The genomic signatures of natural selection in admixed human populations.

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

HaploBlocks: Efficient Detection of Positive Selection in Large Population Genomic Datasets.

Genomic regions under positive selection harbor variation linked for example to adaptation. Most tools for detecting positively selected variants have computational resource requirements rendering them impractical on population genomic datasets with hundreds of thousands of individuals or more. We have developed and implemented an efficient haplotype-based approach able to scan large datasets and accurately detect positive selection. We achieve this by combining a pattern matching approach based on the positional Burrows-Wheeler transform with model-based inference which only requires the evaluation of closed-form expressions. We evaluate our approach with simulations, and find it to be both sensitive and specific. The computational resource requirements quantified using UK Biobank data indicate that our implementation is scalable to population genomic datasets with millions of individuals. Our approach may serve as an algorithmic blueprint for the era of "big data" genomics: a combinatorial core coupled with statistical inference in closed form.

Deciphering signatures of natural selection via deep learning.

Identifying genomic regions influenced by natural selection provides fundamental insights into the genetic basis of local adaptation. However, it remains challenging to detect loci under complex spatially varying selection. We propose a deep learning-based framework, DeepGenomeScan, which can detect signatures of spatially varying selection. We demonstrate that DeepGenomeScan outperformed principal component analysis- and redundancy analysis-based genome scans in identifying loci underlying quantitative traits subject to complex spatial patterns of selection. Noticeably, DeepGenomeScan increases statistical power by up to 47.25% under nonlinear environmental selection patterns. We applied DeepGenomeScan to a European human genetic dataset and identified some well-known genes under selection and a substantial number of clinically important genes that were not identified by SPA, iHS, Fst and Bayenv when applied to the same dataset.

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.

Genomic signatures of local adaptation in recent invasive Aedes aegypti populations in California.

BACKGROUND: Rapid adaptation to new environments can facilitate species invasions and range expansions. Understanding the mechanisms of adaptation used by invasive disease vectors in new regions has key implications for mitigating the prevalence and spread of vector-borne disease, although they remain relatively unexplored. RESULTS: Here, we integrate whole-genome sequencing data from 96 Aedes aegypti mosquitoes collected from various sites in southern and central California with 25 annual topo-climate variables to investigate genome-wide signals of local adaptation among populations. Patterns of population structure, as inferred using principal components and admixture analysis, were consistent with three genetic clusters. Using various landscape genomics approaches, which all remove the confounding effects of shared ancestry on correlations between genetic and environmental variation, we identified 112 genes showing strong signals of local environmental adaptation associated with one or more topo-climate factors. Some of them have known effects in climate adaptation, such as heat-shock proteins, which shows selective sweep and recent positive selection acting on these genomic regions. CONCLUSIONS: Our results provide a genome wide perspective on the distribution of adaptive loci and lay the foundation for future work to understand how environmental adaptation in Ae. aegypti impacts the arboviral disease landscape and how such adaptation could help or hinder efforts at population control.

The Impact of Genetic Surfing on Neutral Genomic Diversity.

Range expansions have been common in the history of most species. Serial founder effects and subsequent population growth at expansion fronts typically lead to a loss of genomic diversity along the expansion axis. A frequent consequence is the phenomenon of "gene surfing," where variants located near the expanding front can reach high frequencies or even fix in newly colonized territories. Although gene surfing events have been characterized thoroughly for a specific locus, their effects on linked genomic regions and the overall patterns of genomic diversity have been little investigated. In this study, we simulated the evolution of whole genomes during several types of 1D and 2D range expansions differing by the extent of migration, founder events, and recombination rates. We focused on the characterization of local dips of diversity, or "troughs," taken as a proxy for surfing events. We find that, for a given recombination rate, once we consider the amount of diversity lost since the beginning of the expansion, it is possible to predict the initial evolution of trough density and their average width irrespective of the expansion condition. Furthermore, when recombination rates vary across the genome, we find that troughs are over-represented in regions of low recombination. Therefore, range expansions can leave local and global genomic signatures often interpreted as evidence of past selective events. Given the generality of our results, they could be used as a null model for species having gone through recent expansions, and thus be helpful to correctly interpret many evolutionary biology studies.

From common gardens to candidate genes: exploring local adaptation to climate in red spruce.

Local adaptation to climate is common in plant species and has been studied in a range of contexts, from improving crop yields to predicting population maladaptation to future conditions. The genomic era has brought new tools to study this process, which was historically explored through common garden experiments. In this study, we combine genomic methods and common gardens to investigate local adaptation in red spruce and identify environmental gradients and loci involved in climate adaptation. We first use climate transfer functions to estimate the impact of climate change on seedling performance in three common gardens. We then explore the use of multivariate gene-environment association methods to identify genes underlying climate adaptation, with particular attention to the implications of conducting genome scans with and without correction for neutral population structure. This integrative approach uncovered phenotypic evidence of local adaptation to climate and identified a set of putatively adaptive genes, some of which are involved in three main adaptive pathways found in other temperate and boreal coniferous species: drought tolerance, cold hardiness, and phenology. These putatively adaptive genes segregated into two 'modules' associated with different environmental gradients. This study nicely exemplifies the multivariate dimension of adaptation to climate in trees.

Whole genome resequencing identifies local adaptation associated with environmental variation for redband trout.

Aquatic ectotherms are predicted to harbour genomic signals of local adaptation resulting from selective pressures driven by the strong influence of climate conditions on body temperature. We investigated local adaptation in redband trout (Oncorhynchus mykiss gairdneri) using genome scans for 547 samples from 11 populations across a wide range of habitats and thermal gradients in the interior Columbia River. We estimated allele frequencies for millions of single nucleotide polymorphism loci (SNPs) across populations using low-coverage whole genome resequencing, and used population structure outlier analyses to identify genomic regions under divergent selection between populations. Twelve genomic regions showed signatures of local adaptation, including two regions associated with genes known to influence migration and developmental timing in salmonids (GREB1L, ROCK1, SIX6). Genotype-environment association analyses indicated that diurnal temperature variation was a strong driver of local adaptation, with signatures of selection driven primarily by divergence of two populations in the northern extreme of the subspecies range. We also found evidence for adaptive differences between high-elevation desert vs. montane habitats at a smaller geographical scale. Finally, we estimated vulnerability of redband trout to future climate change using ecological niche modelling and genetic offset analyses under two climate change scenarios. These analyses predicted substantial habitat loss and strong genetic shifts necessary for adaptation to future habitats, with the greatest vulnerability predicted for high-elevation desert populations. Our results provide new insight into the complexity of local adaptation in salmonids, and important predictions regarding future responses of redband trout to climate change.

Hard versus soft selective sweeps during domestication and improvement in soybean.

Genome scans for selection can provide an efficient way to dissect the genetic basis of domestication traits and understand mechanisms of adaptation during crop evolution. Selection involving soft sweeps (simultaneous selection for multiple alleles) is probably common in plant genomes but is under-studied, and few if any studies have systematically scanned for soft sweeps in the context of crop domestication. Using genome resequencing data from 302 wild and domesticated soybean accessions, we conducted selection scans using five widely employed statistics to identify selection candidates under classical (hard) and soft sweeps. Across the genome, inferred hard sweeps are predominant in domesticated soybean landraces and improved varieties, whereas soft sweeps are more prevalent in a representative subpopulation of the wild ancestor. Six domestication-related genes, representing both hard and soft sweeps and different stages of domestication, were used as positive controls to assess the detectability of domestication-associated sweeps. Performance of various test statistics suggests that differentiation-based (FST ) methods are robust for detecting complete hard sweeps, and that LD-based strategies perform well for identifying recent/ongoing sweeps; however, none of the test statistics detected a known soft sweep we previously documented at the domestication gene Dt1. Genome scans yielded a set of 66 candidate loci that were identified by both differentiation-based and LD-based (iHH) methods; notably, this shared set overlaps with many previously identified QTLs for soybean domestication/improvement traits. Collectively, our results will help to advance genetic characterizations of soybean domestication traits and shed light on selection modes involved in adaptation in domesticated plant species.

Complex adaptive architecture underlies adaptation to quantitative host resistance in a fungal plant pathogen.

Plant pathogens often adapt to plant genetic resistance so characterization of the architecture underlying such an adaptation is required to understand the adaptive potential of pathogen populations. Erosion of banana quantitative resistance to a major leaf disease caused by polygenic adaptation of the causal agent, the fungus Pseudocercospora fijiensis, was recently identified in the northern Caribbean region. Genome scan and quantitative genetics approaches were combined to investigate the adaptive architecture underlying this adaptation. Thirty-two genomic regions showing host selection footprints were identified by pool sequencing of isolates collected from seven plantation pairs of two cultivars with different levels of quantitative resistance. Individual sequencing and phenotyping of isolates from one pair revealed significant and variable levels of correlation between haplotypes in 17 of these regions with a quantitative trait of pathogenicity (the diseased leaf area). The multilocus pattern of haplotypes detected in the 17 regions was found to be highly variable across all the population pairs studied. These results suggest complex adaptive architecture underlying plant pathogen adaptation to quantitative resistance with a polygenic basis, redundancy, and a low level of parallel evolution between pathogen populations. Candidate genes involved in quantitative pathogenicity and host adaptation of P. fijiensis were identified in genomic regions by combining annotation analysis with available biological data.

Gene mapping, gene-set analysis, and genomic prediction of postpartum blood calcium in Holstein cows.

The onset of lactation results in a sudden irreversible loss of Ca for colostrum and milk synthesis. Some cows are unable to quickly adapt to this demand and succumb to clinical hypocalcemia, whereas a larger proportion of cows develop subclinical hypocalcemia that predisposes them to other peripartum diseases. The objective of this study was to perform a comprehensive genomic analysis of blood total Ca concentration in periparturient Holstein cows. We first performed a genomic scan and a subsequent gene-set analysis to identify candidate genes, biological pathways, and molecular mechanisms affecting postpartum Ca concentration. Then, we assessed the prediction of postpartum Ca concentration using genomic information. Data consisted of 7,691 records of plasma or serum concentrations of Ca measured in the first, second, and third day after parturition of 959 primiparous and 1,615 multiparous cows that calved between December 2015 and June 2020 in 2 dairy herds. All cows were genotyped with 80k SNPs. The statistical model included lactation (1 to 5+), calf category (male, females, twins), and day as fixed effects, and season-treatment-experiment, animal, and permanent environmental as random effects. Model predictive ability was evaluated using 10-fold cross-validation. Heritability and repeatability estimates were 0.083 (standard error = 0.017) and 0.444 (standard error = 0.028). The association mapping identified 2 major regions located on Bos taurus autosome (BTA)6 and BTA16 that explained 1.2% and 0.7% of additive genetic variance of Ca concentration, respectively. Interestingly, the region on BTA6 harbors the GC gene, which encodes the vitamin D binding protein, and the region on BTA16 harbors LRRC38, which is actively involved in K transport. Other sizable peaks were identified on BTA5, BTA2, BTA7, BTA14, and BTA9. These regions harbor genes associated with Ca channels (CACNA1S, CRACR2A), K channels (KCNK9), bone remodeling (LRP6), and milk production (SOCS2). The gene-set analysis revealed terms related to vitamin transport, calcium ion transport, calcium ion binding, and calcium signaling. Genomic predictions of phenotypic and genomic estimated breeding values of Ca concentration yielded predictive correlations up to 0.50 and 0.15, respectively. Overall, the present study contributes to a better understanding of the genetic basis of postpartum blood Ca concentration in Holstein cows. In addition, the findings may contribute to the development of novel selection and management strategies for reducing periparturient hypocalcemia in dairy cattle.

Facilitating population genomics of non-model organisms through optimized experimental design for reduced representation sequencing.

BACKGROUND: Genome-wide data are invaluable to characterize differentiation and adaptation of natural populations. Reduced representation sequencing (RRS) subsamples a genome repeatedly across many individuals. However, RRS requires careful optimization and fine-tuning to deliver high marker density while being cost-efficient. The number of genomic fragments created through restriction enzyme digestion and the sequencing library setup must match to achieve sufficient sequencing coverage per locus. Here, we present a workflow based on published information and computational and experimental procedures to investigate and streamline the applicability of RRS. RESULTS: In an iterative process genome size estimates, restriction enzymes and size selection windows were tested and scaled in six classes of Antarctic animals (Ostracoda, Malacostraca, Bivalvia, Asteroidea, Actinopterygii, Aves). Achieving high marker density would be expensive in amphipods, the malacostracan target taxon, due to the large genome size. We propose alternative approaches such as mitogenome or target capture sequencing for this group. Pilot libraries were sequenced for all other target taxa. Ostracods, bivalves, sea stars, and fish showed overall good coverage and marker numbers for downstream population genomic analyses. In contrast, the bird test library produced low coverage and few polymorphic loci, likely due to degraded DNA. CONCLUSIONS: Prior testing and optimization are important to identify which groups are amenable for RRS and where alternative methods may currently offer better cost-benefit ratios. The steps outlined here are easy to follow for other non-model taxa with little genomic resources, thus stimulating efficient resource use for the many pressing research questions in molecular ecology.

A QTL for conformation of back and croup influences lateral gait quality in Icelandic horses.

BACKGROUND: The back plays a vital role in horse locomotion, where the spine functions as a spring during the stride cycle. A complex interaction between the spine and the muscles of the back contribute to locomotion soundness, gait ability, and performance of riding and racehorses. Conformation is commonly used to select horses for breeding and performance in multiple horse breeds, where the back and croup conformation plays a significant role. The conformation of back and croup plays an important role on riding ability in Icelandic horses. However, the genes behind this trait are still unknown. Therefore, the aim of this study was to identify genomic regions associated with conformation of back and croup in Icelandic horses and to investigate their effects on riding ability. One hundred seventy-seven assessed Icelandic horses were included in the study. A genome-wide association analysis was performed using the 670 K+ Axiom Equine Genotyping Array, and the effects of different haplotypes in the top associated region were estimated for riding ability and additional conformation traits assessed during breeding field tests. RESULTS: A suggestive quantitative trait loci (QTL) for the score of back and croup was detected on Equus caballus (ECA) 22 (p-value = 2.67 × 10- 7). Haplotype analysis revealed two opposite haplotypes, which resulted in higher and lower scores of the back and croup, respectively (p-value < 0.001). Horses with the favorable haplotype were more inclined to have a well-balanced backline with an uphill conformation and had, on average, higher scores for the lateral gaits tölt (p-value = 0.02) and pace (p-value = 0.004). This genomic region harbors three genes: C20orf85, ANKRD60 and LOC100056167. ANKRD60 is associated with body height in humans. C20orf85 and ANKRD60 are potentially linked to adolescent idiopathic scoliosis in humans. CONCLUSIONS: Our results show that the detected QTL for conformation of back and croup is of importance for quality of lateral gaits in Icelandic horses. These findings could result in a genetic test to aid in the selection of breeding horses, thus they are of major interest for horse breeders. The results may also offer a gateway to comparative functional genomics by potentially linking both motor laterality and back inclination in horses with scoliosis in humans.

Genomic signatures of divergent selection are associated with social behaviour for spinner dolphin ecotypes.

Understanding the genomic basis of adaptation is critical for understanding evolutionary processes and predicting how species will respond to environmental change. Spinner dolphins in the eastern tropical Pacific (ETP) present a unique system for studying adaptation. Within this large geographical region are four spinner dolphin ecotypes with weak neutral genetic divergence and no obvious barriers to gene flow, but strong spatial variation in morphology, behaviour and habitat. These ecotypes have large population sizes, which could reduce the effects of drift and facilitate selection. To identify genomic regions putatively under divergent selective pressures between ecotypes, we used genome scans with 8994 RADseq single nucleotide polymorphisms (SNPs) to identify population differentiation outliers and genotype-environment association outliers. Gene ontology enrichment analyses indicated that outlier SNPs from both types of analyses were associated with multiple genes involved in social behaviour and hippocampus development, including 15 genes associated with the human social disorder autism. Evidence for divergent selection on social behaviour is supported by previous evidence that these spinner dolphin ecotypes differ in mating systems and associated social behaviours. In particular, three of the ETP ecotypes probably have a polygynous mating system characterized by strong premating competition among males, whereas the fourth ecotype probably has a polygynandrous mating system characterized by strong postmating competition such as sperm competition. Our results provide evidence that selection for social behaviour may be an evolutionary force driving diversification of spinner dolphins in the ETP, potentially as a result of divergent sexual selection associated with different mating systems. Future studies should further investigate the potential adaptive role of the candidate genes identified here, and could probably find further signatures of selection using whole genome sequence data.

Harnessing landscape genomics to identify future climate resilient genotypes in a desert annual.

Local adaptation features critically in shaping species responses to changing environments, complicating efforts to revegetate degraded areas. Rapid climate change poses an additional challenge that could reduce fitness of even locally sourced seeds in restoration. Predictive restoration strategies that apply seeds with favourable adaptations to future climate may promote long-term resilience. Landscape genomics is increasingly used to assess spatial patterns in local adaption and may represent a cost-efficient approach for identifying future-adapted genotypes. To demonstrate such an approach, we genotyped 760 plants from 64 Mojave Desert populations of the desert annual Plantago ovata. Genome scans on 5,960 SNPs identified 184 potentially adaptive loci related to climate and satellite vegetation metrics. Causal modelling indicated that variation in potentially adaptive loci was not confounded by isolation by distance or isolation by habitat resistance. A generalized dissimilarity model (GDM) attributed spatial turnover in potentially adaptive loci to temperature, precipitation and NDVI amplitude, a measure of vegetation green-up potential. By integrating a species distribution model (SDM), we find evidence that summer maximum temperature may both constrain the range of P. ovata and drive adaptive divergence in populations exposed to higher temperatures. Within the species' current range, warm-adapted genotypes are predicted to experience a fivefold expansion in climate niche by midcentury and could harbour key adaptations to cope with future climate. We recommend eight seed transfer zones and project each zone into its relative position in future climate. Prioritizing seed collection efforts on genotypes with expanding future habitat represents a promising strategy for restoration practitioners to address rapidly changing climates.

Identification of Arabis alpina genomic regions associated with climatic variables along an elevation gradient through whole genome scan.

We performed a pooled whole-genome sequencing on samples of the alpine plant Arabis alpina, harvested in ten populations along an elevation gradient in the French Alps. A large dataset of genetic variations was produced as single nucleotide polymorphisms (SNPs). A combined genome scan approach enabled detecting genomic regions associated with a synthetic environmental variable characterizing the climate at each sampling location. Positive loci detected by two methods were retained and belong to 19 regions in the Arabis alpina genome. The most significant region harbors an ortholog of the AtNAC062 gene, encoding a membrane-bound transcription factor described as linking the cold response and pathogen resistance that may confer protection to plants under extended snow coverage at high elevations. Other genes involved in the stress response or in flowering regulation were also detected. Altogether, our results indicated that Arabis alpina represent a suitable model for studying genomic adaptation in alpine perennial plants.

fcScan: a versatile tool to cluster combinations of sites using genomic coordinates.

BACKGROUND: Finding combinations of homotypic or heterotypic genomic sites obeying a specific grammar in DNA sequences is a frequent task in bioinformatics. A typical case corresponds to the identification of cis-regulatory modules characterized by a combination of transcription factor binding sites in a defined window size. Although previous studies identified clusters of genomic sites in species with varying genome sizes, the availability of a dedicated and versatile tool to search for such clusters is lacking. RESULTS: We present fcScan, an R/Bioconductor package to search for clusters of genomic sites based on user defined criteria including cluster size, inter-cluster distances and sites order and orientation allowing users to adapt their search criteria to specific biological questions. It supports GRanges, data frame and VCF/BED files as input and returns data in GRanges format. By performing clustering on vectorized data, fcScan is adapted to search for genomic clusters in millions of sites as input in short time and is thus ideal to scan data generated by high throughput methods including next generation sequencing. CONCLUSIONS: fcScan is ideal for detecting cis-regulatory modules of transcription factor binding sites with a specific grammar as well as genomic loci enriched for mutations. The flexibility in input parameters allows users to perform searches targeting specific research questions. It is released under Artistic-2.0 License. The source code is freely available through Bioconductor (https://bioconductor.org/packages/fcScan) and GitHub (https://github.com/pkhoueiry/fcScan).

Massive postglacial gene flow between European white oaks uncovered genes underlying species barriers.

Oaks are dominant forest tree species widely distributed across the Northern Hemisphere, where they constitute natural resources of economic, ecological, social and historical value. Hybridisation and adaptive introgression have long been thought to be major drivers of their ecological success. Therefore, the maintenance of species barriers remains a key question, given the extent of interspecific gene flow. In this study, we made use of the tremendous genetic variation among four European white oak species (31 million single nucleotide polymorphisms (SNPs)) to infer the evolutionary history of these species, study patterns of genetic differentiation and identify reproductive barriers. We first analysed the ecological and historical relationships among these species and inferred a long-term strict isolation followed by a recent and extensive postglacial contact using approximate Bayesian computation. Assuming this demographic scenario, we then performed backward simulations to generate the expected distributions of differentiation under neutrality to scan their genomes for reproductive barriers. We finally identified important intrinsic and ecological functions driving the reproductive isolation. We discussed the importance of identifying the genetic basis for the ecological preferences between these oak species and its implications for the renewal of European forests under global warming.

Instability of natural selection at candidate barrier loci underlying speciation in wood ants.

Speciation underlies the generation of novel biodiversity. Yet, there is much to learn about how natural selection shapes genomes during speciation. Selection is assumed to act against gene flow at barrier loci, promoting reproductive isolation. However, evidence for gene flow and selection is often indirect and we know very little about the temporal stability of barrier loci. Here we utilize haplodiploidy to identify candidate male barrier loci in hybrids between two wood ant species. As ant males are haploid, they are expected to reveal recessive barrier loci, which can be masked in diploid females if heterozygous. We then test for barrier stability in a sample collected 10 years later and use survival analysis to provide a direct measure of natural selection acting on candidate male barrier loci. We find multiple candidate male barrier loci scattered throughout the genome. Surprisingly, a proportion of them are not stable after 10 years, natural selection apparently switching from acting against to favouring introgression in the later sample. Instability of the barrier effect and natural selection for introgressed alleles could be due to environment-dependent selection, emphasizing the need to consider temporal variation in the strength of natural selection and the stability of the barrier effect at putative barrier loci in future speciation work.

Genetic dissection of reproductive performance of dairy cows under heat stress.

Heat stress negatively impacts the reproductive performance of dairy cows. The main objective of this study was to dissect the genetic basis underlying dairy cow fertility under heat stress conditions. Our first goal was to estimate genetic components of cow conception across lactations considering heat stress. Our second goal was to reveal individual genes and functional gene-sets that explain a cow's ability to conceive under thermal stress. Data consisted of 74 221 insemination records on 13 704 Holstein cows. Multitrait linear repeatability test-day models with random regressions on a function of temperature-humidity index values were used for the analyses. Heritability estimates for cow conception under heat stress were around 2-3%, whereas genetic correlations between general and thermotolerance additive genetic effects were negative and ranged between -0.35 and -0.82, indicating an unfavorable relationship between cows' ability to conceive under thermo-neutral vs. thermo-stress conditions. Whole-genome scans identified at least six genomic regions on BTA1, BTA10, BTA11, BTA17, BTA21 and BTA23 associated with conception under thermal stress. These regions harbor candidate genes such as BRWD1, EXD2, ADAM20, EPAS1, TAOK3, and NOS1, which are directly implicated in reproductive functions and cellular response to heat stress. The gene-set enrichment analysis revealed functional terms related to fertilization, developmental biology, heat shock proteins and oxidative stress, among others. Overall, our findings contribute to a better understanding of the genetics underlying the reproductive performance of dairy cattle under heat stress conditions and point out novel genomic strategies for improving thermotolerance and fertility via marker-assisted breeding.