Runs of homozygosity and signatures of selection: a comparison among eight local Swiss sheep breeds

A dataset consisting of 787 animals with high‐density SNP chip genotypes (346 774 SNPs) and 939 animals with medium‐density SNP chip genotypes (33 828 SNPs) from eight indigenous Swiss sheep breeds was analyzed to characterize population structure, quantify genomic inbreeding based on runs of homozygosity and identify selection signatures. In concordance with the recent known history of these breeds, the highest genetic diversity was observed in Engadine Red sheep and the lowest in Valais Blacknose sheep. Correlation between F_PED and F_ROH was around 0.50 and thereby lower than that found in similar studies in cattle. Mean F_ROH estimates from medium‐density data and HD data were highly correlated (0.95). Signatures of selection and candidate gene analysis revealed that the most prominent signatures of selection were found in the proximity of genes associated with body size (NCAPG, LCORL, LAP3, SPP1, PLAG1, ALOX12, TP53), litter size (SPP1), milk production (ABCG2, SPP1), coat color (KIT, ASIP, TBX3) and horn status (RXFP2). For the Valais Blacknose sheep, the private signatures in proximity of genes/QTL influencing body size, coat color and fatty acid composition were confirmed based on runs of homozygosity analysis. These private signatures underline the genetic uniqueness of the Valais Blacknose sheep breed. In conclusion, we identified differences in the genetic make‐up of Swiss sheep breeds, and we present relevant candidate genes responsible for breed differentiation in locally adapted breeds.     

Genome-Wide Specific Selection in Three Domestic Sheep Breeds

Background

Commercial sheep raised for mutton grow faster than traditional Chinese sheep breeds. Here, we aimed to evaluate genetic selection among three different types of sheep breed: two well-known commercial mutton breeds and one indigenous Chinese breed.

Results

We first combined locus-specific branch lengths and d_i statistical methods to detect candidate regions targeted by selection in the three different populations. The results showed that the genetic distances reached at least medium divergence for each pairwise combination. We found these two methods were highly correlated, and identified many growth-related candidate genes undergoing artificial selection. For production traits, APOBR and FTO are associated with body mass index. For meat traits, ALDOA, STK32B and FAM190A are related to marbling. For reproduction traits, CCNB2 and SLC8A3 affect oocyte development. We also found two well-known genes, GHR (which affects meat production and quality) and EDAR (associated with hair thickness) were associated with German mutton merino sheep. Furthermore, four genes (POL, RPL7, MSL1 and SHISA9) were associated with pre-weaning gain in our previous genome-wide association study.

Conclusions

Our results indicated that combine locus-specific branch lengths and d_i statistical approaches can reduce the searching ranges for specific selection. And we got many credible candidate genes which not only confirm the results of previous reports, but also provide a suite of novel candidate genes in defined breeds to guide hybridization breeding.     

Detection of selection signatures in dairy and beef cattle using high-density genomic information

Background

Artificial selection for economically important traits in cattle is expected to have left distinctive selection signatures on the genome. Access to high-density genotypes facilitates the accurate identification of genomic regions that have undergone positive selection. These findings help to better elucidate the mechanisms of selection and to identify candidate genes of interest to breeding programs.

Results

Information on 705 243 autosomal single nucleotide polymorphisms (SNPs) in 3122 dairy and beef male animals from seven cattle breeds (Angus, Belgian Blue, Charolais, Hereford, Holstein-Friesian, Limousin and Simmental) were used to detect selection signatures by applying two complementary methods, integrated haplotype score (iHS) and global fixation index (F_ST). To control for false positive results, we used false discovery rate (FDR) adjustment to calculate adjusted iHS within each breed and the genome-wide significance level was about 0.003. Using the iHS method, 83, 92, 91, 101, 85, 101 and 86 significant genomic regions were detected for Angus, Belgian Blue, Charolais, Hereford, Holstein-Friesian, Limousin and Simmental cattle, respectively. None of these regions was common to all seven breeds. Using the F_ST approach, 704 individual SNPs were detected across breeds. Annotation of the regions of the genome that showed selection signatures revealed several interesting candidate genes i.e. DGAT1, ABCG2, MSTN, CAPN3, FABP3, CHCHD7, PLAG1, JAZF1, PRKG2, ACTC1, TBC1D1, GHR, BMP2, TSG1, LYN, KIT and MC1R that play a role in milk production, reproduction, body size, muscle formation or coat color. Fifty-seven common candidate genes were found by both the iHS and global F_ST methods across the seven breeds. Moreover, many novel genomic regions and genes were detected within the regions that showed selection signatures; for some candidate genes, signatures of positive selection exist in the human genome. Multilevel bioinformatic analyses of the detected candidate genes suggested that the PPAR pathway may have been subjected to positive selection.

Conclusions

This study provides a high-resolution bovine genomic map of positive selection signatures that are either specific to one breed or common to a subset of the seven breeds analyzed. Our results will contribute to the detection of functional candidate genes that have undergone positive selection in future studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0127-3) contains supplementary material, which is available to authorized users.     

Multiple genomic signatures of selection in goats and sheep indigenous to a hot arid environment

Goats and sheep are versatile domesticates that have been integrated into diverse environments and production systems. Natural and artificial selection have shaped the variation in the two species, but natural selection has played the major role among indigenous flocks. To investigate signals of natural selection, we analyzed genotype data generated using the caprine and ovine 50K SNP BeadChips from Barki goats and sheep that are indigenous to a hot arid environment in Egypt''s Coastal Zone of the Western Desert. We identify several candidate regions under selection that spanned 119 genes. A majority of the genes were involved in multiple signaling and signal transduction pathways in a wide variety of cellular and biochemical processes. In particular, selection signatures spanning several genes that directly or indirectly influenced traits for adaptation to hot arid environments, such as thermo-tolerance (melanogenesis) (FGF2, GNAI3, PLCB1), body size and development (BMP2, BMP4, GJA3, GJB2), energy and digestive metabolism (MYH, TRHDE, ALDH1A3), and nervous and autoimmune response (GRIA1, IL2, IL7, IL21, IL1R1) were identified. We also identified eight common candidate genes under selection in the two species and a shared selection signature that spanned a conserved syntenic segment to bovine chromosome 12 on caprine and ovine chromosomes 12 and 10, respectively, providing, most likely, the evidence for selection in a common environment in two different but closely related species. Our study highlights the importance of indigenous livestock as model organisms for investigating selection sweeps and genome-wide association mapping.     

Genomic scans for selection signatures revealed candidate genes for adaptation and production traits in a variety of cattle breeds

Domestication and selection are the major driving forces responsible for the determinative genetic variability in livestock. These selection patterns create unique genetic signatures within the genome. BovineSNP50 chip data from 236 animals (seven indicine and five taurine cattle breeds) were analyzed in the present study. We implemented three complementary approaches viz. iHS (Integrated haplotype score), ROH (Runs of homozygosity), and F_ST, to detect selection signatures. A total of 179, 56, and 231 regions revealed 518, 277, and 267 candidate genes identified by iHS, ROH, and F_ST methods, respectively. We found several candidate genes (e.g., NCR3, ARID5A, HIST1H2BN, DEFB4, DEFB7, HSPA1L, HSPA1B, and DNAJB4) related to production traits and the adaptation of indigenous breeds to local environmental constraints such as heat stress and disease susceptibility. However, further studies are warranted to refine the findings using a larger sample size, whole-genome sequencing, and/or high density genotyping.     

Detection of selection signatures in the genome of a farmed population of anadromous rainbow trout (Oncorhynchus mykiss)

Domestication processes and artificial selection are likely to leave signatures that can be detected at a molecular level in farmed rainbow trout (Oncorhynchus mykiss). These signatures of selection are genomic regions that contain functional genetic variants conferring a higher fitness to their bearers. We genotyped 749 rainbow trout from a commercial population using a rainbow trout Axiom 57 K SNP array panel and identified putative genomic regions under selection using the pcadapt, Composite Likelihood Ratio (CLR) and Integrated Haplotype Score (iHS) methods. After applying quality-control pipelines and statistical analyses, we detected 12, 96 and 16 SNPs putatively under selection, associated with 96, 781 and 115 candidate genes, respectively. Several of these candidate genes were associated with growth, early development, reproduction, behavior and immune system traits. In addition, some of the SNPs were found in interesting regions located in autosomal inversions on Omy05 and Omy20. These findings could represent a genome-wide map of selection signatures in farmed rainbow trout and could be important in explaining domestication and selection for genetic traits of commercial interest.     

Uncovering Signals of Positive Selection in Peruvian Populations from Three Ecological Regions

Peru hosts extremely diverse ecosystems which can be broadly classified into the following three major ecoregions: the Pacific desert coast, the Andean highlands, and the Amazon rainforest. Since its initial peopling approximately 12,000 years ago, the populations inhabiting such ecoregions might have differentially adapted to their contrasting environmental pressures. Previous studies have described several candidate genes underlying adaptation to hypobaric hypoxia among Andean highlanders. However, the adaptive genetic diversity of coastal and rainforest populations has been less studied. Here, we gathered genome-wide single-nucleotide polymorphism-array data from 286 Peruvians living across the three ecoregions and analyzed signals of recent positive selection through population differentiation and haplotype-based selection scans. Among highland populations, we identify candidate genes related to cardiovascular function (TLL1, DUSP27, TBX5, PLXNA4, SGCD), to the Hypoxia-Inducible Factor pathway (TGFA, APIP), to skin pigmentation (MITF), as well as to glucose (GLIS3) and glycogen metabolism (PPP1R3C, GANC). In contrast, most signatures of adaptation in coastal and rainforest populations comprise candidate genes related to the immune system (including SIGLEC8, TRIM21, CD44, and ICAM1 in the coast; CBLB and PRDM1 in the rainforest; and BRD2, HLA-DOA, HLA-DPA1 regions in both), possibly as a result of strong pathogen-driven selection. This study identifies candidate genes related to human adaptation to the diverse environments of South America.     

Genome-wide scans identify known and novel regions associated with prolificacy and reproduction traits in a sub-Saharan African indigenous sheep (Ovis aries)

Maximizing the number of offspring born per female is a key functionality trait in commercial- and/or subsistence-oriented livestock enterprises. Although the number of offspring born is closely associated with female fertility and reproductive success, the genetic control of these traits remains poorly understood in sub-Saharan Africa livestock. Using selection signature analysis performed on Ovine HD BeadChip data from the prolific Bonga sheep in Ethiopia, 41 candidate regions under selection were identified. The analysis revealed one strong selection signature on a candidate region on chromosome X spanning BMP15, suggesting this to be the primary candidate prolificacy gene in the breed. The analysis also identified several candidate regions spanning genes not reported before in prolific sheep but underlying fertility and reproduction in other species. The genes associated with female reproduction traits included SPOCK1 (age at first oestrus), GPR173 (mediator of ovarian cyclicity), HB-EGF (signalling early pregnancy success) and SMARCAL1 and HMGN3a (regulate gene expression during embryogenesis). The genes involved in male reproduction were FOXJ1 (sperm function and successful fertilization) and NME5 (spermatogenesis). We also observed genes such as PKD2L2, MAGED1 and KDM3B, which have been associated with diverse fertility traits in both sexes of other species. The results confirm the complexity of the genetic mechanisms underlying reproduction while suggesting that prolificacy in the Bonga sheep, and possibly African indigenous sheep is partly under the control of BMP15 while other genes that enhance male and female fertility are essential for reproductive fitness.

     

Whole-genome resequencing reveals selection signatures associated with milk production traits in African Kenana dairy zebu cattle

Milk production and composition are the most economically important traits affecting profitability in dairy cattle. In this study, we aimed at detecting signatures of positive selection in Kenana, known as one of the high milk production African indigenous zebu cattle, using next-generation sequencing data. To detect genomic signatures of positive selection, we applied three methods based on population comparison, fixation index (F_ST), cross population composite likelihood ratio (XP-CLR) and nucleotide diversity (Pi). Further analysis showed that several candidate genes such as CSN3, IGFBP-2, RORA, ABCG2, B4GALT1 and GHR are positively selected for milk production traits in Kenana cattle. The candidate genes and enriched pathways identified in this study may provide a basis for future genome-wide association studies and investigations into genomic targets of selection in dairy cattle.     

Genotyping of the prion protein (PrP) gene in Red Maasai and Black Head Persian sheep in Tanzania

Susceptibility to scrapie in sheep is largely influenced by four polymorphic amino acid positions of the ovine PrP gene at codons 136, 141, 154 and 171. Genotyping of corresponding DNA polymorphism can be used as a basis for selection decisions. A total of 100 Red Maasai and 79 Black Herd Persian sheep, representative of the widely distributed breeds in Tanzania, were genotyped by real-time PCR. Genomic DNA was extracted from buccal epithelial cells. We report six genotypes derived from four different alleles, with the ARQ/ARQ genotype being more frequent (p = 0.0081) in the Red Maasai than in the Black Head Persian sheep. Our study also demonstrated higher allelic frequency (p = 0.00055) of the ARQ in the Red Maasai than in Black Head Persian sheep, while the AHQ allelic frequency was higher (p = 0.00086) in the Black Head Persian. All the animals were homozygous LL₁₄₁. The highly susceptible VRQ allele was not found in any of the sheep breeds examined in this study. Both breeds were genetically low-level resistant to scrapie (NSP3). Due to absence or very low frequency of the ARR allele in the two breeds, selection for genetic resistance to scrapie through an increase of the ARR allele does not seem very relevant. If new breeds of sheep are to be introduced for crossbreeding in Tanzania, care should be taken to avoid import of the VRQ allele. To our knowledge, this is the first study exploring the PrP genotypes in sub-Saharan African sheep and in the Red Maasai and Black Head Persian sheep breeds in particular. The data provide base-line information on genetic susceptibility of the two sheep breeds to scrapie, which may be useful in policy formulation for prevention and future research on prion diseases.     

Signatures of adaptation and genetic structure among the mainland populations of Pinus radiata (D. Don) inferred from SNP loci

Insights into the relative contributions of locus specific and genome-wide effects on population genetic diversity can be gained through separation of their resulting genetic signals. Here we explore patterns of adaptive and neutral genetic diversity in the disjunct natural populations of Pinus radiata (D. Don) from mainland California. A first-generation common garden of 447 individuals revealed significant differentiation of wood phenotypes among populations (P _ST), possibly reflecting local adaptation in response to environment. We subsequently screened all trees for genetic diversity at 149 candidate gene single nucleotide polymorphism (SNP) loci for signatures of adaptation. Ten loci were identified as being possible targets of diversifying selection following F _ST outlier tests. Multivariate canonical correlation performed on a data set of 444 individuals identified significant covariance between environment, adaptive phenotypes and outlier SNP diversity, lending support to the case for local adaptation suggested from F _ST and P _ST tests. Covariation among discrete sets of outlier SNPs and adaptive phenotypes (inferred from multivariate loadings) with environment are supported by existing studies of candidate gene function and genotype–phenotype association. Canonical analyses failed to detect significant correlations between environment and 139 non-outlier SNP loci, which were applied to estimate neutral patterns of genetic differentiation among populations (F _ST 4.3 %). Using this data set, significant hierarchical structure was detected, indicating three populations on the mainland. The hierarchical relationships based on neutral SNP markers (and SSR) were in contrast with those inferred from putatively adaptive loci, potentially highlighting the independent action of selection and demography in shaping genetic structure in this species.     

Integration of selection signatures and multi-trait GWAS reveals polygenic genetic architecture of carcass traits in beef cattle

Carcass merits are widely considered as economically important traits affecting beef production in the beef cattle industry. However, the genetic basis of carcass traits remains to be well understood. Here, we applied multiple methods, including the Composite of Likelihood Ratio (CLR) and Genome-wide Association Study (GWAS), to explore the selection signatures and candidate variants affecting carcass traits. We identified 11,600 selected regions overlapping with 2214 candidate genes, and most of those were enriched in binding and gene regulation. Notably, we identified 66 and 110 potential variants significantly associated with carcass traits using single-trait and multi-traits analyses, respectively. By integrating selection signatures with single and multi-traits associations, we identified 12 and 27 putative genes, respectively. Several highly conserved missense variants were identified in OR5M13D, NCAPG, and TEX2. Our study supported polygenic genetic architecture of carcass traits and provided novel insights into the genetic basis of complex traits in beef cattle.     

Genetic diversity of two native sheep breeds by genome-wide analysis of single nucleotide polymorphisms

Wallachian and Sumava sheep are autochthonous breeds that have undergone a significant bottleneck effect and subsequent restoration efforts. The first objective of this study was to evaluate the degree of genetic variability of both breeds and, therefore, the current management of the breeding. The second was to determine whether these two breeds still retain their genetic uniqueness in relation to each other and other breeds, despite regenerative interventions. Our data consisted of 48 individuals of Sumava and 37 individuals of Wallachian sheep. The comparison data contained 25 other breeds (primarily European) from the HapMap dataset generated by the International Sheep Genomics Consortium. When comparing all 27 breeds, the Czech breeds clustered with 15 other breeds and formed a single branch with them according to Nei's distances. At the same time, however, the clusters of both breeds were integral and easily distinguishable from the others when displayed with principal component analysis (PCA). Population substructure analysis did not show any common genetic ancestry of the Czech national breeds and breeds used for regeneration or, eventually, breeds whose ancestral population was used for regeneration. The average values of F_ST were higher in Wallachian sheep (F_ST = 0.14) than in Sumava sheep (F_ST = 0.08). The linkage disequilibrium (LD) extension per autosome was higher in Wallachian than in Sumava sheep. Consequently, the N_e estimates five generations ago were 68 for Sumava versus 34 for Wallachian sheep. Both native Czech breeds exhibit a wide range of inbreeding based on the excess of homozygosity (F_HOM) among individuals, from ?0.04 to 0.16 in Sumava and from ?0.13 to 0.12 in Wallachian. Average inbreeding based on runs of homozygosity was 0.21 in Sumava and 0.27 in Wallachian. Most detected runs of homozygosity (ROH) were less than 5 Mb long for both breeds. ROH segments longer than 15 Mb were absent in Wallachian sheep. Concerning putative selection signatures, a total of 471 candidate genes in Wallachian sheep within 11 hotspots and 653 genes within 13 hotspots in Sumava sheep were identified. Czech breeds appear to be well differentiated from each other and other European breeds. Their genetic diversity is low, especially in the case of the Wallachian breed. Sumava is not so threatened by low diversity but has a larger share of the non-native gene pool.     

Evidence of positive selection towards Zebuine haplotypes in the BoLA region of Brangus cattle

The Brangus breed was developed to combine the superior characteristics of both of its founder breeds, Angus and Brahman. It combines the high adaptability to tropical and subtropical environments, disease resistance, and overall hardiness of Zebu cattle with the reproductive potential and carcass quality of Angus. It is known that the major histocompatibility complex (MHC, also known as bovine leucocyte antigen: BoLA), located on chromosome 23, encodes several genes involved in the adaptive immune response and may be responsible for adaptation to harsh environments. The objective of this work was to evaluate whether the local breed ancestry percentages in the BoLA locus of a Brangus population diverged from the estimated genome-wide proportions and to identify signatures of positive selection in this genomic region. For this, 167 animals (100 Brangus, 45 Angus and 22 Brahman) were genotyped using a high-density single nucleotide polymorphism array. The local ancestry analysis showed that more than half of the haplotypes (55.0%) shared a Brahman origin. This value was significantly different from the global genome-wide proportion estimated by cluster analysis (34.7% Brahman), and the proportion expected by pedigree (37.5% Brahman). The analysis of selection signatures by genetic differentiation (F_st) and extended haplotype homozygosity-based methods (iHS and Rsb) revealed 10 and seven candidate regions, respectively. The analysis of the genes located within these candidate regions showed mainly genes involved in immune response-related pathway, while other genes and pathways were also observed (cell surface signalling pathways, membrane proteins and ion-binding proteins). Our results suggest that the BoLA region of Brangus cattle may have been enriched with Brahman haplotypes as a consequence of selection processes to promote adaptation to subtropical environments.     

Population Genomic Analyses Based on 1 Million SNPs in Commercial Egg Layers

Identifying signatures of selection can provide valuable insight about the genes or genomic regions that are or have been under selective pressure, which can lead to a better understanding of genotype-phenotype relationships. A common strategy for selection signature detection is to compare samples from several populations and search for genomic regions with outstanding genetic differentiation. Wright''s fixation index, F_ST, is a useful index for evaluation of genetic differentiation between populations. The aim of this study was to detect selective signatures between different chicken groups based on SNP-wise F_ST calculation. A total of 96 individuals of three commercial layer breeds and 14 non-commercial fancy breeds were genotyped with three different 600K SNP-chips. After filtering a total of 1 million SNPs were available for F_ST calculation. Averages of F_ST values were calculated for overlapping windows. Comparisons of these were then conducted between commercial egg layers and non-commercial fancy breeds, as well as between white egg layers and brown egg layers. Comparing non-commercial and commercial breeds resulted in the detection of 630 selective signatures, while 656 selective signatures were detected in the comparison between the commercial egg-layer breeds. Annotation of selection signature regions revealed various genes corresponding to productions traits, for which layer breeds were selected. Among them were NCOA1, SREBF2 and RALGAPA1 associated with reproductive traits, broodiness and egg production. Furthermore, several of the detected genes were associated with growth and carcass traits, including POMC, PRKAB2, SPP1, IGF2, CAPN1, TGFb2 and IGFBP2. Our approach demonstrates that including different populations with a specific breeding history can provide a unique opportunity for a better understanding of farm animal selection.     

Genome-wide analysis reveals population structure and selection in Chinese indigenous sheep breeds

Background

Traditionally, Chinese indigenous sheep were classified geographically and morphologically into three groups: Mongolian, Kazakh and Tibetan. Herein, we aimed to evaluate the population structure and genome selection among 140 individuals from ten representative Chinese indigenous sheep breeds: Ujimqin, Hu, Tong, Large-Tailed Han and Lop breed (Mongolian group); Duolang and Kazakh (Kazakh group); and Diqing, Plateau-type Tibetan, and Valley-type Tibetan breed (Tibetan group).

Results

We analyzed the population using principal component analysis (PCA), STRUCTURE and a Neighbor-Joining (NJ)-tree. In PCA plot, the Tibetan and Mongolian groups were clustered as expected; however, Duolang and Kazakh (Kazakh group) were segregated. STRUCTURE analyses suggested two subpopulations: one from North China (Kazakh and Mongolian groups) and the other from the Southwest (Tibetan group). In the NJ-tree, the Tibetan group formed an independent branch and the Kazakh and Mongolian groups were mixed. We then used the d_i statistic approach to reveal selection in Chinese indigenous sheep breeds. Among the 599 genome sequence windows analyzed, sixteen (2.7%) exhibited signatures of selection in four or more breeds. We detected three strong selection windows involving three functional genes: RXFP2, PPP1CC and PDGFD. PDGFD, one of the four subfamilies of PDGF, which promotes proliferation and inhibits differentiation of preadipocytes, was significantly selected in fat type breeds by the Rsb (across pairs of populations) approach. Two consecutive selection regions in Duolang sheep were obviously different to other breeds. One region was in OAR2 including three genes (NPR2, SPAG8 and HINT2) the influence growth traits. The other region was in OAR 6 including four genes (PKD2, SPP1, MEPE, and IBSP) associated with a milk production quantitative trait locus. We also identified known candidate genes such as BMPR1B, MSRB3, and three genes (KIT, MC1R, and FRY) that influence lambing percentage, ear size and coat phenotypes, respectively.

Conclusions

Based on the results presented here, we propose that Chinese native sheep can be divided into two genetic groups: the thin type (Tibetan group), and the fat type (Mongolian and Kazakh group). We also identified important genes that drive valuable phenotypes in Chinese indigenous sheep, especially PDGFD, which may influence fat deposition in fat type sheep.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1384-9) contains supplementary material, which is available to authorized users.     

A genome-wide perspective on the diversity and selection signatures in indigenous goats using 53 K single nucleotide polymorphism array

Tibetan goats, Taihang goats, Jining grey goats, and Meigu goats are the representative indigenous goats in China, found in Qinghai-Tibet Plateau, Western pastoral area, Northern and Southern agricultural regions. Very few studies have conducted a comprehensive analysis of the genomic diversity and selection of these breeds. We genotyped 96 unrelated individuals, using goat 53 K Illumina BeadChip array, of the following goat breeds: Tibetan (TG), Taihang (THG), Jining grey (JGG), and Meigu (MGG). A total of 45 951 single nucleotide polymorphisms were filtered to estimate the genetic diversity and selection signatures. All breeds had a high proportion (over 95%) of polymorphic loci. The observed and excepted heterozygosity ranged from 0.338 (MGG) to 0.402 (JGG) and 0.339 (MGG) to 0.395 (JGG), respectively. Clustering analysis displayed a genetically distinct lineage for each breed, and their Fst were greater than 0.25, indicating that they had a higher genetic differentiation between groups. Furthermore, effective population size reduced in all four populations, indicating a loss of genetic diversity. In addition, runs of homozygosity were mainly distributed in 5–10 Mb. Lastly, we identified signature genes, which were closely related to high-altitude adaptation (ADIRF) and prolificity (CNTROB, SMC3, and PTEN). This study provides a valuable resource for future studies on genome-wide perspectives on the diversity and selection signatures of Chinese indigenous goats.     

Genome‐wide scans to detect positive selection in Large White and Tongcheng pigs

Due to the direction, intensity, duration and consistency of genetic selection, especially recent artificial selection, the production performance of domestic pigs has been greatly changed. Therefore, we reasoned that there must be footprints or selection signatures that had been left during domestication. In this study, with porcine 60K BeadChip genotyping data from both commercial Large White and local Chinese Tongcheng pigs, we calculated the extended haplotype homozygosity values of the two breeds using the long‐range haplotype method to detect selection signatures. We found 34 candidate regions, including 61 known genes, from Large White pigs and 25 regions comprising 57 known genes from Tongcheng pigs. Many selection signatures were found on SSC1, SSC4, SSC7 and SSC14 regions in both populations. According to quantitative trait loci and network pathway analyses, most of the regions and genes were linked to growth, reproduction and immune responses. In addition, the average genetic differentiation coefficient F_ST was 0.254, which means that there had already been a significant differentiation between the breeds. The findings from this study can contribute to further research on molecular mechanisms of pig evolution and domestication and also provide valuable references for improvement of their breeding and cultivation.