Assembly of a pangenome for global cattle reveals missing sequences and novel structural variations, providing new insights into their diversity and evolutionary history.

A cattle pangenome representation was created based on the genome sequences of 898 cattle representing 57 breeds. The pangenome identified 83 Mb of sequence not found in the cattle reference genome, representing 3.1% novel sequence compared with the 2.71-Gb reference. A catalog of structural variants developed from this cattle population identified 3.3 million deletions, 0.12 million inversions, and 0.18 million duplications. Estimates of breed ancestry and hybridization between cattle breeds using insertion/deletions as markers were similar to those produced by single nucleotide polymorphism-based analysis. Hundreds of deletions were observed to have stratification based on subspecies and breed. For example, an insertion of a Bov-tA1 repeat element was identified in the first intron of the APPL2 gene and correlated with cattle breed geographic distribution. This insertion falls within a segment overlapping predicted enhancer and promoter regions of the gene, and could affect important traits such as immune response, olfactory functions, cell proliferation, and glucose metabolism in muscle. The results indicate that pangenomes are a valuable resource for studying diversity and evolutionary history, and help to delineate how domestication, trait-based breeding, and adaptive introgression have shaped the cattle genome.

A million-cow genome-wide association study of productive life in U.S. Holstein cows.

BACKGROUND: Productive life (PL) of a cow is the time the cow remains in the milking herd from first calving to exit from the herd due to culling or death and is an important economic trait in U.S. Holstein cattle. The large samples of Holstein genomic evaluation data that have become available recently provided unprecedented statistical power to identify genetic factors affecting PL in Holstein cows using the approach of genome-wide association study (GWAS). METHODS: The GWAS analysis used 1,103,641 Holstein cows with phenotypic observations on PL and genotypes of 75,282 single nucleotide polymorphism (SNP) markers. The statistical tests and estimation of SNP additive and dominance effects used the approximate generalized least squares method implemented by the EPISNPmpi computer program. RESULTS: The GWAS detected 5390 significant additive effects of PL distributed over all 29 autosomes and the X-Y nonrecombining region of the X chromosome (Chr31). Two chromosome regions had the most significant and largest cluster of additive effects, the SLC4A4-GC-NPFFR2 (SGN) region of Chr06 with pleiotropic effects for PL, fertility, somatic cell score and milk yield; and the 32-52 Mb region of Chr10 with peak effects for PL in or near RASGRP1 with many important immunity functions. The dominance tests detected 38 significant dominance effects including 12 dominance effects with sharply negative homozygous recessive genotypes on Chr18, Chr05, Chr23 and Chr24. CONCLUSIONS: The GWAS results showed that highly significant genetic effects for PL were in chromosome regions known to have highly significant effects for fertility and health and a chromosome region with multiple genes with reproductive and immunity functions. SNPs with rare but sharply negative homozygous recessive genotypes for PL existed and should be used for eliminating heifers carrying those homozygous recessive genotypes.

Validating genomic predictions for economic traits in purebred U.S. dairy heifers.

Most genotypes in the National Cooperator Database now originate from cows, but most previous studies validating genomic predictions have primarily focused on bulls. This study paired official within-breed genomic predicted transmitting ability (GPTA) and parent average (PA) for genotyped heifer calves born between 2019 and 2021 using the August 2021 database with their corresponding performance deviations (PDEV) for 17 different traits. The PDEV data became available when the heifers completed their first lactation and were extracted from the August 2023 database in which at least one PDEV value for those 17 traits existed for each genotyped heifer record. The separate breed analyses included records for 219 Ayrshires (AY), 2,715 Brown Swiss (BS), 1,055 Guernseys (GU), 949,904 Holsteins (HO), and 125,275 Jerseys (JE). These validation cows were heifer calves born between 2019 and 2021. However, due to timing or recording patterns, each trait had missing or incomplete PDEV data, leading to unbalanced distributions of records across traits. The squared accuracy of genomic prediction, or genomic reliability (r2), was divided by the corresponding heritability for each trait, as only the heritable portion of cow records could be predicted, and this reliability varied across different traits and breeds. For HO and JE, the predictive ability of GPTA outperformed PA in predicting cow PDEV for yield, productive life, somatic cell score, fertility, and health traits. The improvement ranged from 33% to 142% compared with the predictive ability of the PA. However, the results for AY, BS, and GU breeds were less consistent due to the smaller number of genotyped heifers. The r2 gains in those breeds were smaller and aligned with the published reliabilities of GPTA. Weighted and unweighted regressions of PDEV on GPTA and PA traits mostly exceeded the expected value of 2.00 when predicting the future trait PDEV using GPTA or PA. The larger number of observations and lower standard error of the weighted regression coefficient prediction in HO and JE breeds contributed to more stable and consistent regression coefficients for all traits except milk fever and heifer livability. Our study suggests that herd owners may experience greater benefits from genomics than originally forecast.

A Million-Cow Validation of a Chromosome 14 Region Interacting with All Chromosomes for Fat Percentage in U.S. Holstein Cows.

A genome-wide association study (GWAS) of fat percentage (FPC) using 1,231,898 first lactation cows and 75,198 SNPs confirmed a previous result that a Chr14 region about 9.38 Mb in size (0.14-9.52 Mb) had significant inter-chromosome additive × additive (A×A) effects with all chromosomes and revealed many new such effects. This study divides this 9.38 Mb region into two sub-regions, Chr14a at 0.14-0.88 Mb (0.74 Mb in size) with 78% and Chr14b at 2.21-9.52 Mb (7.31 Mb in size) with 22% of the 2761 significant A×A effects. These two sub-regions were separated by a 1.3 Mb gap at 0.9-2.2 Mb without significant inter-chromosome A×A effects. The PPP1R16A-FOXH1-CYHR1-TONSL (PFCT) region of Chr14a (29 Kb in size) with four SNPs had the largest number of inter-chromosome A×A effects (1141 pairs) with all chromosomes, including the most significant inter-chromosome A×A effects. The SLC4A4-GC-NPFFR2 (SGN) region of Chr06, known to have highly significant additive effects for some production, fertility and health traits, specifically interacted with the PFCT region and a Chr14a region with CPSF1, ADCK5, SLC52A2, DGAT1, SMPD5 and PARP10 (CASDSP) known to have highly significant additive effects for milk production traits. The most significant effects were between an SNP in SGN and four SNPs in PFCT. The CASDSP region mostly interacted with the SGN region. In the Chr14b region, the 2.28-2.42 Mb region (138.46 Kb in size) lacking coding genes had the largest cluster of A×A effects, interacting with seventeen chromosomes. The results from this study provide high-confidence evidence towards the understanding of the genetic mechanism of FPC in Holstein cows.

Large-Sample Genome-Wide Association Study of Resistance to Retained Placenta in U.S. Holstein Cows.

A genome-wide association study of resistance to retained placenta (RETP) using 632,212 Holstein cows and 74,747 SNPs identified 200 additive effects with p-values < 10-8 on thirteen chromosomes but no dominance effect was statistically significant. The regions of 87.61-88.74 Mb of Chr09 about 1.13 Mb in size had the most significant effect in LOC112448080 and other highly significant effects in CCDC170 and ESR1, and in or near RMND1 and AKAP12. Four non-ESR1 genes in this region were reported to be involved in ESR1 fusions in humans. Chr23 had the largest number of significant effects that peaked in SLC17A1, which was involved in urate metabolism and transport that could contribute to kidney disease. The PKHD1 gene contained seven significant effects and was downstream of another six significant effects. The ACOT13 gene also had a highly significant effect. Both PKHD1 and ACOT13 were associated with kidney disease. Another highly significant effect was upstream of BOLA-DQA2. The KITLG gene of Chr05 that acts in utero in germ cell and neural cell development, and hematopoiesis was upstream of a highly significant effect, contained a significant effect, and was between another two significant effects. The results of this study provided a new understanding of genetic factors underlying RETP in U.S. Holstein cows.

Participatory investigation of goat farmers' breeding practices, trait preference, and selection criteria in Burkina Faso.

The community-based breeding program (CBBP) is an innovative approach recommended for genetic improvement and sustainable use of animal genetic resources in extensive farming systems. Successful implementation of this approach requires an understanding of the characteristics of production systems, breeding objectives, and farmers' trait preference. This study aimed to identify the selection criteria of goat farmers in rural areas of Burkina Faso and their potential implications in establishing CBBP. Following focus group discussions, a well-structured questionnaire was designed and administered to 372 randomly selected goat farmers in two different agro-ecological zones. A list of traits obtained during focus group discussions was provided to farmers individually, and they were asked to rank the ones they preferentially use to select breeding animals. Statistical tests were conducted to compare data between the two agro-ecological zones. The results showed that the average goat flock per household was higher (P < 0.05) in the Sudanian (15.68 ± 13.76), compared to the Sudano-Sahelian area (12.93 ± 13.3). Adult females were the dominant age-sex group in both areas. Reasons for culling, keeping breeding bucks, and castration practice were significantly different (P < 0.05) among agro-ecological zones. The most important common criterion for selection in the two zones was body size, coat color, and growth rate for the bucks and does, while fertility (0.06) parameters including twining ability (0.18), kidding frequency (0.11), and mothering ability (0.15) were furthermore considered for breeding does selection. These findings provide valuable insights for developing CBBPs tailored to goat production in the study areas.

Comprehensive analyses of 723 transcriptomes enhance genetic and biological interpretations for complex traits in cattle.

By uniformly analyzing 723 RNA-seq data from 91 tissues and cell types, we built a comprehensive gene atlas and studied tissue specificity of genes in cattle. We demonstrated that tissue-specific genes significantly reflected the tissue-relevant biology, showing distinct promoter methylation and evolution patterns (e.g., brain-specific genes evolve slowest, whereas testis-specific genes evolve fastest). Through integrative analyses of those tissue-specific genes with large-scale genome-wide association studies, we detected relevant tissues/cell types and candidate genes for 45 economically important traits in cattle, including blood/immune system (e.g., CCDC88C) for male fertility, brain (e.g., TRIM46 and RAB6A) for milk production, and multiple growth-related tissues (e.g., FGF6 and CCND2) for body conformation. We validated these findings by using epigenomic data across major somatic tissues and sperm. Collectively, our findings provided novel insights into the genetic and biological mechanisms underlying complex traits in cattle, and our transcriptome atlas can serve as a primary source for biological interpretation, functional validation, studies of adaptive evolution, and genomic improvement in livestock.

Invited review: Reliability computation from the animal model era to the single-step genomic model era.

The calculation of exact reliabilities involving the inversion of mixed model equations poses a heavy computational challenge when the system of equations is large. This has prompted the development of different approximation methods. We give an overview of the various methods and computational approaches in calculating reliability from the era before the animal model to the era of single-step genomic models. The different methods are discussed in terms of modeling, development, and applicability in large dairy cattle populations. The paper also describes the problems faced in reliability computation. Many details dispersed throughout the literature are presented in this paper. It is clear that a universal solution applicable to every model and input data may not be possible, but we point out several efficient and accurate algorithms developed recently for a variety of very large genomic evaluations.

Estimating test-day milk yields by modeling proportional daily yields: Going beyond linearity.

In the United States, lactation milk yields are not measured directly but are calculated from the test-day milk yields. Still, test-day milk yields are estimated from partial yields obtained from single milkings. Various methods have been proposed to estimate test-day milk yields, primarily to deal with unequal milking intervals dating back to the 1970s and 1980s. The Wiggans model is a de facto method for estimating test-day milk yields in the United States, which was initially proposed for cows milked 3 times daily, assuming a linear relationship between a proportional test-day milk yield and milking interval. However, the linearity assumption did not hold precisely in Holstein cows milked twice daily because of prolonged and uneven milking intervals. The present study reviewed and evaluated the nonlinear models that extended the Wiggans model for estimating daily or test-day milk yields. These nonlinear models, except step functions, demonstrated smaller errors and greater accuracies for estimated test-day milk yields compared with the conventional methods. The nonlinear models offered additional benefits. For example, the locally weighted regression model (e.g., locally estimated scatterplot smoothing) could utilize data information in scalable neighborhoods and weigh observations according to their distance in milking interval time. General additive models provide a flexible, unified framework to model nonlinear predictor variables additively. Another drawback of the conventional methods is a loss of accuracy caused by discretizing milking interval time into large bins while deriving multiplicative correction factors for estimating test-day milk yields. To overcome this problem, we proposed a general approach that allows milk yield correction factors to be derived for every possible milking interval time, resulting in more accurately estimated test-day milk yields. This approach can be applied to any model, including nonparametric models.

Towards the detection of copy number variation from single sperm sequencing in cattle.

BACKGROUND: Copy number variation (CNV) has been routinely studied using bulk-cell sequencing. However, CNV is not well studied on the single-cell level except for humans and a few model organisms. RESULTS: We sequenced 143 single sperms of two Holstein bulls, from which we predicted CNV events using 14 single sperms with deep sequencing. We then compared the CNV results derived from single sperms with the bulk-cell sequencing of one bull's family trio of diploid genomes. As a known CNV hotspot, segmental duplications were also predicted using the bovine ARS-UCD1.2 genome. Although the trio CNVs validated only some single sperm CNVs, they still showed a distal chromosomal distribution pattern and significant associations with segmental duplications and satellite repeats. CONCLUSION: Our preliminary results pointed out future research directions and highlighted the importance of uniform whole genome amplification, deep sequence coverage, and dedicated software pipelines for CNV detection using single cell sequencing data.

Genome-wide recombination map construction from single sperm sequencing in cattle.

BACKGROUND: Meiotic recombination is one of the important phenomena contributing to gamete genome diversity. However, except for human and a few model organisms, it is not well studied in livestock, including cattle. RESULTS: To investigate their distributions in the cattle sperm genome, we sequenced 143 single sperms from two Holstein bulls. We mapped meiotic recombination events at high resolution based on phased heterozygous single nucleotide polymorphism (SNP). In the absence of evolutionary selection pressure in fertilization and survival, recombination events in sperm are enriched near distal chromosomal ends, revealing that such a pattern is intrinsic to the molecular mechanism of meiosis. Furthermore, we further validated these findings in single sperms with results derived from sequencing its family trio of diploid genomes and our previous studies of recombination in cattle. CONCLUSIONS: To our knowledge, this is the first large-scale single sperm whole-genome sequencing effort in livestock, which provided useful information for future studies of recombination, genome instability, and male infertility.

Single-cell transcriptomic analyses of dairy cattle ruminal epithelial cells during weaning.

Using the 10× Genomics Chromium Controller, we obtained scRNA-seq data of 5064 and 1372 individual cells from two Holstein calf ruminal epithelial tissues before and after weaning, respectively. We detected six distinct cell clusters, designated their cell types, and reported their marker genes. We then examined these clusters' underlining cell types and relationships by performing cell cycle, pseudotime trajectory, regulatory network, weighted gene co-expression network and gene ontology analyses. By integrating these cell marker genes with Holstein GWAS signals, we found they were enriched for animal production and body conformation traits. Finally, we confirmed their cell identities by comparing them with human and mouse stomach epithelial cells. This study presents an initial effort to implement single-cell transcriptomic analysis in cattle, and demonstrates ruminal tissue epithelial cell types and their developments during weaning, opening the door for new discoveries about tissue/cell type roles in complex traits at single-cell resolution.

Detection of copy number variants in African goats using whole genome sequence data.

BACKGROUND: Copy number variations (CNV) are a significant source of variation in the genome and are therefore essential to the understanding of genetic characterization. The aim of this study was to develop a fine-scaled copy number variation map for African goats. We used sequence data from multiple breeds and from multiple African countries. RESULTS: A total of 253,553 CNV (244,876 deletions and 8677 duplications) were identified, corresponding to an overall average of 1393 CNV per animal. The mean CNV length was 3.3 kb, with a median of 1.3 kb. There was substantial differentiation between the populations for some CNV, suggestive of the effect of population-specific selective pressures. A total of 6231 global CNV regions (CNVR) were found across all animals, representing 59.2 Mb (2.4%) of the goat genome. About 1.6% of the CNVR were present in all 34 breeds and 28.7% were present in all 5 geographical areas across Africa, where animals had been sampled. The CNVR had genes that were highly enriched in important biological functions, molecular functions, and cellular components including retrograde endocannabinoid signaling, glutamatergic synapse and circadian entrainment. CONCLUSIONS: This study presents the first fine CNV map of African goat based on WGS data and adds to the growing body of knowledge on the genetic characterization of goats.

VarGoats project: a dataset of 1159 whole-genome sequences to dissect Capra hircus global diversity.

BACKGROUND: Since their domestication 10,500 years ago, goat populations with distinctive genetic backgrounds have adapted to a broad variety of environments and breeding conditions. The VarGoats project is an international 1000-genome resequencing program designed to understand the consequences of domestication and breeding on the genetic diversity of domestic goats and to elucidate how speciation and hybridization have modeled the genomes of a set of species representative of the genus Capra. FINDINGS: A dataset comprising 652 sequenced goats and 507 public goat sequences, including 35 animals representing eight wild species, has been collected worldwide. We identified 74,274,427 single nucleotide polymorphisms (SNPs) and 13,607,850 insertion-deletions (InDels) by aligning these sequences to the latest version of the goat reference genome (ARS1). A Neighbor-joining tree based on Reynolds genetic distances showed that goats from Africa, Asia and Europe tend to group into independent clusters. Because goat breeds from Oceania and Caribbean (Creole) all derive from imported animals, they are distributed along the tree according to their ancestral geographic origin. CONCLUSIONS: We report on an unprecedented international effort to characterize the genome-wide diversity of domestic goats. This large range of sequenced individuals represents a unique opportunity to ascertain how the demographic and selection processes associated with post-domestication history have shaped the diversity of this species. Data generated for the project will also be extremely useful to identify deleterious mutations and polymorphisms with causal effects on complex traits, and thus will contribute to new knowledge that could be used in genomic prediction and genome-wide association studies.

Comparative whole genome DNA methylation profiling across cattle tissues reveals global and tissue-specific methylation patterns.

BACKGROUND: Efforts to improve animal health, and understand genetic bases for production, may benefit from a comprehensive analysis of animal genomes and epigenomes. Although DNA methylation has been well studied in humans and other model species, its distribution patterns and regulatory impacts in cattle are still largely unknown. Here, we present the largest collection of cattle DNA methylation epigenomic data to date. RESULTS: Using Holstein cattle, we generated 29 whole genome bisulfite sequencing (WGBS) datasets for 16 tissues, 47 corresponding RNA-seq datasets, and 2 whole genome sequencing datasets. We did read mapping and DNA methylation calling based on two different cattle assemblies, demonstrating the high quality of the long-read-based assembly markedly improved DNA methylation results. We observed large differences across cattle tissues in the methylation patterns of global CpG sites, partially methylated domains (PMDs), hypomethylated regions (HMRs), CG islands (CGIs), and common repeats. We detected that each tissue had a distinct set of PMDs, which showed tissue-specific patterns. Similar to human PMD, cattle PMDs were often linked to a general decrease of gene expression and a decrease in active histone marks and related to long-range chromatin organizations, like topologically associated domains (TADs). We tested a classification of the HMRs based on their distributions relative to transcription start sites (TSSs) and detected tissue-specific TSS-HMRs and genes that showed strong tissue effects. When performing cross-species comparisons of paired genes (two opposite strand genes with their TSS located in the same HMR), we found out they were more consistently co-expressed among human, mouse, sheep, goat, yak, pig, and chicken, but showed lower consistent ratios in more divergent species. We further used these WGBS data to detect 50,023 experimentally supported CGIs across bovine tissues and found that they might function as a guard against C-to-T mutations for TSS-HMRs. Although common repeats were often heavily methylated, some young Bov-A2 repeats were hypomethylated in sperm and could affect the promoter structures by exposing potential transcription factor binding sites. CONCLUSIONS: This study provides a comprehensive resource for bovine epigenomic research and enables new discoveries about DNA methylation and its role in complex traits.

Genome-wide CNV analysis revealed variants associated with growth traits in African indigenous goats.

Using the CaprineSNP50 data generated by the AGIN consortium, we detected common CNVs in 126 samples from four African indigenous goat breeds. A total of 30 CNVs ranging from 30,237 bp to 4,910,757 bp were identified. These CNVs were then associated with six growth traits by a linear regression analysis. Three significant associations were identified between two CNVs and two body traits after false discovery rate (FDR) correction (P < .05). One of them (CNV27) was significantly associated with both chest width and width of pin bones. It overlaps the SNX29 gene, the Gene Ontology (GO) annotations of which indicate CNV27 could be a potential functional candidate for meat production, health and reproduction traits. To our knowledge, this study is the first CNV-based association test of growth traits using SNP chip data in African meat goats.

Computational detection and experimental validation of segmental duplications and associated copy number variations in water buffalo ( Bubalus bubalis ).

Duplicated sequences are an important source of gene evolution and structural variation within mammalian genomes. Using a read depth approach based on next-generation sequencing, we performed a genome-wide analysis of segmental duplications (SDs) and associated copy number variations (CNVs) in the water buffalo (Bubalus bubalis). By aligning short reads of Olimpia (the reference water buffalo) to the UMD3.1 cattle genome, we identified 1,038 segmental duplications comprising 44.6 Mb (equivalent to ~1.73% of the cattle genome) of the autosomal and X chromosomal sequence in the buffalo genome. We experimentally validated 70.3% (71/101) of these duplications using fluorescent in situ hybridization. We also detected a total of 1,344 CNV regions across 14 additional water buffaloes, amounting to 59.8 Mb of variable sequence or the equivalent of 2.2% of the cattle genome. The CNV regions overlap 1,245 genes that are significantly enriched for specific biological functions including immune response, oxygen transport, sensory system and signal transduction. Additionally, we performed array Comparative Genomic Hybridization (aCGH) experiments using the 14 water buffaloes as test samples and Olimpia as the reference. Using a linear regression model, a high Pearson correlation (r = 0.781) was observed between the log2 ratios between copy number estimates and the log2 ratios of aCGH probes. We further designed Quantitative PCR assays to confirm CNV regions within or near annotated genes and found 74.2% agreement with our CNV predictions. These results confirm sub-chromosome-scale structural rearrangements present in the cattle and water buffalo. The information on genome variation that will be of value for evolutionary and phenotypic studies, and may be useful for selective breeding of both species.

Diversity of copy number variation in the worldwide goat population.

Goats (Capra hircus) are an important farm animal species. Copy number variation (CNV) represents a major source of genomic structural variation. We investigated the diversity of CNV distribution in goats using CaprineSNP50 genotyping data generated by the ADAPTmap Project. We identified 6286 putative CNVs in 1023 samples from 50 goat breeds using PennCNV. These CNVs were merged into 978 CNV regions, spanning ~262 Mb of total length and corresponding to ~8.96% of the goat genome. We then divided the samples into six subgroups per geographic distribution and constructed a comparative CNV map. Our results revealed a population differentiation in CNV across different geographical areas, including Western Asia, Eastern Mediterranean, Alpine & Northern Europe, Madagascar, Northwestern Africa, and Southeastern Africa groups. The results of a cluster heatmap analysis based on the CNV count per individual across different groups was generally consistent with the one generated from the SNP data, likely reflecting the population history of different goat breeds. We sought to determine the gene content of these CNV events and found several important CNV-overlapping genes (e.g. EDNRA, ADAMTS20, ASIP, KDM5B, ADAM8, DGAT1, CHRNB1, CLCN7, and EXOSC4), which are involved in local adaptations such as coat color, muscle development, metabolic processes, osteopetrosis, and embryonic development. Therefore, this research generated an extensive CNV map in the worldwide population of goat, which offers novel insight into the goat genome and its functional annotation.

Changes in genetic selection differentials and generation intervals in US Holstein dairy cattle as a result of genomic selection.

Seven years after the introduction of genomic selection in the United States, it is now possible to evaluate the impact of this technology on the population. Selection differential(s) (SD) and generation interval(s) (GI) were characterized in a four-path selection model that included sire(s) of bulls (SB), sire(s) of cows (SC), dam(s) of bulls (DB), and dam(s) of cows (DC). Changes in SD over time were estimated for milk, fat, and protein yield; somatic cell score (SCS); productive life (PL); and daughter pregnancy rate (DPR) for the Holstein breed. In the period following implementation of genomic selection, dramatic reductions were seen in GI, especially the SB and SC paths. The SB GI reduced from ∼7 y to less than 2.5 y, and the DB GI fell from about 4 y to nearly 2.5 y. SD were relatively stable for yield traits, although modest gains were noted in recent years. The most dramatic response to genomic selection was observed for the lowly heritable traits DPR, PL, and SCS. Genetic trends changed from close to zero to large and favorable, resulting in rapid genetic improvement in fertility, lifespan, and health in a breed where these traits eroded over time. These results clearly demonstrate the positive impact of genomic selection in US dairy cattle, even though this technology has only been in use for a short time. Based on the four-path selection model, rates of genetic gain per year increased from ∼50-100% for yield traits and from threefold to fourfold for lowly heritable traits.

Signatures of selection and environmental adaptation across the goat genome post-domestication.

BACKGROUND: Since goat was domesticated 10,000 years ago, many factors have contributed to the differentiation of goat breeds and these are classified mainly into two types: (i) adaptation to different breeding systems and/or purposes and (ii) adaptation to different environments. As a result, approximately 600 goat breeds have developed worldwide; they differ considerably from one another in terms of phenotypic characteristics and are adapted to a wide range of climatic conditions. In this work, we analyzed the AdaptMap goat dataset, which is composed of data from more than 3000 animals collected worldwide and genotyped with the CaprineSNP50 BeadChip. These animals were partitioned into groups based on geographical area, production uses, available records on solid coat color and environmental variables including the sampling geographical coordinates, to investigate the role of natural and/or artificial selection in shaping the genome of goat breeds. RESULTS: Several signatures of selection on different chromosomal regions were detected across the different breeds, sub-geographical clusters, phenotypic and climatic groups. These regions contain genes that are involved in important biological processes, such as milk-, meat- or fiber-related production, coat color, glucose pathway, oxidative stress response, size, and circadian clock differences. Our results confirm previous findings in other species on adaptation to extreme environments and human purposes and provide new genes that could explain some of the differences between goat breeds according to their geographical distribution and adaptation to different environments. CONCLUSIONS: These analyses of signatures of selection provide a comprehensive first picture of the global domestication process and adaptation of goat breeds and highlight possible genes that may have contributed to the differentiation of this species worldwide.