Genome-wide scans for signatures of selection in North African sheep reveals differentially selected regions between fat- and thin-tailed breeds

North Africa counts several sheep breeds that can be categorized as fat- and thin-tailed. The former are well adapted to dryland environments. In this study, we used 50K genome-wide single nucleotide polymorphism profiles from 462 animals representing nine fat-tailed and 13 thin-tailed sheep breeds across North Africa to localize genomic regions putatively under differential selective pressures between the two types of breeds. We observed genetic clines from east to west and from north to south. The east-west cline separates the fat- and thin-tailed breeds, with the exception of the fat-tailed Algerian Barbarine, which is closely related to a genetically homogeneous cluster of Moroccan and Algerian thin-tailed breeds. Using a combination of three extended haplotype homozygosity tests, we detected seven candidate regions under divergent selection between fat- and thin-tailed sheep. The strongest selection signals reside on chromosomes 1 and 13, with the latter spanning the BMP2 gene, known to be associated with the fat-tail phenotype. Overall, the candidate regions under selection in fat-tailed sheep overlap with genes associated with adaptation to desert-like environments including adipogenesis, as well as heat and drought tolerance. Our results confirm previously reported candidate genes known to be a target of fat-tail selection in sheep but also reveal novel candidate genes specifically under selection in North African populations.

Dynamic Outlier Slicing Allows Broader Exploration of Adaptive Divergence: A Comparison of Individual Genome and Pool-Seq Data Linked to Humic Adaptation in Perch

How genetic variation contributes to adaptation at different environments is a central focus in evolutionary biology. However, most free-living species still lack a comprehensive understanding of the primary molecular mechanisms of adaptation. Here, we characterised the targets of selection associated with drastically different aquatic environments-humic and clear water-in the common freshwater fish, Eurasian perch (Perca fluviatilis). By using whole-genome sequencing (WGS) on a large population dataset (n = 42 populations) and analysing 873,788 SNPs, our primary aim was to uncover novel and confirm known footprints of selection. We compared individual and pooled WGS, and developed a novel approach, termed dynamic outlier slicing, to assess how the choice of outlier-calling stringency influences functional and Gene Ontology (GO) enrichment. By integrating genome-environment association (GEA) analysis with allele frequency-based approaches, we estimated composite selection signals (CSS) and identified 2679 outlier SNPs distributed across 324 genomic regions, involving 468 genes. Dynamic outlier slicing identified robust enrichment signals in five annotation categories (upstream, downstream, synonymous, 5'UTR and 3'UTR) highlighting the crucial role of regulatory elements in adaptive evolution. Furthermore, GO analyses revealed strong enrichment of molecular functions associated with gated channel activity, transmembrane transporter activity and ion channel activity, emphasising the importance of osmoregulation and ion balance maintenance. Our findings demonstrate that despite substantial random drift and divergence, WGS of high number of population pools enabled the identification of strong selection signals associated with adaptation to both humic and clear water environments, providing robust evidence of widespread adaptation. We anticipate that the dynamic outlier slicing method we developed will enable a more thorough exploration of adaptive divergence across a diverse range of species.

Fast and accurate deep learning scans for signatures of natural selection in genomes using FASTER-NN

Deep learning classification models based on Convolutional Neural Networks (CNNs) are increasingly used in population genetic inference for detecting signatures of natural selection. Prevailing detection methods treat the design of the classifier as a discrete phase, assuming that high classification accuracy is the sole prerequisite for precise detection. This frequently steers method development toward classification-driven optimizations that can inadvertently impede detection. We present FASTER-NN, a CNN classifier designed specifically for the precise detection of natural selection. It has higher sensitivity than state-of-the-art CNN classifiers while only processing allele frequencies and genomic positions through dilated convolutions to maximize data reuse. As a result, execution time is invariant to the sample size and the chromosome length, creating a highly suitable solution for large-scale, whole-genome scans. Furthermore, FASTER-NN can accurately identify selective sweeps in recombination hotspots, which is a highly challenging detection problem with very limited theoretical treatment to date.

Repeated global adaptation across plant species

Global adaptation occurs when all populations of a species undergo selection toward a common optimum. This can occur by a hard selective sweep with the emergence of a new globally advantageous allele that spreads throughout a species' natural range until reaching fixation. This evolutionary process leaves a temporary trace in the region affected, which is detectable using population genomic methods. While selective sweeps have been identified in many species, there have been few comparative and systematic studies of the genes involved in global adaptation. Building upon recent findings showing repeated genetic basis of local adaptation across independent populations and species, we asked whether certain genes play a more significant role in driving global adaptation across plant species. To address this question, we scanned the genomes of 17 plant species to identify signals of repeated global selective sweeps. Despite the substantial evolutionary distance between the species analyzed, we identified several gene families with strong evidence of repeated positive selection. These gene families tend to be enriched for reduced pleiotropy, consistent with predictions from Fisher's evolutionary model and the cost of complexity hypothesis. We also found that genes with repeated sweeps exhibit elevated levels of gene duplication. Our findings contrast with recent observations of increased pleiotropy in genes driving local adaptation, consistent with predictions based on the theory of migration-selection balance.

Inversions contribute disproportionately to parallel genomic divergence in dune sunflowers

The probability of parallel genetic evolution is a function of the strength of selection and constraints imposed by genetic architecture. Inversions capture locally adapted alleles and suppress recombination between them, which limits the range of adaptive responses. In addition, the combined phenotypic effect of alleles within inversions is likely to be greater than that of individual alleles; this should further increase the contributions of inversions to parallel evolution. We tested the hypothesis that inversions contribute disproportionately to parallel genetic evolution in independent dune ecotypes of Helianthus petiolaris. We analysed habitat data and identified variables underlying parallel habitat shifts. Genotype-environment association analyses of these variables indicated parallel responses of inversions to shared selective pressures. We also confirmed larger seed size across the dunes and performed quantitative trait locus mapping with multiple crosses. Quantitative trait loci shared between locations fell into inversions more than expected by chance. We used whole-genome sequencing data to identify selective sweeps in the dune ecotypes and found that the majority of shared swept regions were found within inversions. Phylogenetic analyses of shared regions indicated that within inversions, the same allele typically was found in the dune habitat at both sites. These results confirm predictions that inversions drive parallel divergence in the dune ecotypes.

Assessment of genome complementarity in three beef-on-dairy crossbreds reveals sire-specific effects on production traits with comparable rates of genomic inbreeding reduction

BACKGROUND

Crossbreeding beef bulls with dairy cows can improve the economic value and fitness of calves not entering dairy production owing to increased meat yield and heterosis. However, outcrossing might reduce the dosage of alleles that confer local adaptation or result in a higher risk of dystocia due to increased calf size. Given the clear phenotypic differences between beef breeds, the varying phylogenetic distances between beef and dairy breeds, and the genomic variations within breeds, the attainable economic and fitness gains of calves will strongly depend on the selection of sires for crossing. Thus, the aim of this study was to assess genome complementarity between Angus (AAN), Limousin (LIM), or Simmental (SIM) beef bulls and Brown Swiss (BSW) dairy cows by quantifying genomic inbreeding reduction in F1 crosses and identifying genes potentially under BSW-specific selection that might be affected by outcrossing.

RESULTS

Low-pass sequencing data from 181 cows, 34 bulls, and 301 of their F1 progeny, and body weight and carcass composition measurements of 248 F1s were obtained. The high genomic inbreeding levels detected in the BSW cows were substantially reduced in the crossbreds, with only minor differences between the sire breeds. In the BSW cows, 585 candidate genes under selection were identified, overrepresenting genes associated with milk, meat and carcass, and production traits. Only a few genes were strongly differentiated at nonsynonymous variants between the BSW and beef breeds, including four tightly clustered genes (FAM184B, NCAPG, DCAF16, and LCORL) nearly fixed for alternate alleles in the BSW cows but mostly heterozygous or homozygous for the reference alleles in the AAN and LIM bulls. The alternate allele dosage at these genes significantly correlated with reduced carcass weight and protein mass in F1s.

CONCLUSION

Some of the few genes that were highly divergent between the BSW and beef breeds at nonsynonymous variants were likely under strong selection for reduced carcass weight in the BSW breed, potentially due to trade-offs between beef and dairy productions. As alleles with opposing effects still segregate in beef cattle, marker-assisted selection of mating pairs may be used to modulate the desired phenotypes and simultaneously decrease genomic inbreeding.

Selection signatures for high altitude adaptation in livestock: A review

High altitude adapted livestock species (cattle, yak, goat, sheep, and horse) has critical role in the human socioeconomic sphere and acts as good source of animal source products including milk, meat, and leather, among other things. These species sustain production and reproduction even in harsh environments on account of adaptation resulting from continued evolution of beneficial traits. Selection pressure leads to various adaptive strategies in livestock whose footprints are evident at the different genomic sites as the "Selection Signature". Scrutiny of these signatures provides us crucial insight into the evolutionary process and domestication of livestock adapted to diverse climatic conditions. These signatures have the potential to change the sphere of animal breeding and further usher the selection programmes in right direction. Technological revolution and recent strides made in genomic studies has opened the routes for the identification of selection signatures. Numerous statistical approaches and bioinformatics tools have been developed to detect the selection signature. Consequently, studies across years have identified candidate genes under selection region found associated with numerous traits which have a say in adaptation to high-altitude environment. This makes it pertinent to have a better understanding about the selection signature, the ways to identify and how to utilize them for betterment of livestock populations as well as farmers. This review takes a closer look into the general concept, various methodologies, and bioinformatics tools commonly employed in selection signature studies and summarize the results of recent selection signature studies related to high-altitude adaptation in various livestock species. This review will serve as an informative and useful insight for researchers and students in the field of animal breeding and evolutionary biology.

Supergenes are not necessary to explain the maintenance of complex alternative phenotypes

Evolutionary biology aims to explain the diversity seen in nature. Evolutionary theory provides frameworks to understand how simple polymorphisms or continuous variation are maintained, but phenotypes inherited as discrete suites of quantitative traits are difficult to fit into this framework. Supergenes have been proposed as a solution to this problem-if causal genes are co-located, they can be inherited as if a single gene, thus bridging the gap between simple polymorphisms and continuous traits. We develop models to ask: how are critical supergenes for maintaining phenotypic diversity? In our simplest model, without explicit genetic architectures, three alternative reproductive morphs are maintained in many of the parameter combinations we evaluated. For these same parameter values, models with demographic stochasticity, recombination and mutation (but without explicit genetic architecture) maintained only two of these three morphs, with stochasticity determining which morphs persisted. With explicit genetic architectures, regardless of whether causal loci were co-located in a supergene or distributed randomly, this stochasticity in which morphs are maintained was reduced. Even when phenotypic variation was lost, genetic diversity was maintained. Altogether, categorical traits with polygenic bases exhibited similar evolutionary dynamics to those determined by supergenes. Our work suggests that supergenes are not the only answer to the puzzle of how discrete polygenic phenotypic variation is maintained.

Scalable CNN-based classification of selective sweeps using derived allele frequencies

MOTIVATION

Selective sweeps can successfully be distinguished from neutral genetic data using summary statistics and likelihood-based methods that analyze single nucleotide polymorphisms (SNPs). However, these methods are sensitive to confounding factors, such as severe population bottlenecks and old migration. By virtue of machine learning, and specifically convolutional neural networks (CNNs), new accurate classification models that are robust to confounding factors have been recently proposed. However, such methods are more computationally expensive than summary-statistic-based ones, yielding them impractical for processing large-scale genomic data. Moreover, SNP data are frequently preprocessed to improve classification accuracy, further exacerbating the long analysis times.

RESULTS

To this end, we propose a 1D CNN-based model, dubbed FAST-NN, that does not require any preprocessing while using only derived allele frequencies instead of summary statistics or raw SNP data, thereby yielding a sample-size-invariant, scalable solution. We evaluated several data fusion approaches to account for the variance of the density of genetic diversity across genomic regions (a selective sweep signature), and performed an extensive neural architecture search based on a state-of-the-art reference network architecture (SweepNet). The resulting model, FAST-NN, outperforms the reference architecture by up to 12% inference accuracy over all challenging evolutionary scenarios with confounding factors that were evaluated. Moreover, FAST-NN is between 30× and 259× faster on a single CPU core, and between 2.0× and 6.2× faster on a GPU, when processing sample sizes between 128 and 1000 samples. Our work paves the way for the practical use of CNNs in large-scale selective sweep detection.

AVAILABILITY AND IMPLEMENTATION

https://github.com/SjoerdvandenBelt/FAST-NN.

Genome resequencing reveals population divergence and local adaptation of blacklegged ticks in the United States

Tick vectors and tick-borne disease are increasingly impacting human populations globally. An important challenge is to understand tick movement patterns, as this information can be used to improve management and predictive modelling of tick population dynamics. Evolutionary analysis of genetic divergence, gene flow and local adaptation provides insight on movement patterns at large spatiotemporal scales. We develop low coverage, whole genome resequencing data for 92 blacklegged ticks, Ixodes scapularis, representing range-wide variation across the United States. Through analysis of population genomic data, we find that tick populations are structured geographically, with gradual isolation by distance separating three population clusters in the northern United States, southeastern United States and a unique cluster represented by a sample from Tennessee. Populations in the northern United States underwent population contractions during the last glacial period and diverged from southern populations at least 50 thousand years ago. Genome scans of selection provide strong evidence of local adaptation at genes responding to host defences, blood-feeding and environmental variation. In addition, we explore the potential of low coverage genome sequencing of whole-tick samples for documenting the diversity of microbial pathogens and recover important tick-borne pathogens such as Borrelia burgdorferi. The combination of isolation by distance and local adaptation in blacklegged ticks demonstrates that gene flow, including recent expansion, is limited to geographical scales of a few hundred kilometres.

Genome-wide relaxation of selection and the evolution of the island syndrome in Orkney voles

Island populations often experience different ecological and demographic conditions than their counterparts on the continent, resulting in divergent evolutionary forces affecting their genomes. Random genetic drift and selection both may leave their imprints on island populations, although the relative impact depends strongly on the specific conditions. Here we address their contributions to the island syndrome in a rodent with an unusually clear history of isolation. Common voles (Microtus arvalis) were introduced by humans on the Orkney archipelago north of Scotland >5000 years ago and rapidly evolved to exceptionally large size. Our analyses show that the genomes of Orkney voles were dominated by genetic drift, with extremely low diversity, variable Tajima's D, and very high divergence from continental conspecifics. Increased d N/d S ratios over a wide range of genes in Orkney voles indicated genome-wide relaxation of purifying selection. We found evidence of hard sweeps on key genes of the lipid metabolism pathway only in continental voles. The marked increase of body size in Orkney-a typical phenomenon of the island syndrome-may thus be associated to the relaxation of positive selection on genes related to this pathway. On the other hand, a hard sweep on immune genes of Orkney voles likely reflects the divergent ecological conditions and possibly the history of human introduction. The long-term isolated Orkney voles show that adaptive changes may still impact the evolutionary trajectories of such populations despite the pervasive consequences of genetic drift at the genome level.

Signatures of positive selection after the introduction of genomic selection in the Finnish Ayrshire population

The Finnish Ayrshire (FAY) belongs to the Nordic Red breeds and is characterized by high milk yield, high milk components, good fertility, and functional conformation. The FAY breeding program is based on genomic selection. Despite the benefits of selection on breeding values, autozygosity in the genome may increase due to selection, and increased autozygosity may cause inbreeding depression in selected traits. However, there is lack of studies concerning selection signatures in the FAY after genomic selection introduction. The aim of this study was to identify signatures of selection in FAY after the introduction of genomic selection. Genomic data included 45,834 SNPs. The genotyped animals were divided into 2 groups: animals born before genomic selection introduction (6,108 cows) and animals born after genomic selection introduction (47,361 cows). We identified the selection signatures using 3 complementary methods: 2 based on identification of selection signatures from runs of homozygosity (ROH) islands and one based on the decay of site-specific extended haplotype between populations at SNP sites (Rsb). In total, we identified 34 ROH islands on chromosomes 1, 3, 6, 8, 12-15, 17, 19, 22, and 26 in FAY animals born before genomic selection (between 1980 and 2011) and 30 ROH islands on chromosomes 1-3, 13-17, 22, and 25-26 in FAY animals born after genomic selection introduction (between 2015 and 2020). We additionally detected 22 ΔROH islands on chromosomes 2-3, 11, 13, 14, 16, 18, 20, and 25-26. Finally, a total of 31 Rsb regions on chromosomes 2, 3, 14, 18, 20, and 25 were identified. Based on the results, genomic selection has favored certain alleles and haplotypes on genomic regions related to traits relevant in the FAY breeding program: milk production, fertility, growth, beef production traits, and feed efficiency. Several genes related to these traits (e.g., PLA2G4A, MECR, CHUK, COX15, RICTOR, SHISA9, and SEMA4G) overlapped or partially overlapped the observed selection signature regions. The association of genotypes within these regions and their effects on traits relevant in the FAY breeding program should be studied and genetic regions undergoing selection monitored in the FAY population.

Approximate Bayesian computational methods to estimate the strength of divergent selection in population genomics models

Statistical estimation of parameters in large models of evolutionary processes is often too computationally inefficient to pursue using exact model likelihoods, even with single-nucleotide polymorphism (SNP) data, which offers a way to reduce the size of genetic data while retaining relevant information. Approximate Bayesian Computation (ABC) to perform statistical inference about parameters of large models takes the advantage of simulations to bypass direct evaluation of model likelihoods. We develop a mechanistic model to simulate forward-in-time divergent selection with variable migration rates, modes of reproduction (sexual, asexual), length and number of migration-selection cycles. We investigate the computational feasibility of ABC to perform statistical inference and study the quality of estimates on the position of loci under selection and the strength of selection. To expand the parameter space of positions under selection, we enhance the model by implementing an outlier scan on summarized observed data. We evaluate the usefulness of summary statistics well-known to capture the strength of selection, and assess their informativeness under divergent selection. We also evaluate the effect of genetic drift with respect to an idealized deterministic model with single-locus selection. We discuss the role of the recombination rate as a confounding factor in estimating the strength of divergent selection, and emphasize its importance in break down of linkage disequilibrium (LD). We answer the question for which part of the parameter space of the model we recover strong signal for estimating the selection, and determine whether population differentiation-based summary statistics or LD-based summary statistics perform well in estimating selection.

Dissecting the genomic regions of selection on the X chromosome in different cattle breeds

Mammalian X and Y chromosomes independently evolved from various autosomes approximately 300 million years ago (MYA). To fully understand the relationship between genomic composition and phenotypic diversity arising due to the course of evolution, we have scanned regions of selection signatures on the X chromosome in different cattle breeds. In this study, we have prepared the datasets of 184 individuals of different cattle breeds and explored the complete X chromosome by utilizing four within-population and two between-population methods. There were 23, 25, 30, 17, 17, and 12 outlier regions identified in Tajima's D, CLR, iHS, ROH, FST, and XP-EHH. Bioinformatics analysis showed that these regions harbor important candidate genes like AKAP4 for reproduction in Brown Swiss, MBTS2 for production traits in Brown Swiss and Guernsey, CXCR3 and CITED1 for health traits in Jersey and Nelore, and BMX and CD40LG for regulation of X chromosome inactivation in Nelore and Gir. We identified genes shared among multiple methods, such as TRNAC-GCA and IL1RAPL1, which appeared in Tajima's D, ROH, and iHS analyses. The gene TRNAW-CCA was found in ROH, CLR and iHS analyses. The X chromosome exhibits a distinctive interaction between demographic factors and genetic variations, and these findings may provide new insight into the X-linked selection in different cattle breeds.

Two-speed genomes of Epichloe fungal pathogens show contrasting signatures of selection between species and across populations

Antagonistic selection between pathogens and their hosts can drive rapid evolutionary change and leave distinct molecular footprints of past and ongoing selection in the genomes of the interacting species. Despite an increasing availability of tools able to identify signatures of selection, the genetic mechanisms underlying coevolutionary interactions and the specific genes involved are still poorly understood, especially in heterogeneous natural environments. We searched the genomes of two species of Epichloe plant pathogen for evidence of recent selection. The Epichloe genus includes highly host-specific species that can sterilize their grass hosts. We performed selection scans using genome-wide SNP data from seven natural populations of two co-occurring Epichloe sibling species specialized on different hosts. We found evidence of recent (and ongoing) selective sweeps across the genome in both species. However, selective sweeps were more abundant in the species with a larger effective population size. Sweep regions often overlapped with highly polymorphic AT-rich regions supporting the role of these genome compartments in adaptive evolution. Although most loci under selection were specific to individual populations, we could also identify several candidate genes targeted by selection in sweep regions shared among populations. The genes encoded small secreted proteins typical of fungal effectors and cell wall-degrading enzymes. By investigating the genomic signatures of selection across multiple populations and species, this study contributes to our understanding of complex adaptive processes in natural plant pathogen systems.

Comprehensive selection signature analyses in dairy cattle exploiting purebred and crossbred genomic data

The main objective of the current research was to locate, annotate, and highlight specific areas of the bovine genome that are undergoing intense positive selection. Here, we are analyzing selection signatures in crossbred (Bos taurus X Bos indicus), taurine (Bos taurus), and indicine (Bos indicus) cattle breeds. Indicine cattle breeds found throughout India are known for their higher heat tolerance and disease resilience. More breeds and more methods can provide a better understanding of the selection signature. So, we have worked on nine distinct cattle breeds utilizing seven different summary statistics, which is a fairly extensive approach. In this study, we carried out a thorough genome-wide investigation of selection signatures using bovine 50K SNP data. We have included the genotyped data of two taurine, two crossbreds, and five indicine cattle breeds, for a total of 320 animals. During the 1950s, these indicine (cebuine) cattle breeds were exported with the aim of enhancing the resilience of taurine breeds in Western countries. For this study, we employed seven summary statistics, including intra-population, i.e., Tajima's D, CLR, iHS, and ROH and inter-population statistics, i.e., FST, XP-EHH, and Rsb. The NCBI database, PANTHER 17.0, and CattleQTL database were used for annotation after finding the important areas under selection. Some genes, including EPHA6, CTNNA2, NPFFR2, HS6ST3, NPR3, KCNIP4, LIPK, SDCBP, CYP7A1, NSMAF, UBXN2B, UGDH, UBE2K, and DAB1, were shown to be shared by three or more different approaches. Therefore, it gives evidence of the most intense selection in these areas. These genes are mostly linked to milk production and adaptability traits. This study also reveals selection regions that contain genes which are crucial to numerous biological functions, including those associated with milk production, coat color, glucose metabolism, oxidative stress response, immunity and circadian rhythms.

Candidate signatures of positive selection for environmental adaptation in indigenous African cattle: A review

Environmental adaptation traits of indigenous African cattle are increasingly being investigated to respond to the need for sustainable livestock production in the context of unpredictable climatic changes. Several studies have highlighted genomic regions under positive selection probably associated with adaptation to environmental challenges (e.g. heat stress, trypanosomiasis, tick and tick-borne diseases). However, little attention has focused on pinpointing the candidate causative variant(s) controlling the traits. This review compiled information from 22 studies on signatures of positive selection in indigenous African cattle breeds to identify regions under positive selection. We highlight some key candidate genome regions and genes of relevance to the challenges of living in extreme environments (high temperature, high altitude, high infectious disease prevalence). They include candidate genes involved in biological pathways relating to innate and adaptive immunity (e.g. BoLAs, SPAG11, IL1RL2 and GFI1B), heat stress (e.g. HSPs, SOD1 and PRLH) and hypoxia responses (e.g. BDNF and INPP4A). Notably, the highest numbers of candidate regions are found on BTA3, BTA5 and BTA7. They overlap with genes playing roles in several biological functions and pathways. These include but are not limited to growth and feed intake, cell stability, protein stability and sweat gland development. This review may further guide targeted genome studies aiming to assess the importance of candidate causative mutations, within regulatory and protein-coding genome regions, to further understand the biological mechanisms underlying African cattle's unique adaption.

Understanding anthelmintic resistance in livestock using "omics" approaches

Widespread and improper use of various anthelmintics, genetic, and epidemiological factors has resulted in anthelmintic-resistant (AR) helminth populations in livestock. This is currently quite common globally in different livestock animals including sheep, goats, and cattle to gastrointestinal nematode (GIN) infections. Therefore, the mechanisms underlying AR in parasitic worm species have been the subject of ample research to tackle this challenge. Current and emerging technologies in the disciplines of genomics, transcriptomics, metabolomics, and proteomics in livestock species have advanced the understanding of the intricate molecular AR mechanisms in many major parasites. The technologies have improved the identification of possible biomarkers of resistant parasites, the ability to find actual causative genes, regulatory networks, and pathways of parasites governing the AR development including the dynamics of helminth infection and host-parasite infections. In this review, various "omics"-driven technologies including genome scan, candidate gene, quantitative trait loci, transcriptomic, proteomic, and metabolomic approaches have been described to understand AR of parasites of veterinary importance. Also, challenges and future prospects of these "omics" approaches are also discussed.

Landmarks in the history of selective sweeps

Half a century ago, a seminal article on the hitchhiking effect by Smith and Haigh inaugurated the concept of the selection signature. Selective sweeps are characterised by the rapid spread of an advantageous genetic variant through a population and hence play an important role in shaping evolution and research on genetic diversity. The process by which a beneficial allele arises and becomes fixed in a population, leading to a increase in the frequency of other linked alleles, is known as genetic hitchhiking or genetic draft. Kimura's neutral theory and hitchhiking theory are complementary, with Kimura's neutral evolution as the 'null model' and positive selection as the 'signal'. Both are widely accepted in evolution, especially with genomics enabling precise measurements. Significant advances in genomic technologies, such as next-generation sequencing, high-density SNP arrays and powerful bioinformatics tools, have made it possible to systematically investigate selection signatures in a variety of species. Although the history of selection signatures is relatively recent, progress has been made in the last two decades, owing to the increasing availability of large-scale genomic data and the development of computational methods. In this review, we embark on a journey through the history of research on selective sweeps, ranging from early theoretical work to recent empirical studies that utilise genomic data.

Genome-environment association analyses reveal geographically restricted adaptive divergence across the range of the widespread Eurasian carnivore Lynx lynx (Linnaeus, 1758)

Local adaptations to the environment are an important aspect of the diversity of a species and their discovery, description and quantification has important implications for the fields of taxonomy, evolutionary and conservation biology. In this study, we scan genomes from several populations across the distributional range of the Eurasian lynx, with the objective of finding genomic windows under positive selection which may underlie local adaptations to different environments. A total of 394 genomic windows are found to be associated to local environmental conditions, and they are enriched for genes involved in metabolism, behaviour, synaptic organization and neural development. Adaptive genetic structure, reconstructed from SNPs in candidate windows, is considerably different than the neutral genetic structure of the species. A widespread adaptively homogeneous group is recovered occupying areas of harsher snow and temperature climatic conditions in the north-western, central and eastern parts of the distribution. Adaptively divergent populations are recovered in the westernmost part of the range, especially within the Baltic population, but also predicted for different patches in the western and southern part of the range, associated with different snow and temperature regimes. Adaptive differentiation driven by climate does not correlate much with the subspecies taxonomic delimitations, suggesting that subspecific divergences are mostly driven by neutral processes of genetic drift and gene flow. Our results will aid the selection of source populations for assisted gene flow or genetic rescue programs by identifying what climatic patterns to look for as predictors of pre-adaptation of individuals. Particularly, the Carpathian population is confirmed as the best source of individuals for the genetic rescue of the endangered, isolated and genetically eroded Balkan population. Additionally, reintroductions in central and western Europe, currently based mostly on Carpathian lynxes, could consider the Baltic population as an additional source to increase adaptive variation and likely improve adaptation to their milder climate.

Power of neutrality tests for detecting natural selection

Detection of natural selection is one of the main interests in population genetics. Thus, many tests have been developed for detecting natural selection using genomic data. Although it is recognized that the utility of tests depends on several evolutionary factors, such as the timing of selection, strength of selection, frequency of selected alleles, demographic events, and initial frequency of selected allele when selection started acting (softness of selection), the relationships between such evolutionary factors and the power of tests are not yet entirely clear. In this study, we investigated the power of 4 tests: Tajiama's D, Fay and Wu's H, relative extended haplotype homozygosity (rEHH), and integrated haplotype score (iHS), under ranges of evolutionary parameters and demographic models to quantitatively expand the understanding of approaches for detecting selection. The results show that each test detects selection within a limited parameter range, and there are still wide ranges of parameters for which none of these tests work effectively. In addition, the parameter space in which each test shows the highest power overlaps the empirical results of previous research. These results indicate that our present perspective of adaptation is limited to only a part of actual adaptation.

Analysis of polygenic selection in purebred and crossbred pig genomes using generation proxy selection mapping

BACKGROUND

Artificial selection on quantitative traits using breeding values and selection indices in commercial livestock breeding populations causes changes in allele frequency over time at hundreds or thousands of causal loci and the surrounding genomic regions. In population genetics, this type of selection is called polygenic selection. Researchers and managers of pig breeding programs are motivated to understand the genetic basis of phenotypic diversity across genetic lines, breeds, and populations using selection mapping analyses. Here, we applied generation proxy selection mapping (GPSM), a genome-wide association analysis of single nucleotide polymorphism (SNP) genotypes (38,294-46,458 markers) of birth date, in four pig populations (15,457, 15,772, 16,595 and 8447 pigs per population) to identify loci responding to artificial selection over a period of five to ten years. Gene-drop simulation analyses were conducted to provide context for the GPSM results. Selected loci within and across each population of pigs were compared in the context of swine breeding objectives.

RESULTS

The GPSM identified 49 to 854 loci as under selection (Q-values less than 0.10) across 15 subsets of pigs based on combinations of populations. The number of significant associations increased when data were pooled across populations. In addition, several significant associations were identified in more than one population. These results indicate concurrent selection objectives, similar genetic architectures, and shared causal variants responding to selection across these pig populations. Negligible error rates (less than or equal to 0.02%) of false-positive associations were found when testing GPSM on gene-drop simulated genotypes, suggesting that GPSM distinguishes selection from random genetic drift in actual pig populations.

CONCLUSIONS

This work confirms the efficacy and the negligible error rates of the GPSM method in detecting selected loci in commercial pig populations. Our results suggest shared selection objectives and genetic architectures across swine populations. The identified polygenic selection highlights loci that are important to swine production.

Multiple domestications of Asian rice

The origin of domesticated Asian rice (Oryza sativa L.) has been controversial for more than half a century. The debates have focused on two leading hypotheses: a single domestication event in China or multiple domestication events in geographically separate areas. These two hypotheses differ in their predicted history of genes/alleles selected during domestication. Here we amassed a dataset of 1,578 resequenced genomes, including an expanded sample of wild rice from throughout its geographic range. We identified 993 selected genes that generated phylogenetic trees on which japonica and indica formed a monophyletic group, suggesting that the domestication alleles of these genes originated only once in either japonica or indica. Importantly, the domestication alleles of most selected genes (~80%) stemmed from wild rice in China, but the domestication alleles of a substantial minority of selected genes (~20%) originated from wild rice in South and Southeast Asia, demonstrating separate domestication events of Asian rice.

Genome-wide scans for selective sweeps using convolutional neural networks

MOTIVATION

Recent methods for selective sweep detection cast the problem as a classification task and use summary statistics as features to capture region characteristics that are indicative of a selective sweep, thereby being sensitive to confounding factors. Furthermore, they are not designed to perform whole-genome scans or to estimate the extent of the genomic region that was affected by positive selection; both are required for identifying candidate genes and the time and strength of selection.

RESULTS

We present ASDEC (https://github.com/pephco/ASDEC), a neural-network-based framework that can scan whole genomes for selective sweeps. ASDEC achieves similar classification performance to other convolutional neural network-based classifiers that rely on summary statistics, but it is trained 10× faster and classifies genomic regions 5× faster by inferring region characteristics from the raw sequence data directly. Deploying ASDEC for genomic scans achieved up to 15.2× higher sensitivity, 19.4× higher success rates, and 4× higher detection accuracy than state-of-the-art methods. We used ASDEC to scan human chromosome 1 of the Yoruba population (1000Genomes project), identifying nine known candidate genes.

Reconstructing the colonization history of Indo-Pacific bottlenose dolphins (Tursiops aduncus) in Northwestern Australia

Bottlenose dolphins (Tursiops spp.) are found in waters around Australia, with T. truncatus typically occupying deeper, more oceanic habitat, while T. aduncus occur in shallower, coastal waters. Little is known about the colonization history of T. aduncus along the Western Australian coastline; however, it has been hypothesized that extant populations are the result of an expansion along the coastline originating from a source in the north of Australia. To investigate the history of coastal T. aduncus populations in the area, we generated a genomic SNP dataset using a double-digest restriction-site-associated DNA (ddRAD) sequencing approach. The resulting dataset consisted of 103,201 biallelic SNPs for 112 individuals which were sampled from eleven coastal and two offshore sites between Shark Bay and Cygnet Bay, Western Australia. Our population genomic analyses showed a pattern consistent with the proposed source in the north with significant isolation by distance along the coastline, as well as a reduction in genomic diversity measures along the coastline with Shark Bay showing the most pronounced reduction. Our demographic analysis indicated that the expansion of T. aduncus along the coastline began around the last glacial maximum and progressed southwards with the Shark Bay population being founded only 13 kya. Our results are in line with coastal colonization histories inferred for Tursiops globally, highlighting the ability of delphinids to rapidly colonize novel coastal niches as habitat is released during glacial cycle-related global sea level and temperature changes.

Genetic architecture of a pollinator shift and its fate in secondary hybrid zones of two Petunia species

BACKGROUND

Theory suggests that the genetic architecture of traits under divergent natural selection influences how easily reproductive barriers evolve and are maintained between species. Divergently selected traits with a simple genetic architecture (few loci with major phenotypic effects) should facilitate the establishment and maintenance of reproductive isolation between species that are still connected by some gene flow. While empirical support for this idea appears to be mixed, most studies test the influence of trait architectures on reproductive isolation only indirectly. Petunia plant species are, in part, reproductively isolated by their different pollinators. To investigate the genetic causes and consequences of this ecological isolation, we deciphered the genetic architecture of three floral pollination syndrome traits in naturally occurring hybrids between the widespread Petunia axillaris and the highly endemic and endangered P. exserta.

RESULTS

Using population genetics, Bayesian linear mixed modelling and genome-wide association studies, we found that the three pollination syndrome traits vary in genetic architecture. Few genome regions explain a majority of the variation in flavonol content (defining UV floral colour) and strongly predict the trait value in hybrids irrespective of interspecific admixture in the rest of their genomes. In contrast, variation in pistil exsertion and anthocyanin content (defining visible floral colour) is controlled by many genome-wide loci. Opposite to flavonol content, the genome-wide proportion of admixture between the two species predicts trait values in their hybrids. Finally, the genome regions strongly associated with the traits do not show extreme divergence between individuals representing the two species, suggesting that divergent selection on these genome regions is relatively weak within their contact zones.

CONCLUSIONS

Among the traits analysed, those with a more complex genetic architecture are best maintained in association with the species upon their secondary contact. We propose that this maintained genotype-phenotype association is a coincidental consequence of the complex genetic architectures of these traits: some of their many underlying small-effect loci are likely to be coincidentally linked with the actual barrier loci keeping these species partially isolated upon secondary contact. Hence, the genetic architecture of a trait seems to matter for the outcome of hybridization not only then when the trait itself is under selection.

Genomic diversity and signals of selection processes in wild and farm-reared red-legged partridges (Alectoris rufa)

The genetic dynamics of wild populations with releases of farm-reared reinforcements are very complex. These releases can endanger wild populations through genetic swamping or by displacing them. We assessed the genomic differences between wild and farm-reared red-legged partridges (Alectoris rufa) and described differential selection signals between both populations. We sequenced the whole genome of 30 wild and 30 farm-reared partridges. Both partridges had similar nucleotide diversity (π). Farm-reared partridges had a more negative Tajima's D and more and longer regions of extended haplotype homozygosity than wild partridges. We observed higher inbreeding coefficients (F_IS and F_ROH) in wild partridges. Selective sweeps (Rsb) were enriched with genes that contribute to the reproductive, skin and feather colouring, and behavioural differences between wild and farm-reared partridges. The analysis of genomic diversity should inform future decisions for the preservation of wild populations.

Selection signatures for fiber production in commercial species: A review

Natural fibers derived from diverse animal species have gained increased attention in recent years due to their favorable environmental effects, long-term sustainability benefits, and remarkable physical and mechanical properties that make them valuable raw materials used for textile and non-textile production. Domestication and selective breeding for the economically significant fiber traits play an imperative role in shaping the genomes and, thus, positively impact the overall productivity of the various fiber-producing species. These selection pressures leave unique footprints on the genome due to alteration in the allelic frequencies at specific loci, characterizing selective sweeps. Recent advances in genomics have enabled the discovery of selection signatures across the genome using a variety of methods. The increased demand for 'green products' manufactured from natural fibers necessitates a detailed investigation of the genomes of the various fiber-producing plant and animal species to identify the candidate genes associated with important fiber attributes such as fiber diameter/fineness, color, length, and strength, among others. The objective of this review is to present a comprehensive overview of the concept of selection signature and selective sweeps, discuss the main methods used for its detection, and address the selection signature studies conducted so far in the diverse fiber-producing animal species.

Three perspectives on the prediction of chemical effects in ecosystems

The increasing production, use and emission of synthetic chemicals into the environment represents a major driver of global change. The large number of synthetic chemicals, limited knowledge on exposure patterns and effects in organisms and their interaction with other global change drivers hamper the prediction of effects in ecosystems. However, recent advances in biomolecular and computational methods are promising to improve our capacity for prediction. We delineate three idealised perspectives for the prediction of chemical effects: the suborganismal, organismal and ecological perspective, which are currently largely separated. Each of the outlined perspectives includes essential and complementary theories and tools for prediction but captures only part of the phenomenon of chemical effects. Links between the perspectives may foster predictive modelling of chemical effects in ecosystems and extrapolation between species. A major challenge for the linkage is the lack of data sets simultaneously covering different levels of biological organisation (here referred to as biological levels) as well as varying temporal and spatial scales. Synthesising the three perspectives, some central aspects and associated types of data seem particularly necessary to improve prediction. First, suborganism- and organism-level responses to chemicals need to be recorded and tested for relationships with chemical groups and organism traits. Second, metrics that are measurable at many biological levels, such as energy, need to be scrutinised for their potential to integrate across levels. Third, experimental data on the simultaneous response over multiple biological levels and spatiotemporal scales are required. These could be collected in nested and interconnected micro- and mesocosm experiments. Lastly, prioritisation of processes involved in the prediction framework needs to find a balance between simplification and capturing the essential complexity of a system. For example, in some cases, eco-evolutionary dynamics and interactions may need stronger consideration. Prediction needs to move from a static to a real-world eco-evolutionary view.

Evidence of selection in the uncoupling protein 1 gene region suggests local adaptation to solar irradiance in savannah monkeys (Chlorocebus spp.)

In the last 300 thousand years, the genus Chlorocebus expanded from equatorial Africa into the southernmost latitudes of the continent, where colder climate was a probable driver of natural selection. We investigated population-level genetic variation in the mitochondrial uncoupling protein 1 (UCP1) gene region-implicated in non-shivering thermogenesis (NST)-in 73 wild savannah monkeys from three taxa representing this southern expansion (Chlorocebus pygerythrus hilgerti, Chlorocebus cynosuros and Chlorocebus pygerythrus pygerythrus) ranging from Kenya to South Africa. We found 17 single nucleotide polymorphisms with extended haplotype homozygosity consistent with positive selective sweeps, 10 of which show no significant linkage disequilibrium with each other. Phylogenetic generalized least-squares modelling with ecological covariates suggest that most derived allele frequencies are significantly associated with solar irradiance and winter precipitation, rather than overall low temperatures. This selection and association with irradiance is demonstrated by a relatively isolated population in the southern coastal belt of South Africa. We suggest that sunbathing behaviours common to savannah monkeys, in combination with the strength of solar irradiance, may mediate adaptations to thermal stress via NST among savannah monkeys. The variants we discovered all lie in non-coding regions, some with previously documented regulatory functions, calling for further validation and research.

Analysis on the desert adaptability of indigenous sheep in the southern edge of Taklimakan Desert

The southern margin of the Taklimakan Desert is characterized by low rainfall, heavy sandstorms, sparse vegetation and harsh ecological environment. The indigenous sheep in this area are rich in resources, with the advantages of perennial estrus and good resistance to stress in most sheep. Exploring the molecular markers of livestock adaptability in this environment will provide the molecular basis for breeding research to cope with extreme future changes in the desert environment. In this study, we analyzed the population genetic structure and linkage imbalance of five sheep breeds with three different agricultural geographic characteristics using four complementary genomic selection signals: fixation index (FST), cross-population extended haplotype homozygosity (xp-EHH), Rsb (extended haplotype homozygosity between-populations) and iHS (integrated haplotype homozygosity score). We used Illumina Ovine SNP 50K Genotyping BeadChip Array, and gene annotation and enrichment analysis were performed on selected regions of the obtained genome. The ovary of Qira Black sheep (Follicular phase, Luteal phase, 30th day of pregnancy, 45th day of pregnancy) was collected, and the differentially expressed genes were screened by transcriptomic sequencing. Genome-wide selective sweep results and transcriptome data were combined for association analysis to obtain candidate genes associated with perennial estrus and stable reproduction. In order to verify the significance of the results, 15 resulting genes were randomly selected for fluorescence quantitative analysis. The results showed that Dolang sheep and Qira Black sheep evolved from Kazak sheep. Linkage disequilibrium analysis showed that the decay rate of sheep breeds in the Taklimakan Desert was higher than that in Yili grassland. The signals of FST, xp-EHH, Rsb and iHS detected 526, 332, 308 and 408 genes, respectively, under the threshold of 1% and 17 overlapping genes under the threshold of 5%. A total of 29 genes were detected in association analysis of whole-genome and transcriptome data. This study reveals the genetic mechanism of perennial estrus and environmental adaptability of indigenous sheep breeds in the Taklimakan Desert. It provides a theoretical basis for the conservation and exploitation of genetic resources of indigenous sheep breeds in extreme desert environment. This provides a new perspective for the quick adaptation of sheep and other mammals to extreme environments and future climate changes.

Population-specific, recent positive selection signatures in cultivated Cucumis sativus L. (cucumber)

Population-specific, positive selection promotes the diversity of populations and drives local adaptations in the population. However, little is known about population-specific, recent positive selection in the populations of cultivated cucumber (Cucumis sativus L.). Based on a genomic variation map of individuals worldwide, we implemented a Fisher’s combination method by combining 4 haplotype-based approaches: integrated haplotype score (iHS), number of segregating sites by length (nSL), cross-population extended haplotype homozygosity (XP-EHH), and Rsb. Overall, we detected 331, 2,147, and 3,772 population-specific, recent positive selective sites in the East Asian, Eurasian, and Xishuangbanna populations, respectively. Moreover, we found that these sites were related to processes for reproduction, response to abiotic and biotic stress, and regulation of developmental processes, indicating adaptations to their microenvironments. Meanwhile, the selective genes associated with traits of fruits were also observed, such as the gene related to the shorter fruit length in the Eurasian population and the gene controlling flesh thickness in the Xishuangbanna population. In addition, we noticed that soft sweeps were common in the East Asian and Xishuangbanna populations. Genes involved in hard or soft sweeps were related to developmental regulation and abiotic and biotic stress resistance. Our study offers a comprehensive candidate dataset of population-specific, selective signatures in cultivated cucumber populations. Our methods provide guidance for the analysis of population-specific, positive selection. These findings will help explore the biological mechanisms of adaptation and domestication of cucumber.

Detecting Local Adaptation between North and South European Atlantic Salmon Populations

Pollution and other anthropogenic effects have driven a decrease in Atlantic salmon (Salmo salar) in the Iberian Peninsula. The restocking effort carried out in the 1980s, with salmon from northern latitudes with the aim of mitigating the decline of native populations, failed, probably due to the deficiency in adaptation of foreign salmon from northern Europe to the warm waters of the Iberian Peninsula. This result would imply that the Iberian populations of Atlantic salmon have experienced local adaptation in their past evolutionary history, as has been described for other populations of this species and other salmonids. Local adaptation can occur by divergent selections between environments, favoring the fixation of alleles that increase the fitness of a population in the environment it inhabits relative to other alleles favored in another population. In this work, we compared the genomes of different populations from the Iberian Peninsula (Atlantic and Cantabric basins) and Scotland in order to provide tentative evidence of candidate SNPs responsible for the adaptive differences between populations, which may explain the failures of restocking carried out during the 1980s. For this purpose, the samples were genotyped with a 220,000 high-density SNP array (Affymetrix) specific to Atlantic salmon. Our results revealed potential evidence of local adaptation for North Spanish and Scottish populations. As expected, most differences concerned the comparison of the Iberian Peninsula with Scotland, although there were also differences between Atlantic and Cantabric populations. A high proportion of the genes identified are related to development and cellular metabolism, DNA transcription and anatomical structure. A particular SNP was identified within the NADP-dependent malic enzyme-2 (_mMEP-2*), previously reported by independent studies as a candidate for local adaptation in salmon from the Iberian Peninsula. Interestingly, the corresponding SNP within the _mMEP-2* region was consistent with a genomic pattern of divergent selection.

Selection Signature Analyses Revealed Genes Associated With Adaptation, Production, and Reproduction in Selected Goat Breeds in Kenya

Artificial and natural selection in livestock is expected to leave unique footprints on their genomes. Goat breeds in Kenya have evolved for survival, breeding, and production in various harsh ecological areas, and their genomes are likely to have acquired unique alleles for adaptation to such diverse production environments and other traits of economic importance. To investigate signals of selection for some selected goat breeds in Kenya, Alpine (n = 29), Galla (n = 12), Saanen (n = 24), and Toggenburg (n = 31) were considered. A total of 53,347 single-nucleotide polymorphisms (SNPs) generated using the Illumina GoatSNP50 BeadChip were analyzed. After quality control, 47,663 autosomal single-nucleotide polymorphisms remained for downstream analyses. Several complementary approaches were applied for the following analyses: integrated Haplotype Score (iHS), cross-population-extended haplotype homozygosity (XP-EHH), hapFLK, and FLK. A total of 404 top genomic regions were identified across all the four breeds, based on the four complementary analyses. Out of the 16 identified putative selection signature regions by the intersection of multiple-selective signal analyses, most of the putative regions were found to overlap significantly with the iHS and XP-EHH analyses on chromosomes 3, 4, 10, 15, 22, and 26. These regions were enriched with some genes involved in pathways associated directly or indirectly with environmental adaptation regulating immune responses (e.g., HYAL1 and HYAL3), milk production (e.g., LEPR and PDE4B), and adaptability (e.g., MST1 and PCK). The results revealed few intersect between breeds in genomic selection signature regions. In general, this did not present the typical classic selection signatures as predicted due to the complex nature of the traits. The results support that some various selection pressures (e.g., environmental challenges, artificial selection, and genome admixture challenges) have molded the genome of goat breeds in Kenya. Therefore, the research provides new knowledge on the conservation and utilization of these goat genetic resources in Kenya. In-depth research is needed to detect precise genes connected with adaptation and production in goat breeds in Kenya.

Investigation of the Genetic Architecture of Pigs Subjected to Breeding Intensification

Pigs are strategically important animals for the agricultural industry. An assessment of genetic differentiation between pigs, undergone and not undergone to selection intensification, is of particular interest. Our research was conducted on two groups of Large White pigs grown on the same farm but in different years. A total of 165 samples were selected with 78 LW_А (n = 78, the Russian selection) and LW_B (n = 87, a commercial livestock). For genotyping, we used GeneSeek^® GGP Porcine HD Genomic Profiler v1 (Illumina Inc, San Diego, CA, USA). To define breeding characteristics of selection, we used smoothing FST and segment identification of HBD (Homozygous-by-Descent). The results of smoothing FST showed 20 areas of a genome with strong ejection regions of the genome located on all chromosomes except SSC2, SSC3, and SSC8. The average realized autozygosity in Large White pigs of native selection was in (LW_A)—0.21, in LW_В—0.29. LW_А showed 13,338 HBD segments, 171 per one animal, and LW_B—15,747 HBD segments, 181 per one animal. The ejections found by the smoothing FST method were partially localized in the HBD regions. In these areas, the genes ((NCBP1, PLPPR1, GRIN3A, NBEA, TRPC4, HS6ST3, NALCN, SMG6, TTC3, KCNJ6, IKZF2, OBSL1, CARD10, ETV6, VWF, CCND2, TSPAN9, CDH13, CEP128, SERPINA11, PIK3CG, COG5, BCAP29, SLC26A4) were defined. The revealed genes can be of special interest for further studying their influence on an organism of an animal since they can act as candidate genes for selection-significant traits.

Detecting selection using extended haplotype homozygosity (EHH)-based statistics in unphased or unpolarized data

Analysis of population genetic data often includes a search for genomic regions with signs of recent positive selection. One of such approaches involves the concept of extended haplotype homozygosity (EHH) and its associated statistics. These statistics typically require phased haplotypes, and some of them necessitate polarized variants. Here, we unify and extend previously proposed modifications to loosen these requirements. We compare the modified versions with the original ones by measuring the false discovery rate in simulated whole-genome scans and by quantifying the overlap of inferred candidate regions in empirical data. We find that phasing information is indispensable for accurate estimation of within-population statistics (for all but very large samples) and of cross-population statistics for small samples. Ancestry information, in contrast, is of lesser importance for both types of statistic. Our publicly available R package rehh incorporates the modified statistics presented here.

A continent-wide high genetic load in African buffalo revealed by clines in the frequency of deleterious alleles, genetic hitchhiking and linkage disequilibrium

A high genetic load can negatively affect population viability and increase susceptibility to diseases and other environmental stressors. Prior microsatellite studies of two African buffalo (Syncerus caffer) populations in South Africa indicated substantial genome-wide genetic load due to high-frequency occurrence of deleterious alleles. The occurrence of these alleles, which negatively affect male body condition and bovine tuberculosis resistance, throughout most of the buffalo's range were evaluated in this study. Using available microsatellite data (2-17 microsatellite loci) for 1676 animals from 34 localities (from 25°S to 5°N), we uncovered continent-wide frequency clines of microsatellite alleles associated with the aforementioned male traits. Frequencies decreased over a south-to-north latitude range (average per-locus Pearson r = -0.22). The frequency clines coincided with a multilocus-heterozygosity cline (adjusted R2 = 0.84), showing up to a 16% decrease in southern Africa compared to East Africa. Furthermore, continent-wide linkage disequilibrium (LD) at five linked locus pairs was detected, characterized by a high fraction of positive interlocus associations (0.66, 95% CI: 0.53, 0.77) between male-deleterious-trait-associated alleles. Our findings suggest continent-wide and genome-wide selection of male-deleterious alleles driven by an earlier observed sex-chromosomal meiotic drive system, resulting in frequency clines, reduced heterozygosity due to hitchhiking effects and extensive LD due to male-deleterious alleles co-occurring in haplotypes. The selection pressures involved must be high to prevent destruction of allele-frequency clines and haplotypes by LD decay. Since most buffalo populations are stable, these results indicate that natural mammal populations, depending on their genetic background, can withstand a high genetic load.

Genome-wide scans for signatures of selection in Mangalarga Marchador horses using high-throughput SNP genotyping

BACKGROUND

The detection of signatures of selection in genomic regions provides insights into the evolutionary process, enabling discoveries regarding complex phenotypic traits. In this research, we focused on identifying genomic regions affected by different selection pressures, mainly highlighting the recent positive selection, as well as understanding the candidate genes and functional pathways associated with the signatures of selection in the Mangalarga Marchador genome. Besides, we seek to direct the discussion about genes and traits of importance in this breed, especially traits related to the type and quality of gait, temperament, conformation, and locomotor system.

RESULTS

Three different methods were used to search for signals of selection: Tajima's D (TD), the integrated haplotype score (iHS), and runs of homozygosity (ROH). The samples were composed of males (n = 62) and females (n = 130) that were initially chosen considering well-defined phenotypes for gait: picada (n = 86) and batida (n = 106). All horses were genotyped using a 670 k Axiom® Equine Genotyping Array​ (Axiom MNEC670). In total, 27, 104 (chosen), and 38 candidate genes were observed within the signatures of selection identified in TD, iHS, and ROH analyses, respectively. The genes are acting in essential biological processes. The enrichment analysis highlighted the following functions: anterior/posterior pattern for the set of genes (GLI3, HOXC9, HOXC6, HOXC5, HOXC4, HOXC13, HOXC11, and HOXC10); limb morphogenesis, skeletal system, proximal/distal pattern formation, JUN kinase activity (CCL19 and MAP3K6); and muscle stretch response (MAPK14). Other candidate genes were associated with energy metabolism, bronchodilator response, NADH regeneration, reproduction, keratinization, and the immunological system.

CONCLUSIONS

Our findings revealed evidence of signatures of selection in the MM breed that encompass genes acting on athletic performance, limb development, and energy to muscle activity, with the particular involvement of the HOX family genes. The genome of MM is marked by recent positive selection. However, Tajima's D and iHS results point also to the presence of balancing selection in specific regions of the genome.

Population and comparative genetics of thermotolerance divergence between yeast species

Many familiar traits in the natural world-from lions' manes to the longevity of bristlecone pine trees-arose in the distant past, and have long since fixed in their respective species. A key challenge in evolutionary genetics is to figure out how and why species-defining traits have come to be. We used the thermotolerance growth advantage of the yeast Saccharomyces cerevisiae over its sister species Saccharomyces paradoxus as a model for addressing these questions. Analyzing loci at which the S. cerevisiae allele promotes thermotolerance, we detected robust evidence for positive selection, including amino acid divergence between the species and conservation within S. cerevisiae populations. Because such signatures were particularly strong at the chromosome segregation gene ESP1, we used this locus as a case study for focused mechanistic follow-up. Experiments revealed that, in culture at high temperature, the S. paradoxus ESP1 allele conferred a qualitative defect in biomass accumulation and cell division relative to the S. cerevisiae allele. Only genetic divergence in the ESP1 coding region mattered phenotypically, with no functional impact detectable from the promoter. Our data support a model in which an ancient ancestor of S. cerevisiae, under selection to boost viability at high temperature, acquired amino acid variants at ESP1 and many other loci, which have been constrained since then. Complex adaptations of this type hold promise as a paradigm for interspecies genetics, especially in deeply diverged traits that may have taken millions of years to evolve.

Genome-wide analysis of genetic diversity and artificial selection in Large White pigs in Russia

Breeding practices adopted at different farms are aimed at maximizing the profitability of pig farming. In this work, we have analyzed the genetic diversity of Large White pigs in Russia. We compared genomes of historic and modern Large White Russian breeds using 271 pig samples. We have identified 120 candidate regions associated with the differentiation of modern and historic pigs and analyzed genomic differences between the modern farms. The identified genes were associated with height, fitness, conformation, reproductive performance, and meat quality.

Limited Evidence for Parallel Evolution Among Desert-Adapted Peromyscus Deer Mice

Warming climate and increasing desertification urge the identification of genes involved in heat and dehydration tolerance to better inform and target biodiversity conservation efforts. Comparisons among extant desert-adapted species can highlight parallel or convergent patterns of genome evolution through the identification of shared signatures of selection. We generate a chromosome-level genome assembly for the canyon mouse (Peromyscus crinitus) and test for a signature of parallel evolution by comparing signatures of selective sweeps across population-level genomic resequencing data from another congeneric desert specialist (Peromyscus eremicus) and a widely distributed habitat generalist (Peromyscus maniculatus), that may be locally adapted to arid conditions. We identify few shared candidate loci involved in desert adaptation and do not find support for a shared pattern of parallel evolution. Instead, we hypothesize divergent molecular mechanisms of desert adaptation among deer mice, potentially tied to species-specific historical demography, which may limit or enhance adaptation. We identify a number of candidate loci experiencing selective sweeps in the P. crinitus genome that are implicated in osmoregulation (Trypsin, Prostasin) and metabolic tuning (Kallikrein, eIF2-alpha kinase GCN2, APPL1/2), which may be important for accommodating hot and dry environmental conditions.

Candidate Genes for the High-Altitude Adaptations of Two Mountain Pine Taxa

Mountain plants, challenged by vegetation time contractions and dynamic changes in environmental conditions, developed adaptations that help them to balance their growth, reproduction, survival, and regeneration. However, knowledge regarding the genetic basis of species adaptation to higher altitudes remain scarce for most plant species. Here, we attempted to identify such corresponding genomic regions of high evolutionary importance in two closely related European pines, Pinus mugo and P. uncinata, contrasting them with a reference lowland relative—P. sylvestris. We genotyped 438 samples at thousands of single nucleotide polymorphism (SNP) markers, tested their genetic differentiation and population structure followed by outlier detection and gene ontology annotations. Markers clearly differentiated the species and uncovered patterns of population structure in two of them. In P. uncinata three Pyrenean sites were grouped together, while two outlying populations constituted a separate cluster. In P. sylvestris, Spanish population appeared distinct from the remaining four European sites. Between mountain pines and the reference species, 35 candidate genes for altitude-dependent selection were identified, including such encoding proteins responsible for photosynthesis, photorespiration and cell redox homeostasis, regulation of transcription, and mRNA processing. In comparison between two mountain pines, 75 outlier SNPs were found in proteins involved mainly in the gene expression and metabolism.

Genomic Analyses of Globodera pallida, A Quarantine Agricultural Pathogen in Idaho

Globodera pallida is among the most significant plant-parasitic nematodes worldwide, causing major damage to potato production. Since it was discovered in Idaho in 2006, eradication efforts have aimed to contain and eradicate G. pallida through phytosanitary action and soil fumigation. In this study, we investigated genome-wide patterns of G. pallida genetic variation across Idaho fields to evaluate whether the infestation resulted from a single or multiple introduction(s) and to investigate potential evolutionary responses since the time of infestation. A total of 53 G. pallida samples (~1,042,000 individuals) were collected and analyzed, representing five different fields in Idaho, a greenhouse population, and a field in Scotland that was used for external comparison. According to genome-wide allele frequency and fixation index (F_st) analyses, most of the genetic variation was shared among the G. pallida populations in Idaho fields pre-fumigation, indicating that the infestation likely resulted from a single introduction. Temporal patterns of genome-wide polymorphisms involving (1) pre-fumigation field samples collected in 2007 and 2014 and (2) pre- and post-fumigation samples revealed nucleotide variants (SNPs, single-nucleotide polymorphisms) with significantly differentiated allele frequencies indicating genetic differentiation. This study provides insights into the genetic origins and adaptive potential of G. pallida invading new environments.

Detection of breeding signatures in wheat using a linkage disequilibrium-corrected mapping approach

Marker assisted breeding, facilitated by reference genome assemblies, can help to produce cultivars adapted to changing environmental conditions. However, anomalous linkage disequilibrium (LD), where single markers show high LD with markers on other chromosomes but low LD with adjacent markers, is a serious impediment for genetic studies. We used a LD-correction approach to overcome these drawbacks, correcting the physical position of markers derived from 15 and 135 K arrays in a diversity panel of bread wheat representing 50 years of breeding history. We detected putative mismapping of 11.7% markers and improved the physical alignment of 5.4% markers. Population analysis indicated reduced genetic diversity over time as a result of breeding efforts. By analysis of outlier loci and allele frequency change over time we traced back the 2NS/2AS translocation of Aegilops ventricosa to one cultivar, "Cardos" (registered in 1998) which was the first among the panel to contain this translocation. A "selective sweep" for this important translocation region on chromosome 2AS was found, putatively linked to plant response to biotic stress factors. Our approach helps in overcoming the drawbacks of incorrectly anchored markers on the wheat reference assembly and facilitates detection of selective sweeps for important agronomic traits.

Detecting genetic signals of selection in heavily bottlenecked reindeer populations by comparing parallel founder events

Founder populations are of special interest to both evolutionary and conservation biologists, but the detection of genetic signals of selection in these populations is challenging due to their demographic history. Geographically separated founder populations likely to have been subjected to similar selection pressures provide an ideal but rare opportunity to overcome these challenges. Here we take advantage of such a situation generated when small, isolated founder populations of reindeer were established on the island of South Georgia, and using this system we look for empirical evidence of selection overcoming strong genetic drift. We generated a 70 k ddRADseq single nucleotide polymorphism database for the two parallel reindeer founder populations and screened for signatures of soft sweeps. We find evidence for a genomic region under selection shared among the two populations, and support our findings with Wright-Fisher model simulations to assess the power and specificity of interpopulation selection scans-namely Bayescan, OutFLANK, PCadapt and a newly developed scan called Genome Wide Differentiation Scan (GWDS)-in the context of pairwise source-founder comparisons. Our simulations indicate that loci under selection in small founder populations are most probably detected by GWDS, and strengthen the hypothesis that the outlier region represents a true locus under selection. We explore possible, relevant functional roles for genes in linkage with the detected outlier loci.

Revealing environmentally driven population dynamics of an Arctic diatom using a novel microsatellite PoolSeq barcoding approach

Ecological stability under environmental change is determined by both interspecific and intraspecific processes. Particularly for planktonic microorganisms, it is challenging to follow intraspecific dynamics over space and time. We propose a new method, microsatellite PoolSeq barcoding (MPB), for tracing allele frequency changes in protist populations. We successfully applied this method to experimental community incubations and field samples of the diatom Thalassiosira hyalina from the Arctic, a rapidly changing ecosystem. Validation of the method found compelling accuracy in comparison with established genotyping approaches within different diversity contexts. In experimental and environmental samples, we show that MPB can detect meaningful patterns of population dynamics, resolving allelic stability and shifts within a key diatom species in response to experimental treatments as well as different bloom phases and years. Through our novel MPB approach, we produced a large dataset of populations at different time-points and locations with comparably little effort. Results like this can add insights into the roles of selection and plasticity in natural protist populations under stable experimental but also variable field conditions. Especially for organisms where genotype sampling remains challenging, MPB holds great potential to efficiently resolve eco-evolutionary dynamics and to assess the mechanisms and limits of resilience to environmental stressors.

Genomic scans for selective sweeps through haplotype homozygosity and allelic fixation in 14 indigenous sheep breeds from Middle East and South Asia

The performance and productivity of livestock have consistently improved by natural and artificial selection over the centuries. Both these selections are expected to leave patterns on the genome and lead to changes in allele frequencies, but natural selection has played the major role among indigenous populations. Detecting selective sweeps in livestock may assist in understanding the processes involved in domestication, genome evolution and discovery of genomic regions associated with economically important traits. We investigated population genetic diversity and selection signals in this study using SNP genotype data of 14 indigenous sheep breeds from Middle East and South Asia, including six breeds from Iran, namely Iranian Balochi, Afshari, Moghani, Qezel, Zel, and Lori-Bakhtiari, three breeds from Afghanistan, namely Afghan Balochi, Arabi, and Gadik, three breeds from India, namely Indian Garole, Changthangi, and Deccani, and two breeds from Bangladesh, namely Bangladeshi Garole and Bangladesh East. The SNP genotype data were generated by the Illumina OvineSNP50 Genotyping BeadChip array. To detect genetic diversity and population structure, we used principal component analysis (PCA), admixture, phylogenetic analyses, and Runs of homozygosity. We applied four complementary statistical tests, FST (fixation index), xp-EHH (cross-population extended haplotype homozygosity), Rsb (extended haplotype homozygosity between-populations), and FLK (the extension of the Lewontin and Krakauer) to detect selective sweeps. Our results not only confirm the previous studies but also provide a suite of novel candidate genes involved in different traits in sheep. On average, FST, xp-EHH, Rsb, and FLK detected 128, 207, 222, and 252 genomic regions as candidates for selective sweeps, respectively. Furthermore, nine overlapping candidate genes were detected by these four tests, especially TNIK, DOCK1, USH2A, and TYW1B which associate with resistance to diseases and climate adaptation. Knowledge of candidate genomic regions in sheep populations may facilitate the identification and potential exploitation of the underlying genes in sheep breeding.

A Genome-Wide Genetic Diversity Scan Reveals Multiple Signatures of Selection in a European Soybean Collection Compared to Chinese Collections of Wild and Cultivated Soybean Accessions

Targeted and untargeted selections including domestication and breeding efforts can reduce genetic diversity in breeding germplasm and create selective sweeps in crop genomes. The genomic regions at which selective sweeps are detected can reveal important information about signatures of selection. We have analyzed the genetic diversity within a soybean germplasm collection relevant for breeding in Europe (the EUCLEG collection), and have identified selective sweeps through a genome-wide scan comparing that collection to Chinese soybean collections. This work involved genotyping of 480 EUCLEG soybean accessions, including 210 improved varieties, 216 breeding lines and 54 landraces using the 355K SoySNP microarray. SNP calling of 477 EUCLEG accessions together with 328 Chinese soybean accessions identified 224,993 high-quality SNP markers. Population structure analysis revealed a clear differentiation between the EUCLEG collection and the Chinese materials. Further, the EUCLEG collection was sub-structured into five subgroups that were differentiated by geographical origin. No clear association between subgroups and maturity group was detected. The genetic diversity was lower in the EUCLEG collection compared to the Chinese collections. Selective sweep analysis revealed 23 selective sweep regions distributed over 12 chromosomes. Co-localization of these selective sweep regions with previously reported QTLs and genes revealed that various signatures of selection in the EUCLEG collection may be related to domestication and improvement traits including seed protein and oil content, phenology, nitrogen fixation, yield components, diseases resistance and quality. No signatures of selection related to stem determinacy were detected. In addition, absence of signatures of selection for a substantial number of QTLs related to yield, protein content, oil content and phenological traits suggests the presence of substantial genetic diversity in the EUCLEG collection. Taken together, the results obtained demonstrate that the available genetic diversity in the EUCLEG collection can be further exploited for research and breeding purposes. However, incorporation of exotic material can be considered to broaden its genetic base.

Red and blond Mangalitza pigs display a signature of divergent directional selection in the SLC45A2 gene

The Mangalitza lard-type pig breed is well known for its fat appearance and curly hair, and it is mainly distributed in Eastern Europe. Four main lines were created in the nineteenth century by artificial selection: Blond Mangalitza, Black Mangalitza, Swallow-Belly Mangalitza and Red Mangalitza. The Swallow-Belly line has a black coat combined with yellow-blond throat and underbelly. In the current work, we aimed to investigate if the colourations of Mangalitza pigs are genetically determined by one or a few loci whose frequencies have been modified by artificial selection. The results of selection scans, with HapFLK and BayeScan, and of a GWAS for coat colour highlighted the existence of one region on SSC16 (18-20 Mb) with potential effects on hair pigmentation (Red vs. Blond contrast). The analysis of the gene content of this region allowed us to detect the solute carrier family 45 member 2 (SLC45A2) locus as a candidate gene for this trait. The polymorphism of the SLC45A2 locus has been associated with reduced levels or the absence of melanin in several mammalian species. The genotyping of four missense polymorphisms evidenced that rs341599992:G > A and rs693695020:G > A SNPs are strongly but not fully associated with the red and blond coat colours of Mangalitza pigs, a result that was confirmed by performing a haplotype association test. The near fixation of alternative SLC45A2 genotypes in Red and Blond Mangalitza pigs provides a compelling example of the consequences of a divergent directional selection for coat colour in a domestic species.