

Gastrointestinal nematode (GIN) infection of ruminants represents a major health and welfare challenge for livestock producers worldwide. The emergence of anthelmintic resistance in important GIN species and the associated animal welfare concerns have stimulated interest in the development of alternative and more sustainable strategies aimed at the effective management of the impact of GINs. These integrative strategies include selective breeding using genetic/genomic tools, grazing management, biological control, nutritional supplementation, vaccination and targeted selective treatment. In this review, the logic of selecting for "resistance" to GIN infection as opposed to "resilience" or "tolerance" is discussed. This is followed by a review of the potential application of immunogenomics to genetic selection for animals that have the capacity to withstand the impact of GIN infection. Advances in relevant genomic technologies are highlighted together with how these tools can be advanced to support the integration of immunogenomic information into ruminant breeding programmes.

Molecular Population Genetics

Molecular population genetics aims to explain genetic variation and molecular evolution from population genetics principles. The field was born 50 years ago with the first measures of genetic variation in allozyme loci, continued with the nucleotide sequencing era, and is currently in the era of population genomics. During this period, molecular population genetics has been revolutionized by progress in data acquisition and theoretical developments. The conceptual elegance of the neutral theory of molecular evolution or the footprint carved by natural selection on the patterns of genetic variation are two examples of the vast number of inspiring findings of population genetics research. Since the inception of the field, Drosophila has been the prominent model species: molecular variation in populations was first described in Drosophila and most of the population genetics hypotheses were tested in Drosophila species. In this review, we describe the main concepts, methods, and landmarks of molecular population genetics, using the Drosophila model as a reference. We describe the different genetic data sets made available by advances in molecular technologies, and the theoretical developments fostered by these data. Finally, we review the results and new insights provided by the population genomics approach, and conclude by enumerating challenges and new lines of inquiry posed by increasingly large population scale sequence data.

The distribution of runs of homozygosity and selection signatures in six commercial meat sheep breeds

Domestication and the subsequent selection of animals for either economic or morphological features can leave a variety of imprints on the genome of a population. Genomic regions subjected to high selective pressures often show reduced genetic diversity and frequent runs of homozygosity (ROH). Therefore, the objective of the present study was to use 42,182 autosomal SNPs to identify genomic regions in 3,191 sheep from six commercial breeds subjected to selection pressure and to quantify the genetic diversity within each breed using ROH. In addition, the historical effective population size of each breed was also estimated and, in conjunction with ROH, was used to elucidate the demographic history of the six breeds. ROH were common in the autosomes of animals in the present study, but the observed breed differences in patterns of ROH length and burden suggested differences in breed effective population size and recent management. ROH provided a sufficient predictor of the pedigree inbreeding coefficient, with an estimated correlation between both measures of 0.62. Genomic regions under putative selection were identified using two complementary algorithms; the fixation index and hapFLK. The identified regions under putative selection included candidate genes associated with skin pigmentation, body size and muscle formation; such characteristics are often sought after in modern-day breeding programs. These regions of selection frequently overlapped with high ROH regions both within and across breeds. Multiple yet uncharacterised genes also resided within putative regions of selection. This further substantiates the need for a more comprehensive annotation of the sheep genome as these uncharacterised genes may contribute to traits of interest in the animal sciences. Despite this, the regions identified as under putative selection in the current study provide an insight into the mechanisms leading to breed differentiation and genetic variation in meat production.

Population transcriptomes reveal synergistic responses of DNA polymorphism and RNA expression to extreme environments on the Qinghai-Tibetan Plateau in a predatory bird

Low oxygen and temperature pose key physiological challenges for endotherms living on the Qinghai-Tibetan Plateau (QTP). Molecular adaptations to high-altitude living have been detected in the genomes of Tibetans, their domesticated animals and a few wild species, but the contribution of transcriptional variation to altitudinal adaptation remains to be determined. Here we studied a top QTP predator, the saker falcon, and analysed how the transcriptome has become modified to cope with the stresses of hypoxia and hypothermia. Using a hierarchical design to study saker populations inhabiting grassland, steppe/desert and highland across Eurasia, we found that the QTP population is already distinct despite having colonized the Plateau <2000 years ago. Selection signals are limited at the cDNA level, but of only seventeen genes identified, three function in hypoxia and four in immune response. Our results show a significant role for RNA transcription: 50% of upregulated transcription factors were related to hypoxia responses, differentiated modules were significantly enriched for oxygen transport, and importantly, divergent EPAS1 functional variants with a refined co-expression network were identified. Conservative gene expression and relaxed immune gene variation may further reflect adaptation to hypothermia. Our results exemplify synergistic responses between DNA polymorphism and RNA expression diversity in coping with common stresses, underpinning the successful rapid colonization of a top predator onto the QTP. Importantly, molecular mechanisms underpinning highland adaptation involve relatively few genes, but are nonetheless more complex than previously thought and involve fine-tuned transcriptional responses and genomic adaptation.

Genetic diversity and signatures of selection in various goat breeds revealed by genome-wide SNP markers

Background

The detection of signatures of selection has the potential to elucidate the identities of genes and mutations associated with phenotypic traits important for livestock species. It is also very relevant to investigate the levels of genetic diversity of a population, as genetic diversity represents the raw material essential for breeding and has practical implications for implementation of genomic selection. A total of 1151 animals from nine goat populations selected for different breeding goals and genotyped with the Illumina Goat 50K single nucleotide polymorphisms (SNP) Beadchip were included in this investigation.

Results

The proportion of polymorphic SNPs ranged from 0.902 (Nubian) to 0.995 (Rangeland). The overall mean H_O and H_E was 0.374 ± 0.021 and 0.369 ± 0.023, respectively. The average pairwise genetic distance (D) ranged from 0.263 (Toggenburg) to 0.323 (Rangeland). The overall average for the inbreeding measures F_EH, F_VR, F_LEUT, F_ROH and F_PED was 0.129, −0.012, −0.010, 0.038 and 0.030, respectively. Several regions located on 19 chromosomes were potentially under selection in at least one of the goat breeds. The genomic population tree constructed using all SNPs differentiated breeds based on selection purpose, while genomic population tree built using only SNPs in the most significant region showed a great differentiation between LaMancha and the other breeds. We hypothesized that this region is related to ear morphogenesis. Furthermore, we identified genes potentially related to reproduction traits, adult body mass, efficiency of food conversion, abdominal fat deposition, conformation traits, liver fat metabolism, milk fatty acids, somatic cells score, milk protein, thermo-tolerance and ear morphogenesis.

Conclusions

In general, moderate to high levels of genetic variability were observed for all the breeds and a characterization of runs of homozygosity gave insights into the breeds’ development history. The information reported here will be useful for the implementation of genomic selection and other genomic studies in goats. We also identified various genome regions under positive selection using smoothed F_ST and hapFLK statistics and suggested genes, which are potentially under selection. These results can now provide a foundation to formulate biological hypotheses related to selection processes in goats.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3610-0) contains supplementary material, which is available to authorized users.

Metafounders are related to F st fixation indices and reduce bias in single-step genomic evaluations

Background

Metafounders are pseudo-individuals that encapsulate genetic heterozygosity and relationships within and across base pedigree populations, i.e. ancestral populations. This work addresses the estimation and usefulness of metafounder relationships in single-step genomic best linear unbiased prediction (ssGBLUP).

Results

We show that ancestral relationship parameters are proportional to standardized covariances of base allelic frequencies across populations, such as \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F_{\text{st}}$$\end{document}Fst fixation indexes. These covariances of base allelic frequencies can be estimated from marker genotypes of related recent individuals and pedigree. Simple methods for their estimation include naïve computation of allele frequencies from marker genotypes or a method of moments that equates average pedigree-based and marker-based relationships. Complex methods include generalized least squares (best linear unbiased estimator (BLUE)) or maximum likelihood based on pedigree relationships. To our knowledge, methods to infer \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F_{\text{st}}$$\end{document}Fst coefficients from marker data have not been developed for related individuals. We derived a genomic relationship matrix, compatible with pedigree relationships, that is constructed as a cross-product of {−1,0,1} codes and that is equivalent (apart from scale factors) to an identity-by-state relationship matrix at genome-wide markers. Using a simulation with a single population under selection in which only males and youngest animals are genotyped, we observed that generalized least squares or maximum likelihood gave accurate and unbiased estimates of the ancestral relationship parameter (true value: 0.40) whereas the naïve method and the method of moments were biased (average estimates of 0.43 and 0.35). We also observed that genomic evaluation by ssGBLUP using metafounders was less biased in terms of estimates of genetic trend (bias of 0.01 instead of 0.12), resulted in less overdispersed (0.94 instead of 0.99) and as accurate (0.74) estimates of breeding values than ssGBLUP without metafounders and provided consistent estimates of heritability.

Conclusions

Estimation of metafounder relationships can be achieved using BLUP-like methods with pedigree and markers. Inclusion of metafounder relationships reduces bias of genomic predictions with no loss in accuracy.

Unveiling genomic regions that underlie differences between Afec-Assaf sheep and its parental Awassi breed

BACKGROUND

Sheep production in Israel has improved by crossing the fat-tailed local Awassi breed with the East Friesian and later, with the Booroola Merino breed, which led to the formation of the highly prolific Afec-Assaf strain. This strain differs from its parental Awassi breed in morphological traits such as tail and horn size, coat pigmentation and wool characteristics, as well as in production, reproductive and health traits. To identify major genes associated with the formation of the Afec-Assaf strain, we genotyped 41 Awassi and 141 Afec-Assaf sheep using the Illumina Ovine SNP50 BeadChip array, and analyzed the results with PLINK and EMMAX software. The detected variable genomic regions that differed between Awassi and Afec-Assaf sheep (variable genomic regions; VGR) were compared to selection signatures that were reported in 48 published genome-wide association studies in sheep. Because the Afec-Assaf strain, but not the Awassi breed, carries the Booroola mutation, association analysis of BMPR1B used as the test gene was performed to evaluate the ability of this study to identify a VGR that includes such a major gene.

RESULTS

Of the 20 detected VGR, 12 were novel to this study. A ~7-Mb VGR was identified on Ovies aries chromosome OAR6 where the Booroola mutation is located. Similar to other studies, the most significant VGR was detected on OAR10, in a region that contains candidate genes affecting horn type (RXFP2), climate adaptation (ALOX5AP), fiber diameter (KATNAl1), coat pigmentation (FRY) and genes associated with fat distribution. The VGR on OAR2 included BNC2, which is also involved in controlling coat pigmentation in sheep. Six other VGR contained genes that were shown to be involved in coat pigmentation by analyzing their mammalian orthologues. Genes associated with fat distribution in humans, including GRB14 and COBLL1, were located in additional VGR. Sequencing DNA from Awassi and Afec-Assaf individuals revealed non-synonymous mutations in some of these candidate genes.

CONCLUSIONS

Our results highlight VGR that differentiate the Awassi breed from the Afec-Assaf strain, some of which may include genes that confer an advantage to Afec-Assaf and Assaf over Awassi sheep with respect to intensive sheep production under Mediterranean conditions.

Detecting polygenic selection in marine populations by combining population genomics and quantitative genetics approaches

Highly fecund marine species with dispersive life-history stages often display large population sizes and wide geographic distribution ranges. Consequently, they are expected to experience reduced genetic drift, efficient selection fueled by frequent adaptive mutations, and high migration loads. This has important consequences for understanding how local adaptation proceeds in the sea. A key issue in this regard, relates to the genetic architecture underlying fitness traits. Theory predicts that adaptation may involve many genes but with a high variance in effect size. Therefore, the effect of selection on allele frequencies may be substantial for the largest effect size loci, but insignificant for small effect genes. In such a context, the performance of population genomic methods to unravel the genetic basis of adaptation depends on the fraction of adaptive genetic variance explained by the cumulative effect of outlier loci. Here, we address some methodological challenges associated with the detection of local adaptation using molecular approaches. We provide an overview of genome scan methods to detect selection, including those assuming complex demographic models that better describe spatial population structure. We then focus on quantitative genetics approaches that search for genotype-phenotype associations at different genomic scales, including genome-wide methods evaluating the cumulative effect of variants. We argue that the limited power of single locus tests can be alleviated by the use of polygenic scores to estimate the joint contribution of candidate variants to phenotypic variation.

Selection signature analysis reveals genes associated with tail type in Chinese indigenous sheep

Fat-tailed sheep have commercial value because consumers prefer high-protein and low-fat food and producers care about feed conversion rate. However, fat-tailed sheep still have some scientific significance, as the fat tail is commonly regarded as a characteristic of environmental adaptability. Finding the candidate genes associated with fat tail formation is essential for breeding and conservation. To identify these candidate genes, we applied FST and hapFLK approaches in fat- and thin-tailed sheep with available 50K SNP genotype data. These two methods found 6.24 Mb of overlapped regions and 43 genes that may associated with fat tail development. Gene annotation showed that HOXA11, BMP2, PPP1CC, SP3, SP9, WDR92, PROKR1 and ETAA1 may play important roles in fat tail formation. These findings provide insight into tail fat development and a guide for molecular breeding and conservation.

Finding the Genomic Basis of Local Adaptation: Pitfalls, Practical Solutions, and Future Directions

Uncovering the genetic and evolutionary basis of local adaptation is a major focus of evolutionary biology. The recent development of cost-effective methods for obtaining high-quality genome-scale data makes it possible to identify some of the loci responsible for adaptive differences among populations. Two basic approaches for identifying putatively locally adaptive loci have been developed and are broadly used: one that identifies loci with unusually high genetic differentiation among populations (differentiation outlier methods) and one that searches for correlations between local population allele frequencies and local environments (genetic-environment association methods). Here, we review the promises and challenges of these genome scan methods, including correcting for the confounding influence of a species' demographic history, biases caused by missing aspects of the genome, matching scales of environmental data with population structure, and other statistical considerations. In each case, we make suggestions for best practices for maximizing the accuracy and efficiency of genome scans to detect the underlying genetic basis of local adaptation. With attention to their current limitations, genome scan methods can be an important tool in finding the genetic basis of adaptive evolutionary change.

Population structure of eleven Spanish ovine breeds and detection of selective sweeps with BayeScan and hapFLK

The goals of the current work were to analyse the population structure of 11 Spanish ovine breeds and to detect genomic regions that may have been targeted by selection. A total of 141 individuals were genotyped with the Infinium 50 K Ovine SNP BeadChip (Illumina). We combined this dataset with Spanish ovine data previously reported by the International Sheep Genomics Consortium (N = 229). Multidimensional scaling and Admixture analyses revealed that Canaria de Pelo and, to a lesser extent, Roja Mallorquina, Latxa and Churra are clearly differentiated populations, while the remaining seven breeds (Ojalada, Castellana, Gallega, Xisqueta, Ripollesa, Rasa Aragonesa and Segureña) share a similar genetic background. Performance of a genome scan with BayeScan and hapFLK allowed us identifying three genomic regions that are consistently detected with both methods i.e. Oar3 (150–154 Mb), Oar6 (4–49 Mb) and Oar13 (68–74 Mb). Neighbor-joining trees based on polymorphisms mapping to these three selective sweeps did not show a clustering of breeds according to their predominant productive specialization (except the local tree based on Oar13 SNPs). Such cryptic signatures of selection have been also found in the bovine genome, posing a considerable challenge to understand the biological consequences of artificial selection.

A haplotype method detects diverse scenarios of local adaptation from genomic sequence variation

Identifying genomic targets of population-specific positive selection is a major goal in several areas of basic and applied biology. However, it is unclear how often such selection should act on new mutations versus standing genetic variation or recurrent mutation, and furthermore, favoured alleles may either become fixed or remain variable in the population. Very few population genetic statistics are sensitive to all of these modes of selection. Here, we introduce and evaluate the Comparative Haplotype Identity statistic (χMD ), which assesses whether pairwise haplotype sharing at a locus in one population is unusually large compared with another population, relative to genomewide trends. Using simulations that emulate human and Drosophila genetic variation, we find that χMD is sensitive to a wide range of selection scenarios, and for some very challenging cases (e.g. partial soft sweeps), it outperforms other two-population statistics. We also find that, as with FST , our haplotype approach has the ability to detect surprisingly ancient selective sweeps. Particularly for the scenarios resembling human variation, we find that χMD outperforms other frequency- and haplotype-based statistics for soft and/or partial selective sweeps. Applying χMD and other between-population statistics to published population genomic data from D. melanogaster, we find both shared and unique genes and functional categories identified by each statistic. The broad utility and computational simplicity of χMD will make it an especially valuable tool in the search for genes targeted by local adaptation.

Whole-genome resequencing of honeybee drones to detect genomic selection in a population managed for royal jelly

Four main evolutionary lineages of A. mellifera have been described including eastern Europe (C) and western and northern Europe (M). Many apiculturists prefer bees from the C lineage due to their docility and high productivity. In France, the routine importation of bees from the C lineage has resulted in the widespread admixture of bees from the M lineage. The haplodiploid nature of the honeybee Apis mellifera, and its small genome size, permits affordable and extensive genomics studies. As a pilot study of a larger project to characterise French honeybee populations, we sequenced 60 drones sampled from two commercial populations managed for the production of honey and royal jelly. Results indicate a C lineage origin, whilst mitochondrial analysis suggests two drones originated from the O lineage. Analysis of heterozygous SNPs identified potential copy number variants near to genes encoding odorant binding proteins and several cytochrome P450 genes. Signatures of selection were detected using the hapFLK haplotype-based method, revealing several regions under putative selection for royal jelly production. The framework developed during this study will be applied to a broader sampling regime, allowing the genetic diversity of French honeybees to be characterised in detail.

Patterns of Genome-Wide Variation in Glossina fuscipes fuscipes Tsetse Flies from Uganda

The tsetse fly Glossina fuscipes fuscipes (Gff) is the insect vector of the two forms of Human African Trypanosomiasis (HAT) that exist in Uganda. Understanding Gff population dynamics, and the underlying genetics of epidemiologically relevant phenotypes is key to reducing disease transmission. Using ddRAD sequence technology, complemented with whole-genome sequencing, we developed a panel of ∼73,000 single-nucleotide polymorphisms (SNPs) distributed across the Gff genome that can be used for population genomics and to perform genome-wide-association studies. We used these markers to estimate genomic patterns of linkage disequilibrium (LD) in Gff, and used the information, in combination with outlier-locus detection tests, to identify candidate regions of the genome under selection. LD in individual populations decays to half of its maximum value (r(2) max/2) between 1359 and 2429 bp. The overall LD estimated for the species reaches r(2) max/2 at 708 bp, an order of magnitude slower than in Drosophila Using 53 infected (Trypanosoma spp.) and uninfected flies from four genetically distinct Ugandan populations adapted to different environmental conditions, we were able to identify SNPs associated with the infection status of the fly and local environmental adaptation. The extent of LD in Gff likely facilitated the detection of loci under selection, despite the small sample size. Furthermore, it is probable that LD in the regions identified is much higher than the average genomic LD due to strong selection. Our results show that even modest sample sizes can reveal significant genetic associations in this species, which has implications for future studies given the difficulties of collecting field specimens with contrasting phenotypes for association analysis.

Rare intronic variants of TCF7L2 arising by selective sweeps in an indigenous population from Mexico

Background

Genetic variations of the TCF7L2 gene are associated with the development of Type 2 diabetes (T2D). The associated mutations have demonstrated an adaptive role in some human populations, but no studies have determined the impact of evolutionary forces on genetic diversity in indigenous populations from Mexico. Here, we sequenced and analyzed the variation of the TCF7L2 gene in three Amerindian populations and compared the results with whole-exon-sequencing of Mestizo populations from Sigma and the 1000 Genomes Project to assess the roles of selection and recombination in diversity.

Results

The diversity in the indigenous populations was biased to intronic regions. Most of the variation was low frequency. Only mutations rs77961654 and rs61724286 were located on exon 15. We did not observe variation in intronic region 4–6 in any of the three indigenous populations. In addition, we identified peaks of selective sweeps in the mestizo samples from the Sigma Project within this region. By replicating the analysis of association with T2D between case-controls from the Sigma Project, we determined that T2D was most highly associated with the rs7903146 risk allele and to a lesser extent with the other six variants. All associated markers were located in intronic region 4–6, and their r² values of linkage disequilibrium were significantly higher in the Mexican population than in Africans from the 1000 Genomes Project. We observed reticulations in both the haplotypes network analysis from seven marker associates and the neighborNet tree based on 6061 markers in the TCF7L2 gene identified from all samples of the 1000 Genomes Project. Finally, we identified two recombination hotspots in the upstream region and 3’ end of the TCF7L2 gene.

Conclusions

The lack of diversity in intronic region 4–6 in Indigenous populations could be an effect of selective sweeps generated by the selection of neighboring rare variants at T2D-associated mutations. The survivors’ variants make the intronic region 4–6 the area of the greatest population differentiation within the TCF7L2 gene. The abundance of selective peak sweeps in the downstream region of the TCF7L2 gene suggests that the TCF7L2 gene is part of a region that is in constant recombination between populations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-016-0372-7) contains supplementary material, which is available to authorized users.

Evaluating the performance of selection scans to detect selective sweeps in domestic dogs

Selective breeding of dogs has resulted in repeated artificial selection on breed-specific morphological phenotypes. A number of quantitative trait loci associated with these phenotypes have been identified in genetic mapping studies. We analysed the population genomic signatures observed around the causal mutations for 12 of these loci in 25 dog breeds, for which we genotyped 25 individuals in each breed. By measuring the population frequencies of the causal mutations in each breed, we identified those breeds in which specific mutations most likely experienced positive selection. These instances were then used as positive controls for assessing the performance of popular statistics to detect selection from population genomic data. We found that artificial selection during dog domestication has left characteristic signatures in the haplotype and nucleotide polymorphism patterns around selected loci that can be detected in the genotype data from a single population sample. However, the sensitivity and accuracy at which such signatures were detected varied widely between loci, the particular statistic used and the choice of analysis parameters. We observed examples of both hard and soft selective sweeps and detected strong selective events that removed genetic diversity almost entirely over regions >10 Mbp. Our study demonstrates the power and limitations of selection scans in populations with high levels of linkage disequilibrium due to severe founder effects and recent population bottlenecks.

Detecting Genomic Signatures of Natural Selection with Principal Component Analysis: Application to the 1000 Genomes Data

To characterize natural selection, various analytical methods for detecting candidate genomic regions have been developed. We propose to perform genome-wide scans of natural selection using principal component analysis (PCA). We show that the common FST index of genetic differentiation between populations can be viewed as the proportion of variance explained by the principal components. Considering the correlations between genetic variants and each principal component provides a conceptual framework to detect genetic variants involved in local adaptation without any prior definition of populations. To validate the PCA-based approach, we consider the 1000 Genomes data (phase 1) considering 850 individuals coming from Africa, Asia, and Europe. The number of genetic variants is of the order of 36 millions obtained with a low-coverage sequencing depth (3×). The correlations between genetic variation and each principal component provide well-known targets for positive selection (EDAR, SLC24A5, SLC45A2, DARC), and also new candidate genes (APPBPP2, TP1A1, RTTN, KCNMA, MYO5C) and noncoding RNAs. In addition to identifying genes involved in biological adaptation, we identify two biological pathways involved in polygenic adaptation that are related to the innate immune system (beta defensins) and to lipid metabolism (fatty acid omega oxidation). An additional analysis of European data shows that a genome scan based on PCA retrieves classical examples of local adaptation even when there are no well-defined populations. PCA-based statistics, implemented in the PCAdapt R package and the PCAdapt fast open-source software, retrieve well-known signals of human adaptation, which is encouraging for future whole-genome sequencing project, especially when defining populations is difficult.

Uncovering Adaptation from Sequence Data: Lessons from Genome Resequencing of Four Cattle Breeds

Detecting the molecular basis of adaptation is one of the major questions in population genetics. With the advance in sequencing technologies, nearly complete interrogation of genome-wide polymorphisms in multiple populations is becoming feasible in some species, with the expectation that it will extend quickly to new ones. Here, we investigate the advantages of sequencing for the detection of adaptive loci in multiple populations, exploiting a recently published data set in cattle (Bos taurus). We used two different approaches to detect statistically significant signals of positive selection: a within-population approach aimed at identifying hard selective sweeps and a population-differentiation approach that can capture other selection events such as soft or incomplete sweeps. We show that the two methods are complementary in that they indeed capture different kinds of selection signatures. Our study confirmed some of the well-known adaptive loci in cattle (e.g., MC1R, KIT, GHR, PLAG1, NCAPG/LCORL) and detected some new ones (e.g., ARL15, PRLR, CYP19A1, PPM1L). Compared to genome scans based on medium- or high-density SNP data, we found that sequencing offered an increased detection power and a higher resolution in the localization of selection signatures. In several cases, we could even pinpoint the underlying causal adaptive mutation or at least a very small number of possible candidates (e.g., MC1R, PLAG1). Our results on these candidates suggest that a vast majority of adaptive mutations are likely to be regulatory rather than protein-coding variants.

The Genetic Basis of Haploid Induction in Maize Identified with a Novel Genome-Wide Association Method

In vivo haploid induction (HI) triggered by pollination with special intraspecific genotypes, called inducers, is unique to Zea maysL. within the plant kingdom and has revolutionized maize breeding during the last decade. However, the molecular mechanisms underlying HI in maize are still unclear. To investigate the genetic basis of HI, we developed a new approach for genome-wide association studies (GWAS), termed conditional haplotype extension (CHE) test that allows detection of selective sweeps even under almost perfect confounding of population structure and trait expression. Here, we applied this test to identify genomic regions required for HI expression and dissected the combined support interval (50.34 Mb) of the QTL qhir1, detected in a previous study, into two closely linked genomic segments relevant for HI expression. The first, termed qhir11(0.54 Mb), comprises an already fine-mapped region but was not diagnostic for differentiating inducers and noninducers. The second segment, termed qhir12(3.97 Mb), had a haplotype allele common to all 53 inducer lines but not found in any of the 1482 noninducers. By comparing resequencing data of one inducer with 14 noninducers, we detected in the qhir12 region three candidate genes involved in DNA or amino acid binding, however, none for qhir11 We propose that the CHE test can be utilized in introgression breeding and different fields of genetics to detect selective sweeps in heterogeneous genetic backgrounds.

R2d2 Drives Selfish Sweeps in the House Mouse

A selective sweep is the result of strong positive selection driving newly occurring or standing genetic variants to fixation, and can dramatically alter the pattern and distribution of allelic diversity in a population. Population-level sequencing data have enabled discoveries of selective sweeps associated with genes involved in recent adaptations in many species. In contrast, much debate but little evidence addresses whether “selfish” genes are capable of fixation—thereby leaving signatures identical to classical selective sweeps—despite being neutral or deleterious to organismal fitness. We previously described R2d2, a large copy-number variant that causes nonrandom segregation of mouse Chromosome 2 in females due to meiotic drive. Here we show population-genetic data consistent with a selfish sweep driven by alleles of R2d2 with high copy number (R2d2^HC) in natural populations. We replicate this finding in multiple closed breeding populations from six outbred backgrounds segregating for R2d2 alleles. We find that R2d2^HC rapidly increases in frequency, and in most cases becomes fixed in significantly fewer generations than can be explained by genetic drift. R2d2^HC is also associated with significantly reduced litter sizes in heterozygous mothers, making it a true selfish allele. Our data provide direct evidence of populations actively undergoing selfish sweeps, and demonstrate that meiotic drive can rapidly alter the genomic landscape in favor of mutations with neutral or even negative effects on overall Darwinian fitness. Further study will reveal the incidence of selfish sweeps, and will elucidate the relative contributions of selfish genes, adaptation and genetic drift to evolution.

Selection for population-specific adaptation shaped patterns of variation in the photoperiod pathway genes in Arabidopsis lyrata during post-glacial colonization

Spatially varying selection can lead to population-specific adaptation, which is often recognized at the phenotypic level; however, the genetic evidence is weaker in many groups of organisms. In plants, environmental shifts that occur due to colonization of a novel environment may require adaptive changes in the timing of growth and flowering, which are often governed by location-specific environmental cues such as day length. We studied locally varying selection in 19 flowering time loci in nine populations of the perennial herb Arabidopsis lyrata, which has a wide but patchy distribution in temperate and boreal regions of the northern hemisphere. The populations differ in their recent population demographic and colonization histories and current environmental conditions, especially in the growing season length. We searched for population-specific molecular signatures of directional selection by comparing a set of candidate flowering time loci with a genomic reference set within each population using multiple approaches and contrasted the patterns of different populations. The candidate loci possessed approximately 20% of the diversity of the reference loci. On average the flowering time loci had more rare alleles (a smaller Tajima's D) and an excess of highly differentiated sites relative to the reference, suggesting positive selection. The strongest signal of selection was detected in photoperiodic pathway loci in the colonizing populations of Northwestern Europe, whereas no evidence of positive selection was detected in the Central European populations. These findings emphasized the population-specific nature of selection and suggested that photoperiodic adaptation was important during postglacial colonization of the species.

Testing for Ancient Selection Using Cross-population Allele Frequency Differentiation

A powerful way to detect selection in a population is by modeling local allele frequency changes in a particular region of the genome under scenarios of selection and neutrality and finding which model is most compatible with the data. A previous method based on a cross-population composite likelihood ratio (XP-CLR) uses an outgroup population to detect departures from neutrality that could be compatible with hard or soft sweeps, at linked sites near a beneficial allele. However, this method is most sensitive to recent selection and may miss selective events that happened a long time ago. To overcome this, we developed an extension of XP-CLR that jointly models the behavior of a selected allele in a three-population tree. Our method - called "3-population composite likelihood ratio" (3P-CLR) - outperforms XP-CLR when testing for selection that occurred before two populations split from each other and can distinguish between those events and events that occurred specifically in each of the populations after the split. We applied our new test to population genomic data from the 1000 Genomes Project, to search for selective sweeps that occurred before the split of Yoruba and Eurasians, but after their split from Neanderthals, and that could have led to the spread of modern-human-specific phenotypes. We also searched for sweep events that occurred in East Asians, Europeans, and the ancestors of both populations, after their split from Yoruba. In both cases, we are able to confirm a number of regions identified by previous methods and find several new candidates for selection in recent and ancient times. For some of these, we also find suggestive functional mutations that may have driven the selective events.

Genome-Wide Scan for Adaptive Divergence and Association with Population-Specific Covariates

In population genomics studies, accounting for the neutral covariance structure across population allele frequencies is critical to improve the robustness of genome-wide scan approaches. Elaborating on the BayEnv model, this study investigates several modeling extensions (i) to improve the estimation accuracy of the population covariance matrix and all the related measures, (ii) to identify significantly overly differentiated SNPs based on a calibration procedure of the XtX statistics, and (iii) to consider alternative covariate models for analyses of association with population-specific covariables. In particular, the auxiliary variable model allows one to deal with multiple testing issues and, providing the relative marker positions are available, to capture some linkage disequilibrium information. A comprehensive simulation study was carried out to evaluate the performances of these different models. Also, when compared in terms of power, robustness, and computational efficiency to five other state-of-the-art genome-scan methods (BayEnv2, BayScEnv, BayScan, flk, and lfmm), the proposed approaches proved highly effective. For illustration purposes, genotyping data on 18 French cattle breeds were analyzed, leading to the identification of 13 strong signatures of selection. Among these, four (surrounding the KITLG, KIT, EDN3, and ALB genes) contained SNPs strongly associated with the piebald coloration pattern while a fifth (surrounding PLAG1) could be associated to morphological differences across the populations. Finally, analysis of Pool-Seq data from 12 populations of Littorina saxatilis living in two different ecotypes illustrates how the proposed framework might help in addressing relevant ecological issues in nonmodel species. Overall, the proposed methods define a robust Bayesian framework to characterize adaptive genetic differentiation across populations. The BayPass program implementing the different models is available at http://www1.montpellier.inra.fr/CBGP/software/baypass/.

Using the variability of linkage disequilibrium between subpopulations to infer sweeps and epistatic selection in a diverse panel of chickens

A whole-genome scan for identifying selection acting on pairs of linked loci is proposed and implemented. The scan is based on , one of Ohta's 1982 measures of between-population linkage disequilibrium (LD). An approximate empirical null distribution for the statistic is suggested. Although the partitioning of LD into between-population components was originally used to investigate epistatic selection, we demonstrate that values of may also be influenced by single-locus selective sweeps with linkage but no epistasis. The proposed scan is implemented in a diverse panel of chickens including 72 distinct breeds genotyped at 538 298 single-nucleotide polymorphisms. In all, 1723 locus pairs are identified as putatively corresponding to a selective sweep or epistatic selection. These pairs of loci generally cluster to form overlapping or neighboring signals of selection. Known variants that were expected to have been under selection in the panel are identified, as well as an assortment of novel regions that have putatively been under selection in chickens. Notably, a promising pair of genes located 8 MB apart on chromosome 9 are identified based on as demonstrating strong evidence of dispersive epistatic selection between populations.

Haplotype-based analysis of selective sweeps in sheep

Domestic animals represent an extremely useful model for linking genotypic and phenotypic variation. One approach involves identifying allele frequency differences between populations, using F(ST), to detect selective sweeps. While simple to calculate, FST may generate false positives due to aspects of population history. This prompted the development of hapFLK, a metric that measures haplotype differentiation while accounting for the genetic relationship between populations. The focus of this paper was to apply hapFLK in sheep with available SNP50 genotypes. The hapFLK approach identified a known selective sweep on chromosome 10 with high precision. Further, five regions were identified centered on genes with strong evidence for positive selection (COL1A2, NCAPG, LCORL, and RXFP2). Estimation of global F(ST) revealed many more genomic regions, providing empirical data in support of published simulation-based results concerning elevated type I error associated with F(ST) when it is being used to characterize sweep regions. The findings, while conducted using sheep SNP data, are likely to be applicable across those domestic animal species that have undergone artificial selection for desirable phenotypic traits.