Selection signatures and landscape genomics analysis to reveal climate adaptation of goat breeds.

Goats have achieved global prominence as essential livestock since their initial domestication, primarily owing to their remarkable adaptability to diverse environmental and production systems. Differential selection pressures influenced by climate have led to variations in their physical attributes, leaving genetic imprints within the genomes of goat breeds raised in diverse agroecological settings. In light of this, our study pursued a comprehensive analysis, merging environmental data with single nucleotide polymorphism (SNP) variations, to unearth indications of selection shaped by climate-mediated forces in goats. Through the examination of 43,300 SNPs from 51 indigenous goat breeds adapting to different climatic conditions using four analytical methods: latent factor mixed models (LFMM), F-statistics (Fst), Extended haplotype homozygosity across populations (XPEHH), and spatial analysis method (SAM), A total of 74 genes were revealed to display clear signs of selection, which are believed to be influenced by climatic conditions. Among these genes, 32 were consistently identified by at least two of the applied methods, and three genes (DENND1A, PLCB1, and ITPR2) were confirmed by all four approaches. Moreover, our investigation yielded 148 Gene Ontology (GO) terms based on these 74 genes, underlining pivotal biological pathways crucial for environmental adaptation. These pathways encompass functions like vascular smooth muscle contraction, cellular response to heat, GTPase regulator activity, rhythmic processes, and responses to temperature stimuli. Of significance, GO terms about endocrine regulation and energy metabolic responses, key for local adaptation were also uncovered, including biological processes, such as cell differentiation, regulation of peptide hormone secretion, and lipid metabolism. These findings contribute to our knowledge of the genetic structure of climate-triggered adaptation across the goat genome and have practical implications for marker-assisted breeding in goats.

Landscape genomics reveals regions associated with adaptive phenotypic and genetic variation in Ethiopian indigenous chickens.

Climate change is a threat to sustainable livestock production and livelihoods in the tropics. It has adverse impacts on feed and water availability, disease prevalence, production, environmental temperature, and biodiversity. Unravelling the drivers of local adaptation and understanding the underlying genetic variation in random mating indigenous livestock populations informs the design of genetic improvement programmes that aim to increase productivity and resilience. In the present study, we combined environmental, genomic, and phenotypic information of Ethiopian indigenous chickens to investigate their environmental adaptability. Through a hybrid sampling strategy, we captured wide biological and ecological variabilities across the country. Our environmental dataset comprised mean values of 34 climatic, vegetation and soil variables collected over a thirty-year period for 260 geolocations. Our biological dataset included whole genome sequences and quantitative measurements (on eight traits) from 513 individuals, representing 26 chicken populations spread along 4 elevational gradients (6-7 populations per gradient). We performed signatures of selection analyses ([Formula: see text] and XP-EHH) to detect footprints of natural selection, and redundancy analyses (RDA) to determine genotype-environment and genotype-phenotype-associations. RDA identified 1909 outlier SNPs linked with six environmental predictors, which have the highest contributions as ecological drivers of adaptive phenotypic variation. The same method detected 2430 outlier SNPs that are associated with five traits. A large overlap has been observed between signatures of selection identified by[Formula: see text]and XP-EHH showing that both methods target similar selective sweep regions. Average genetic differences measured by [Formula: see text] are low between gradients, but XP-EHH signals are the strongest between agroecologies. Genes in the calcium signalling pathway, those associated with the hypoxia-inducible factor (HIF) transcription factors, and sports performance (GALNTL6) are under selection in high-altitude populations. Our study underscores the relevance of landscape genomics as a powerful interdisciplinary approach to dissect adaptive phenotypic and genetic variation in random mating indigenous livestock populations.

Identification of population-informative markers from high-density genotyping data through combined feature selection and machine learning algorithms: Application to European autochthonous and cosmopolitan pig breeds.

Large genotyping datasets, obtained from high-density single nucleotide polymorphism (SNP) arrays, developed for different livestock species, can be used to describe and differentiate breeds or populations. To identify the most discriminating genetic markers among thousands of genotyped SNPs, a few statistical approaches have been proposed. In this study, we applied the Boruta algorithm, a wrapper of the machine learning random forest algorithm, on a database of 23 European pig breeds (20 autochthonous and three cosmopolitan breeds) genotyped with a 70k SNP chip, to pre-select informative SNPs. To identify different sets of SNPs, these pre-selected markers were then ranked with random forest based on their mean decrease accuracy and mean decrease gene indexes. We evaluated the efficiency of these subsets for breed classification and the usefulness of this approach to detect candidate genes affecting breed-specific phenotypes and relevant production traits that might differ among breeds. The lowest overall classification error (2.3%) was reached with a subpanel including only 398 SNPs (ranked based on their mean decrease accuracy), with no classification error in seven breeds using up to 49 SNPs. Several SNPs of these selected subpanels were in genomic regions in which previous studies had identified signatures of selection or genes associated with morphological or production traits that distinguish the analysed breeds. Therefore, even if these approaches have not been originally designed to identify signatures of selection, the obtained results showed that they could potentially be useful for this purpose.

Phylogeny and disparate selection signatures suggest two genetically independent domestication events in pea (Pisum L.).

Domestication is considered a model of adaptation that can be used to draw conclusions about the modus operandi of selection in natural systems. Investigating domestication may give insights into how plants react to different intensities of human manipulation, which has direct implication for the continuing efforts of crop improvement. Therefore, scientists of various disciplines study domestication-related questions to understand the biological and cultural bases of the domestication process. We employed restriction site-associated DNA sequencing (RAD-seq) of 494 Pisum sativum (pea) samples from all wild and domesticated groups to analyze the genetic structure of the collection. Patterns of ancient admixture were investigated by analysis of admixture graphs. We used two complementary approaches, one diversity based and one based on differentiation, to detect the selection signatures putatively associated with domestication. An analysis of the subpopulation structure of wild P. sativum revealed five distinct groups with a notable geographic pattern. Pisum abyssinicum clustered unequivocally within the P. sativum complex, without any indication of hybrid origin. We detected 32 genomic regions putatively subjected to selection: 29 in P. sativum ssp. sativum and three in P. abyssinicum. The two domesticated groups did not share regions under selection and did not display similar haplotype patterns within those regions. Wild P. sativum is structured into well-diverged subgroups. Although Pisum sativum ssp. humile is not supported as a taxonomic entity, the so-called 'southern humile' is a genuine wild group. Introgression did not shape the variation observed within the sampled germplasm. The two domesticated pea groups display distinct genetic bases of domestication, suggesting two genetically independent domestication events.

Genome-wide scan for runs of homozygosity in South American Camelids.

BACKGROUND: Alpaca (Vicugna pacos), llama (Lama glama), vicugna (Vicugna vicugna) and guanaco (Lama guanicoe), are the camelid species distributed over the Andean high-altitude grasslands, the Altiplano, and the Patagonian arid steppes. Despite the wide interest on these animals, most of the loci under selection are still unknown. Using whole-genome sequencing (WGS) data we investigated the occurrence and the distribution of Runs Of Homozygosity (ROHs) across the South American Camelids (SACs) genome to identify the genetic relationship between the four species and the potential signatures of selection. RESULTS: A total of 37 WGS samples covering the four species was included in the final analysis. The multi-dimensional scaling approach showed a clear separation between the four species; however, admixture analysis suggested a strong genetic introgression from vicugna and llama to alpaca. Conversely, very low genetic admixture of the guanaco with the other SACs was found. The four species did not show significant differences in the number, length of ROHs (100-500 kb) and genomic inbreeding values. Longer ROHs (> 500 kb) were found almost exclusively in alpaca. Seven overlapping ROHs were shared by alpacas, encompassing nine loci (FGF5, LOC107034918, PRDM8, ANTXR2, LOC102534792, BSN, LOC116284892, DAG1 and RIC8B) while nine overlapping ROHs were found in llama with twenty-five loci annotated (ERC2, FZD9, BAZ1B, BCL7B, LOC116284208, TBL2, MLXIPL, PHF20, TRNAD-AUC, LOC116284365, RBM39, ARFGEF2, DCAF5, EXD2, HSPB11, LRRC42, LDLRAD1, TMEM59, LOC107033213, TCEANC2, LOC102545169, LOC116278408, SMIM15, NDUFAF2 and RCOR1). Four overlapping ROHs, with three annotated loci (DLG1, KAT6B and PDE4D) and three overlapping ROHs, with seven annotated genes (ATP6V1E1, BCL2L13, LOC116276952, BID, KAT6B, LOC116282667 and LOC107034552), were detected for vicugna and guanaco, respectively. CONCLUSIONS: The signatures of selection revealed genomic areas potentially selected for production traits as well as for natural adaptation to harsh environment. Alpaca and llama hint a selection driven by environment as well as by farming purpose while vicugna and guanaco showed selection signals for adaptation to harsh environment. Interesting, signatures of selection on KAT6B gene were identified for both vicugna and guanaco, suggesting a positive effect on wild populations fitness. Such information may be of interest to further ecological and animal production studies.

High Levels of Genetic Diversity within Nilo-Saharan Populations: Implications for Human Adaptation.

Africa contains more human genetic variation than any other continent, but the majority of the population-scale analyses of the African peoples have focused on just two of the four major linguistic groups, the Niger-Congo and Afro-Asiatic, leaving the Nilo-Saharan and Khoisan populations under-represented. In order to assess genetic variation and signatures of selection within a Nilo-Saharan population and between the Nilo-Saharan and Niger-Congo and Afro-Asiatic, we sequenced 50 genomes from the Nilo-Saharan Lugbara population of North-West Uganda and 250 genomes from 6 previously unsequenced Niger-Congo populations. We compared these data to data from a further 16 Eurasian and African populations including the Gumuz, another putative Nilo-Saharan population from Ethiopia. Of the 21 million variants identified in the Nilo-Saharan population, 3.57 million (17%) were not represented in dbSNP and included predicted non-synonymous mutations with possible phenotypic effects. We found greater genetic differentiation between the Nilo-Saharan Lugbara and Gumuz populations than between any two Afro-Asiatic or Niger-Congo populations. F3 tests showed that Gumuz contributed a genetic component to most Niger-Congo B populations whereas Lugabara did not. We scanned the genomes of the Lugbara for evidence of selective sweeps. We found selective sweeps at four loci (SLC24A5, SNX13, TYRP1, and UVRAG) associated with skin pigmentation, three of which already have been reported to be under selection. These selective sweeps point toward adaptations to the intense UV radiation of the Sahel.

Genomic inbreeding estimation, runs of homozygosity, and heterozygosity-enriched regions uncover signals of selection in the Quarter Horse racing line.

With the advent of genomics, significant progress has been made in the genetic improvement of livestock species, particularly through increased accuracy in predicting breeding values for selecting superior animals and the possibility of performing a high-resolution genetic scan throughout the genome of an individual. The main objectives of this study were to estimate the individual genomic inbreeding coefficient based on runs of homozygosity (FROH ), to identify and characterize runs of homozygosity and heterozygosity (ROH and ROHet, respectively; length and distribution) throughout the genome, and to map selection signatures in relevant chromosomal regions in the Quarter Horse racing line. A total of 336 animals registered with the Brazilian Association of Quarter Horse Breeders (ABQM) were genotyped. One hundred and twelve animals were genotyped using the Equine SNP50 BeadChip (Illumina, USA), with 54,602 single nucleotide polymorphisms (SNPs; 54K). The remaining 224 samples were genotyped using the Equine SNP70 BeadChip (Illumina, USA) with 65,157 SNPs (65K). To ensure data quality, we excluded animals with a call rate below 0.9. We also excluded SNPs located on non-autosomal chromosomes, as well as those with a call rate below 0.9 or a p-value below 1 × 10-5 for Hardy-Weinberg equilibrium. The results indicate moderate to high genomic inbreeding, with 46,594 ROH and 16,101 ROHet detected. In total, 30 and 14 candidate genes overlap with ROH and ROHet regions, respectively. The ROH islands showed genes linked to crucial biological processes, such as cell differentiation (CTBP1, WNT5B, and TMEM120B), regulation of glucose metabolic process (MAEA and NKX1-1), heme transport (PGRMC2), and negative regulation of calcium ion import (VDAC1). In ROHet, the islands showed genes related to respiratory capacity (OR7D19, OR7D4G, OR7D4E, and OR7D4J) and muscle repair (EGFR and BCL9). These findings could aid in selecting animals with greater regenerative capacity and developing treatments for muscle disorders in the QH breed. This study serves as a foundation for future research on equine breeds. It can contribute to developing reproductive strategies in animal breeding programs to improve and preserve the Quarter Horse breed.

Runs of homozygosity in Sable Island feral horses reveal the genomic consequences of inbreeding and divergence from domestic breeds.

BACKGROUND: Understanding inbreeding and its impact on fitness and evolutionary potential is fundamental to species conservation and agriculture. Long stretches of homozygous genotypes, known as runs of homozygosity (ROH), result from inbreeding and their number and length can provide useful population-level information on inbreeding characteristics and locations of signatures of selection. However, the utility of ROH for conservation is limited for natural populations where baseline data and genomic tools are lacking. Comparing ROH metrics in recently feral vs. domestic populations of well understood species like the horse could provide information on the genetic health of those populations and offer insight into how such metrics compare between managed and unmanaged populations. Here we characterized ROH, inbreeding coefficients, and ROH islands in a feral horse population from Sable Island, Canada, using ~41 000 SNPs and contrasted results with those from 33 domestic breeds to assess the impacts of isolation on ROH abundance, length, distribution, and ROH islands. RESULTS: ROH number, length, and ROH-based inbreeding coefficients (FROH) in Sable Island horses were generally greater than in domestic breeds. Short runs, which typically coalesce many generations prior, were more abundant than long runs in all populations, but run length distributions indicated more recent population bottlenecks in Sable Island horses. Nine ROH islands were detected in Sable Island horses, exhibiting very little overlap with those found in domestic breeds. Gene ontology (GO) enrichment analysis for Sable Island ROH islands revealed enrichment for genes associated with 3 clusters of biological pathways largely associated with metabolism and immune function. CONCLUSIONS: This study indicates that Sable Island horses tend to be more inbred than their domestic counterparts and that most of this inbreeding is due to historical bottlenecks and founder effects rather than recent mating between close relatives. Unique ROH islands in the Sable Island population suggest adaptation to local selective pressures and/or strong genetic drift and highlight the value of this population as a reservoir of equine genetic variation. This research illustrates how ROH analyses can be applied to gain insights into the population history, genetic health, and divergence of wild or feral populations of conservation concern.

Weighted Single-Step GWAS for Body Mass Index and Scans for Recent Signatures of Selection in Yorkshire Pigs.

Controlling extra fat deposition is economically favorable in modern swine industry. Understanding the genetic architecture of fat deposition traits such as body mass index (BMI) can help in improving genomic selection for such traits. We utilized a weighted single-step genome-wide association study (WssGWAS) to detect genetic regions and candidate genes associated with BMI in a Yorkshire pig population. Three extended haplotype homozygosity (EHH)-related statistics were also incorporated within a de-correlated composite of multiple signals (DCMS) framework to detect recent selection signatures signals. Overall, the full pedigree consisted of 7016 pigs, of which 5561 had BMI records and 598 pigs were genotyped with an 80 K single nucleotide polymorphism (SNP) array. Results showed that the most significant windows (top 15) explained 9.35% of BMI genetic variance. Several genes were detected in regions previously associated with pig fat deposition traits and treated as potential candidate genes for BMI in Yorkshire pigs: FTMT, SRFBP1, KHDRBS3, FOXG1, SOD3, LRRC32, TSKU, ACER3, B3GNT6, CCDC201, ADCY1, RAMP3, TBRG4, CCM2. Signature of selection analysis revealed multiple candidate genes previously associated with various economic traits. However, BMI genetic variance explained by regions under selection pressure was minimal (1.31%). In conclusion, candidate genes associated with Yorkshire pigs' BMI trait were identified using WssGWAS. Gene enrichment analysis indicated that the identified candidate genes were enriched in the insulin secretion pathway. We anticipate that these results further advance our understanding of the genetic architecture of BMI in Yorkshire pigs and provide information for genomic selection for fat deposition in this breed.

Population structure and genomic footprints of selection in five major Iranian horse breeds.

The genetic structure and characteristics of Iranian native breeds are yet to be comprehensibly investigated and studied. Therefore, we employed genomic information of 364 Iranian native horses representing the Asil (n = 109), Caspian (n = 40), Dareshuri (n = 44), Kurdish (n = 95), and Turkoman (n = 76) breeds to reveal the genetic structure and characteristics. For these and 19 other horse breeds, principal component analysis, Bayesian model-based, Neighbor-Net, and bootstrap-based TreeMix approaches were applied to investigate and compare their genetic structure. Additionally, three haplotype-based methods including haplotype homozygosity pooled, integrated haplotype score, and number of segregating sites by length were applied to trace genomic footprints of selection of Asil, Caspian, Dareshuri, Kurdish, and Turkoman groups. Then, the Mahalanobis distance based on the negative-log10 rank-based P-values was estimated based on the haplotype homozygosity pooled, integrated haplotype score, and number of segregating sites by length values. Asil, Caspian, Dareshuri, Kurdish, and Turkoman can be categorized into five different genetic clusters. Based on the top 1% of Mahalanobis distance based on the negative-log10 rank-based P-values of SNPs, we identified 24 SNPs formerly reported to be associated with different traits and >100 genes undergoing selection pressures in Asil, Caspian, Dareshuri, Kurdish, and Turkoman. The detected QTL undergoing selection pressures were associated with withers height, equine metabolic syndrome, overall body size, insect bite hypersensitivity, guttural pouch tympany, white markings, Rhodococcus equi infection, jumping test score, alternate gaits, and body weight traits. Our findings will aid to have a better perspective of the genetic characteristics and population structure of Asil, Caspian, Dareshuri, Kurdish, and Turkoman horses as Iranian native horse breeds.

Resequencing the Yaroslavl cattle genomes reveals signatures of selection and a rare haplotype on BTA28 likely to be related to breed phenotypes.

The genomes of local livestock could shed light on their genetic history, mechanisms of adaptations to environments and unique genetics. Herein we look into the genetics and adaptations of the Russian native dairy Yaroslavl cattle breed using 22 resequenced individuals and comparing them with two related breeds (Russian Kholmogory and Holstein), and to the taurine set of the 1000 Bull Genomes Project (Run 9). HapFLK analysis with Kholmogory and Holstein breeds (using Yakut cattle as outgroup) resulted in 22 regions under selection (q-value < 0.01) on 11 chromosomes assigned to Yaroslavl cattle, including a strong signature of selection in the region of the KIT gene on BTA6. The FST (fixation index) with the 1000 Bull Genomes Dataset showed 48 non-overlapping top (0.1%) FST regions of which three overlapped HapFLK regions. We identified 1982 highly differentiated (FST > 0.40) missense mutations in the Yaroslavl genomes. These genes were enriched in the epidermal growth factor and calcium-binding functional categories. The top FST intervals contained eight genes with allele frequencies quite different between the Yaroslavl and Kholmogory breeds and the rest of the 1000 Bull Genomes Dataset, including KAT6B, which had a nearly Yaroslavl breed-specific deleterious missense mutation with the highest FST in our dataset (0.99). This gene is a part of a long haplotype containing other genes from FST and hapFLK analyses and with a negative association with weight and carcass traits according to the genotyping of 30 phenotyped Yaroslavl cattle individuals. Our work provides the industry with candidate genetic variants to be focused on in breed improvement efforts.

Investigating the impact of reference assembly choice on genomic analyses in a cattle breed.

BACKGROUND: Reference-guided read alignment and variant genotyping are prone to reference allele bias, particularly for samples that are greatly divergent from the reference genome. A Hereford-based assembly is the widely accepted bovine reference genome. Haplotype-resolved genomes that exceed the current bovine reference genome in quality and continuity have been assembled for different breeds of cattle. Using whole genome sequencing data of 161 Brown Swiss cattle, we compared the accuracy of read mapping and sequence variant genotyping as well as downstream genomic analyses between the bovine reference genome (ARS-UCD1.2) and a highly continuous Angus-based assembly (UOA_Angus_1). RESULTS: Read mapping accuracy did not differ notably between the ARS-UCD1.2 and UOA_Angus_1 assemblies. We discovered 22,744,517 and 22,559,675 high-quality variants from ARS-UCD1.2 and UOA_Angus_1, respectively. The concordance between sequence- and array-called genotypes was high and the number of variants deviating from Hardy-Weinberg proportions was low at segregating sites for both assemblies. More artefactual INDELs were genotyped from UOA_Angus_1 than ARS-UCD1.2 alignments. Using the composite likelihood ratio test, we detected 40 and 33 signatures of selection from ARS-UCD1.2 and UOA_Angus_1, respectively, but the overlap between both assemblies was low. Using the 161 sequenced Brown Swiss cattle as a reference panel, we imputed sequence variant genotypes into a mapping cohort of 30,499 cattle that had microarray-derived genotypes using a two-step imputation approach. The accuracy of imputation (Beagle R2) was very high (0.87) for both assemblies. Genome-wide association studies between imputed sequence variant genotypes and six dairy traits as well as stature produced almost identical results from both assemblies. CONCLUSIONS: The ARS-UCD1.2 and UOA_Angus_1 assemblies are suitable for reference-guided genome analyses in Brown Swiss cattle. Although differences in read mapping and genotyping accuracy between both assemblies are negligible, the choice of the reference genome has a large impact on detecting signatures of selection that already reached fixation using the composite likelihood ratio test. We developed a workflow that can be adapted and reused to compare the impact of reference genomes on genome analyses in various breeds, populations and species.

A selection signatures study among Middle Eastern and European sheep breeds.

Selection, both natural and artificial, leaves patterns on the genome during domestication of animals and leads to changes in allele frequencies among populations. Detecting genomic regions influenced by selection in livestock may assist in understanding the processes involved in genome evolution and discovering genomic regions related to traits of economic and ecological interests. In the current study, genetic diversity analyses were conducted on 34,206 quality-filtered SNP positions from 450 individuals in 15 sheep breeds, including six indigenous breeds from the Middle East, namely Iranian Balouchi, Afshari, Moghani, Qezel, Karakas and Norduz, and nine breeds from Europe, namely East Friesian Sheep, Ile de France, Mourerous, Romane, Swiss Mirror, Spaelsau, Suffolk, Comisana and Engadine Red Sheep. The SNP genotype data generated by the Illumina OvineSNP50 Genotyping BeadChip array were used in this analysis. We applied two complementary statistical analyses, FST (fixation index) and xp-EHH (cross-population extended haplotype homozygosity), to detect selection signatures in Middle Eastern and European sheep populations. FST and xp-EHH detected 629 and 256 genes indicating signatures of selection, respectively. Genomic regions identified using FST and xp-EHH contained the CIDEA, HHATL, MGST1, FADS1, RTL1 and DGKG genes, which were reported earlier to influence a number of economic traits. Both FST and xp-EHH approaches identified 60 shared genes as the signatures of selection, including four candidate genes (NT5E, ADA2, C8A and C8B) that were enriched for two significant Gene Ontology (GO) terms associated with the adenosine metabolic procedure. Knowledge about the candidate genomic regions under selective pressure in sheep breeds may facilitate identification of the underlying genes and enhance our understanding on these genes role in local adaptation.

Genome-wide detection of signatures of selection in indicine and Brazilian locally adapted taurine cattle breeds using whole-genome re-sequencing data.

BACKGROUND: The cattle introduced by European conquerors during the Brazilian colonization period were exposed to a process of natural selection in different types of biomes throughout the country, leading to the development of locally adapted cattle breeds. In this study, whole-genome re-sequencing data from indicine and Brazilian locally adapted taurine cattle breeds were used to detect genomic regions under selective pressure. Within-population and cross-population statistics were combined separately in a single score using the de-correlated composite of multiple signals (DCMS) method. Putative sweep regions were revealed by assessing the top 1% of the empirical distribution generated by the DCMS statistics. RESULTS: A total of 33,328,447 biallelic SNPs with an average read depth of 12.4X passed the hard filtering process and were used to access putative sweep regions. Admixture has occurred in some locally adapted taurine populations due to the introgression of exotic breeds. The genomic inbreeding coefficient based on runs of homozygosity (ROH) concurred with the populations' historical background. Signatures of selection retrieved from the DCMS statistics provided a comprehensive set of putative candidate genes and revealed QTLs disclosing cattle production traits and adaptation to the challenging environments. Additionally, several candidate regions overlapped with previous regions under selection described in the literature for other cattle breeds. CONCLUSION: The current study reported putative sweep regions that can provide important insights to better understand the selective forces shaping the genome of the indicine and Brazilian locally adapted taurine cattle breeds. Such regions likely harbor traces of natural selection pressures by which these populations have been exposed and may elucidate footprints for adaptation to the challenging climatic conditions.

Copy number variation in human genomes from three major ethno-linguistic groups in Africa.

BACKGROUND: Copy number variation is an important class of genomic variation that has been reported in 75% of the human genome. However, it is underreported in African populations. Copy number variants (CNVs) could have important impacts on disease susceptibility and environmental adaptation. To describe CNVs and their possible impacts in Africans, we sequenced genomes of 232 individuals from three major African ethno-linguistic groups: (1) Niger Congo A from Guinea and Côte d'Ivoire, (2) Niger Congo B from Uganda and the Democratic Republic of Congo and (3) Nilo-Saharans from Uganda. We used GenomeSTRiP and cn.MOPS to identify copy number variant regions (CNVRs). RESULTS: We detected 7608 CNVRs, of which 2172 were only deletions, 2384 were only insertions and 3052 had both. We detected 224 previously un-described CNVRs. The majority of novel CNVRs were present at low frequency and were not shared between populations. We tested for evidence of selection associated with CNVs and also for population structure. Signatures of selection identified previously, using SNPs from the same populations, were overrepresented in CNVRs. When CNVs were tagged with SNP haplotypes to identify SNPs that could predict the presence of CNVs, we identified haplotypes tagging 3096 CNVRs, 372 CNVRs had SNPs with evidence of selection (iHS > 3) and 222 CNVRs had both. This was more than expected (p < 0.0001) and included loci where CNVs have previously been associated with HIV, Rhesus D and preeclampsia. When integrated with 1000 Genomes CNV data, we replicated their observation of population stratification by continent but no clustering by populations within Africa, despite inclusion of Nilo-Saharans and Niger-Congo populations within our dataset. CONCLUSIONS: Novel CNVRs in the current study increase representation of African diversity in the database of genomic variants. Over-representation of CNVRs in SNP signatures of selection and an excess of SNPs that both tag CNVs and are subject to selection show that CNVs may be the actual targets of selection at some loci. However, unlike SNPs, CNVs alone do not resolve African ethno-linguistic groups. Tag haplotypes for CNVs identified may be useful in predicting African CNVs in future studies where only SNP data is available.

Signatures of selection analysis using whole-genome sequence data reveals novel candidate genes for pony and light horse types.

Natural selection and domestication have shaped modern horse populations, resulting in a vast range of phenotypically diverse breeds. Horse breeds are classified into three types (pony, light, and draft) generally based on their body type. Understanding the genetic basis of horse type variation and selective pressures related to the evolutionary trend can be particularly important for current selection strategies. Whole-genome sequences were generated for 14 pony and 32 light horses to investigate the genetic signatures of selection of the horse type in pony and light horses. In the overlapping extremes of the fixation index and nucleotide diversity results, we found novel genomic signatures of selective sweeps near key genes previously implicated in body measurements including C4ORF33, CRB1, CPN1, FAM13A, and FGF12 that may influence variation in pony and light horse types. This study contributes to a better understanding of the genetic background of differences between pony and light horse types.

Combined approaches to reveal genes associated with litter size in Yunshang black goats.

Intensive artificial selection has been imposed in Yunshang black goats, the first black specialist mutton goat breed in China, with a breeding object of improving reproductive performance, which has contributed to reshaping of the genome including the characterization of SNP, ROH and haplotype. However, variation in reproductive ability exists in the present population. A WGS was implemented in two subpopulations (polytocous group, PG, and monotocous group, MG) with evident differences of litter size. Following the mapping to reference genome, and SNP calling and pruning, three approaches - GWAS, ROH analysis and detection of signatures of selection - were employed to unveil candidate genes responsible for litter size. Consequently, 12 candidate genes containing OSBPL8 with the minimum P-value were uncovered by GWAS. Differences were observed in the pattern of ROH between two subpopulations that shared similar low inbreeding coefficients. Two ROH hotspots and 12 corresponding genes emerged from ROH pool association analysis. Based on the nSL statistic, 15 and 61 promising genes were disclosed under selection for MG and PG respectively. Of them, some promising genes participate in ovarian function (PPP2R5C, CDC25A, ESR1, RPS26 and SERPINBs), seasonal reproduction (DIO3, BTG1 and CRYM) and metabolism (OSBPL8, SLC39A5 and SERPINBs). Our study pinpointed some novel promising genes influencing litter size, provided a comprehensive insight into genetic makeup of litter size and might facilitate selective breeding in goats.

Signatures of selection for resistance to Haemonchus contortus in sheep and goats.

BACKGROUND: Gastrointestinal nematode infection (GNI) is the most important disease affecting the small ruminant industry in U.S. The environmental conditions in the southern United States are ideal for the survival of the most pathogenic gastrointestinal nematode, Haemonchus contortus. Host genetic variation for resistance to H. contortus allows selective breeding for increased resistance of animals. This selection process increases the prevalence of particular alleles in sheep and goats and creates unique genetic patterns in the genome of these species. The aim of this study was to identify loci with divergent allelic frequencies in a candidate gene panel of 100 genes using two different approaches (frequentist and Bayesian) to estimate Fst outliers in three different breeds of sheep and goats exposed to H. contortus. RESULTS: Our results for sheep populations showed SNPs under selection in C3AR1, CSF3, SOCS2, NOS2, STAT5B, TGFB2 and IL2RA genes using frequentist and Bayesian approaches. For goats, SNPs in CD1D, ITGA9, IL12A, IL13RA1, CD86 and TGFB2 genes were under selection. Common signatures of selection in both species were observed in NOS2, TGFB2 and TLR4 genes. Directional selection was present in all SNPs evaluated in the present study. CONCLUSIONS: A total of 13 SNPs within 7 genes of our candidate gene panel related to H. contortus exposure were identified under selection in sheep populations. For goats, 11 SNPs within 7 genes were identified under selection. Results from this study support the hypothesis that resistance to H. contortus is likely to be controlled by many loci. Shared signatures of selection related to mechanisms of immune protection against H. contortus infection in sheep and goats could be useful targets in breeding programs aimed to produce resistant animals with low FEC.

Ten years of the horse reference genome: insights into equine biology, domestication and population dynamics in the post-genome era.

The horse reference genome from the Thoroughbred mare Twilight has been available for a decade and, together with advances in genomics technologies, has led to unparalleled developments in equine genomics. At the core of this progress is the continuing improvement of the quality, contiguity and completeness of the reference genome, and its functional annotation. Recent achievements include the release of the next version of the reference genome (EquCab3.0) and generation of a reference sequence for the Y chromosome. Horse satellite-free centromeres provide unique models for mammalian centromere research. Despite extremely low genetic diversity of the Y chromosome, it has been possible to trace patrilines of breeds and pedigrees and show that Y variation was lost in the past approximately 2300 years owing to selective breeding. The high-quality reference genome has led to the development of three different SNP arrays and WGSs of almost 2000 modern individual horses. The collection of WGS of hundreds of ancient horses is unique and not available for any other domestic species. These tools and resources have led to global population studies dissecting the natural history of the species and genetic makeup and ancestry of modern breeds. Most importantly, the available tools and resources, together with the discovery of functional elements, are dissecting molecular causes of a growing number of Mendelian and complex traits. The improved understanding of molecular underpinnings of various traits continues to benefit the health and performance of the horse whereas also serving as a model for complex disease across species.

Signatures of selection in Charolais beef cattle identified by genome-wide analysis.

Charolais cattle are one of the most important breeds for meat production worldwide; in México, its selection is mainly made by live weight traits. One strategy for mapping important genomic regions that might influence productive traits is the identification of signatures of selection. This type of genomic features contains loci with extended linkage disequilibrium (LD) and homozygosity patterns that are commonly associated with sites of quantitative trait locus (QTL). Therefore, the objective of this study was to identify the signatures of selection in Charolais cattle genotyped with the GeneSeek Genomic Profiler Bovine HD panel consisting of 77 K single nucleotide polymorphisms (SNPs). A total 61,311 SNPs and 819 samples were used for the analysis. Identification of signatures of selection was carried out using the integrated haplotype score (iHS) methodology implemented in the rehh R package. The top ten SNPs with the highest piHS values were located on BTA 4, 5, 6 and 14. By identifying markers in LD with top ten SNPs, the candidate regions defined were mapped to 52.8-59.3 Mb on BTA 4; 67.5-69.3 on BTA 5; 39.5-41.0 Mb on BTA 6; and 26.4-29.6 Mb on BTA 14. The comparison of these candidate regions with the bovine QTLdb effectively confirmed the association (p < 0.05) with QTL related to growth traits and other important productive traits. The genomic regions identified in this study indicated selection for growth traits on the Charolais population via the conservation of haplotypes on various chromosomes. These genomic regions and their associated genes could serve as the basis for haplotype association studies and for the identification of causal genes related to growth traits.