Detect Selection Signatures Research Articles

Genetic Diversity and Selection Footprints in the Genome of Brazilian Soybean Cultivars.

Although Brazil is currently the largest soybean producer in the world, only a small number of studies have analyzed the genetic diversity of Brazilian soybean. These studies have shown the existence of a narrow genetic base. The objectives of this work were to analyze the population structure and genetic diversity, and to identify selection signatures in the genome of soybean germplasms from different companies in Brazil. A panel consisting of 343 soybean lines from Brazil, North America, and Asia was genotyped using genotyping by sequencing (GBS). Population structure was assessed by Bayesian and multivariate approaches. Genetic diversity was analyzed using metrics such as the fixation index, nucleotide diversity, genetic dissimilarity, and linkage disequilibrium. The software BayeScan was used to detect selection signatures between Brazilian and Asian accessions as well as among Brazilian germplasms. Region of origin, company of origin, and relative maturity group (RMG) all had a significant influence on population structure. Varieties belonging to the same company and especially to the same RMG exhibited a high level of genetic similarity. This result was exacerbated among early maturing accessions. Brazilian soybean showed significantly lower genetic diversity when compared to Asian accessions. This was expected, because the crop’s region of origin is its main genetic diversity reserve. We identified 7 genomic regions under selection between the Brazilian and Asian accessions, and 27 among Brazilian varieties developed by different companies. Associated with these genomic regions, we found 96 quantitative trait loci (QTLs) for important soybean breeding traits such as flowering, maturity, plant architecture, productivity components, pathogen resistance, and seed composition. Some of the QTLs associated with the markers under selection have genes of great importance to soybean’s regional adaptation. The results reported herein allowed to expand the knowledge about the organization of the genetic variability of the Brazilian soybean germplasm. Furthermore, it was possible to identify genomic regions under selection possibly associated with the adaptation of soybean to Brazilian environments.

Selection signatures for heat tolerance in Brazilian horse breeds.

Since domestication, horse breeds have adapted to their environments and differentiated from one another. This paper uses two methods to detect selection signatures in 23 horse breeds, eight of which are Brazilian (610 animals), both cold-blooded and warm-blooded, from temperate and tropical regions. These animals were genotyped using the GGP Equine BeadChip and we analysed the data by Principal Component Analysis (PCA). The samples were separated into groups based on their geographical area of origin and PCA results studied. The genomic regions under selection were detected by hapFLK and PCAdapt methodologies, identifying six regions under selection with at least one Brazilian horse breed. These regions contain genes associated with heat tolerance, skin colour, body size, energy production/metabolism, genes involved in protein degradation/turnover/DNA repair, genes reducing the impact of oxidative stress/cellular repair, and transcriptional regulation. This work confirmed LCORL and NCAPG gene regions in previous studies associated with body size on Equine Chromosome Autosome 3 (ECA3). On the same ECA3, a region implicating genes linked to coat colour was identified, also previously related to heat stress. Regions with genes coding heat shock proteins were found on ECA1 and 2, and many candidate genes for oxidation-reduction which are a natural response to heat stress. However, a larger sample size and whole-genome SNPs are needed to understand better and identify new candidate regions as well as their functional relation with heat tolerance.

Genomic selection signatures in Brazilian sheep breeds reared in a tropical environment

The molecular and genetic effects of heat stress are not as well understood as physiological effects. Heat Stress response should be considered one component of gene network coordinated across various cells, tissues and systems. Its action seeks to minimize the effects of the environment on cellular functions. The detection of selection signatures can identify genes and mutations associated with phenotypic traits even if they are no longer segregating within the populations of interest. This paper looked at 48 sheep breeds (1988 animals), of which 649 animals are from 6 Brazilian breeds reared in a tropical environment. These animals were genotyped using the 50 K SNP Chip. We applied different detection methods (HapFLK and PCAdapt) to identify genomic regions with selection signals (selection signatures). Three groups of breeds were defined, and the first component showed a clear separation between Hair_Warm and Wool_Cold groups. The second component showed some divergence between Wool_Cold and Wool_Warm, with some Hair_Warm breeds located together with Wool_Warm. Hair Brazilian breeds were separated from the others in the first breed component, while the second component segregated European breeds from African and Asian breeds. The four genomic regions identified in chromosomes 2, 7, 11 and 16 harbor several genes related to a wide range of functions. These include production traits (such as milk, growth and reproduction), metabolism (fat and energy), stress response (including immune and inflammation), as well as cell cycle functions. These genomic regions can be a starting point for identifying gene mutations and selecting adapted animals, mainly in a climate change scenario. The locally adapted tropical sheep breeds can be an important genetic reservoir of these thermotolerance genes.

Detection of selection signatures in South African Mutton Merino sheep using whole-genome sequencing data.

The South African Mutton Merino (SAMM), a dual-purpose (meat and wool) sheep breed, is characterized by its excellent performance on growth, carcass traits and meat quality compared to other fine-wool Merino breeds. Nowadays, the SAMM breed has been widely used to cross with commercial and indigenous fine-wool or coarse-wool breeds to improve the growth and meat performance in many countries. To date, however, little is known about the genetic basis for its prominent characteristics. In this study, whole-genome sequences of 10 SAMM were sequenced and the selection signatures were analyzed together with those of 39 Australian Merino and Chinese Merino (wool-type Merino) by FST , iHS, and XP-EHH methods. In total, 313genes in 277 regions were identified by at least 2methods with the signal of selection and 21 of them were identified by all three methods. We highlighted a list of interesting genes, including GHR, LCORL, SMO, NCAPG, DCC, IBSP, PPARGC1A, PACRGL, PRDM5, XYLB, AHCYL2, TEFM, AFG1L, and FAM184B, which have been shown to be involved in growth, carcass traits, and meat quality by previous studies. Herein, GHR, encoding a transmembrane receptor for growth hormone, is the most notable one. We report the first study on selection signatures analysis of SAMM at whole-genome sequence level. These results provide new insights into the genetic mechanisms underlying the growth and carcass traits in SAMM.

Genomic Uniqueness of Local Sheep Breeds From Morocco.

Sheep farming is a major source of meat in Morocco and plays a key role in the country’s agriculture. This study aims at characterizing the whole-genome diversity and demographic history of the main Moroccan sheep breeds, as well as to identify selection signatures within and between breeds. Whole genome data from 87 individuals representing the five predominant local breeds were used to estimate their level of neutral genetic diversity and to infer the variation of their effective population size over time. In addition, we used two methods to detect selection signatures: either for detecting selective sweeps within each breed separately or by detecting differentially selected regions by contrasting different breeds. We identified hundreds of genomic regions putatively under selection, which related to several biological terms involved in local adaptation or the expression of zootechnical performances such as Growth, UV protection, Cell maturation or Feeding behavior. The results of this study revealed selection signatures in genes that have an important role in traits of interest and increased our understanding of how genetic diversity is distributed in these local breeds. Thus, Moroccan local sheep breeds exhibit both a high genetic diversity and a large set of adaptive variations, and therefore, represent a valuable genetic resource for the conservation of sheep in the context of climate change.

Trait-specific Selection Signature Detection Reveals Novel Loci of Meat Quality in Large White Pigs

In past decades, meat quality traits have been shaped by human-driven selection in the process of genetic improvement programs. Exploring the potential genetic basis of artificial selection and mapping functional candidate genes for economic traits are of great significance in genetic improvement of pigs. In this study, we focus on investigating the genetic basis of five meat quality traits, including intramuscular fat content (IMF), drip loss, water binding capacity, pH at 45 min (pH45min), and ultimate pH (pH24h). Through making phenotypic gradient differential population pairs, Wright’s fixation index (FST) and the cross-population extended haplotype homozogysity (XPEHH) were applied to detect selection signatures for these five traits. Finally, a total of 427 and 307 trait-specific selection signatures were revealed by FST and XPEHH, respectively. Further bioinformatics analysis indicates that some genes, such as USF1, NDUFS2, PIGM, IGSF8, CASQ1, and ACBD6, overlapping with the trait-specific selection signatures are responsible for the phenotypes including fat metabolism and muscle development. Among them, a series of promising trait-specific selection signatures that were detected in the high IMF subpopulation are located in the region of 93544042-95179724bp on SSC4, and the genes harboring in this region are all related to lipids and muscle development. Overall, these candidate genes of meat quality traits identified in this analysis may provide some fundamental information for further exploring the genetic basis of this complex trait.

Genome-wide selection signatures detection in Shanghai Holstein cattle population identified genes related to adaption, health and reproduction traits

BackgroundOver several decades, a wide range of natural and artificial selection events in response to subtropical environments, intensive pasture and intensive feedlot systems have greatly changed the customary behaviour, appearance, and important economic traits of Shanghai Holstein cattle. In particular, the longevity of the Shanghai Holstein cattle population is generally short, approximately the 2nd to 3rd lactation. In this study, two complementary approaches, integrated haplotype score (iHS) and runs of homozygosity (ROH), were applied for the detection of selection signatures within the genome using genotyping by genome-reduced sequence data from 1092 cows.ResultsIn total, 101 significant iHS genomic regions containing selection signatures encompassing a total of 256 candidate genes were detected. There were 27 significant |iHS| genomic regions with a mean |iHS| score > 2. The average number of ROH per individual was 42.15 ± 25.47, with an average size of 2.95 Mb. The length of 78 % of the detected ROH was within the range of 1–2 MB and 2–4 MB, and 99 % were shorter than 8 Mb. A total of 168 genes were detected in 18 ROH islands (top 1 %) across 16 autosomes, in which each SNP showed a percentage of occurrence > 30 %. There were 160 and 167 genes associated with the 52 candidate regions within health-related QTL intervals and 59 candidate regions within reproduction-related QTL intervals, respectively. Annotation of the regions harbouring clustered |iHS| signals and candidate regions for ROH revealed a panel of interesting candidate genes associated with adaptation and economic traits, such as IL22RA1, CALHM3, ITGA9, NDUFB3, RGS3, SOD2, SNRPA1, ST3GAL4, ALAD, EXOSC10, and MASP2. In a further step, a total of 1472 SNPs in 256 genes were matched with 352 cis-eQTLs in 21 tissues and 27 trans-eQTLs in 6 tissues. For SNPs located in candidate regions for ROH, a total of 108 cis-eQTLs in 13 tissues and 4 trans-eQTLs were found for 1092 SNPs. Eighty-one eGenes were significantly expressed in at least one tissue relevant to a trait (P value < 0.05) and matched the 256 genes detected by iHS. For the 168 significant genes detected by ROH, 47 gene-tissue pairs were significantly associated with at least one of the 37 traits.ConclusionsWe provide a comprehensive overview of selection signatures in Shanghai Holstein cattle genomes by combining iHS and ROH. Our study provides a list of genes associated with immunity, reproduction and adaptation. For functional annotation, the cGTEx resource was used to interpret SNP-trait associations. The results may facilitate the identification of genes relevant to important economic traits and can help us better understand the biological processes and mechanisms affected by strong ongoing natural or artificial selection in livestock populations.

Detecting Selection in Multiple Populations by Modeling Ancestral Admixture Components.

One of the most powerful and commonly used approaches for detecting local adaptation in the genome is the identification of extreme allele frequency differences between populations. In this article, we present a new maximum likelihood method for finding regions under positive selection. It is based on a Gaussian approximation to allele frequency changes and it incorporates admixture between populations. The method can analyze multiple populations simultaneously and retains power to detect selection signatures specific to ancestry components that are not representative of any extant populations. Using simulated data, we compare our method to related approaches, and show that it is orders of magnitude faster than the state-of-the-art, while retaining similar or higher power for most simulation scenarios. We also apply it to human genomic data and identify loci with extreme genetic differentiation between major geographic groups. Many of the genes identified are previously known selected loci relating to hair pigmentation and morphology, skin, and eye pigmentation. We also identify new candidate regions, including various selected loci in the Native American component of admixed Mexican-Americans. These involve diverse biological functions, such as immunity, fat distribution, food intake, vision, and hair development.

Detecting the selection signatures in Chinese Duroc,Landrace, Yorkshire, Liangshan, and Qingyu pigs.

Here we used two kinds of chips data from 5 pig breeds, Chinese Duroc (DD), Landrace (LL), Yorkshire (YY), Liangshan (LS), and Qingyu pigs (QY) in China to identify genes which show evidence of selection during domestication. Four breed pairs, LS-YY, QY-YY, DD-YY, and LL-YY pair, were performed to detect selection signatures using the Fst method. Then we identified a list of genes that played key roles in domestication and artificial selection. For example, the PTPRM gene was shared in LS-YY, QY-YY, and DD-YY pairs and it regulates a variety of cellular processes including cell growth, differentiation as signaling molecules. The HACD3 gene was shared in QY-YY and DD-YY pairs, and the HACD3 protein is involved in the production of very long-chain fatty acids of different chain lengths. Besides, the MYH11 gene that related to muscle contraction was found in LS-YY and LL-YY pair. These results suggested that genes related to immunity, disease resistance, and metabolism were subjected to strong selection pressure in Chinese domestic pigs in the progress of domestication and evolution; however, genes related to appearance, production performance, and reproduction were undergone strong artificial selection in commercial pig breeds.

Genomic Analyses Revealed the Genetic Difference and Potential Selection Genes of Growth Traits in Two Duroc Lines.

Duroc pigs are famous for their high growth rate, feed conversion efficiency, and lean meat percentage. Given that they have been subjected to artificial selection and breeding in multiple countries, various lines with obvious differences in production performance have formed. In this study, we genotyped 3,770 American Duroc (AD) pigs and 2,098 Canadian Duroc (CD) pigs using the GeneSeek Porcine SNP50 Beadchip to dissect the genetic differences and potential selection genes of growth traits in these two Duroc pig lines. Population structure detection showed that there were significant genetic differences between the two Duroc pig lines. Hence, we performed FST and cross-population extended haplotype homozygosity (XP-EHH) analyses between the two lines. As a result, we identified 38 annotated genes that were significantly enriched in the gland development pathway in the AD line, and 61 annotated genes that were significantly enriched in the immune-related pathway in the CD line. For three growth traits including backfat thickness (BFT), loin muscle depth (LMD), and loin muscle area (LMA), we then performed selection signature detection at 5 and 10% levels within the line and identified different selected regions and a series of candidate genes that are involved in lipid metabolism and skeletal muscle development or repair, such as IRX3, EBF2, WNT10B, TLR2, PITX3, and SGCD. The differences in selected regions and genes between the two lines may be the cause of the differences in growth traits. Our study suggests significant genetic differences between the AD and CD lines, which provide a theoretical basis for selecting different Duroc lines as sires for different needs.

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.

Genome-wide scan for selection signatures based on whole-genome re-sequencing in Landrace and Yorkshire pigs

We performed a genome-wide scan to detect selection signatures that showed evidence of positive selection in the domestication process by re-sequencing the whole genomes of Landrace and Yorkshire pigs. Fifteen annotated elements with 13 associated genes were identified using the Z-transformed FST (Z(FST)) method, and 208 annotated elements with 140 associated genes were identified using the Z-transformed heterozygosity (ZHp) method. The functional analysis and the results of previous studies showed that most of the candidate genes were associated with basic metabolism, disease resistance, cellular processes, and biochemical signals, and several were related to body morphology and organs. They included PPP3CA, which plays an essential role in the transduction of intracellular Ca2+-mediated signals, and WWTR1, which plays a pivotal role in organ size control and tumor suppression. These results suggest that genes associated with body morphology were subject to selection pressure during domestication, whereas genes involved in basic metabolism and disease resistance were subject to selection during artificial breeding. Our findings provide new insights into the potential genetic variation of phenotypic diversity in different pig breeds and will help to better understand the selection effects of modern breeding in Landrace and Yorkshire pigs.

Genome-Wide Detection of Runs of Homozygosity in Laiwu Pigs Revealed by Sequencing Data.

Laiwu pigs, distinguished by their high intramuscular fat of 7–9%, is an indigenous pig breed of China, and recent studies also found that Laiwu pigs showed high resistance to Porcine circovirus type 2. However, with the introduction of commercial varieties, the population of Laiwu pigs has declined, and some lineages have disappeared, which could result in inbreeding. Runs of homozygosity (ROH) can be used as a good measure of individual inbreeding status and is also normally used to detect selection signatures so as to map the candidate genes associated with economically important traits. In this study, we used data from Genotyping by Genome Reducing and Sequencing to investigate the number, length, coverage, and distribution patterns of ROH in 93 Chinese Laiwu pigs and identified genomic regions with a high ROH frequency. The average inbreeding coefficient calculated by pedigree was 0.021, whereas that estimated by all detected ROH segments was 0.133. Covering 13.4% of the whole genome, a total of 7,508 ROH segments longer than 1 Mb were detected, whose average length was 3.76 Mb, and short segments (1–5 Mb) dominated. For individuals, the coverage was in the range between 0.56 and 36.86%. For chromosomes, SSC6 had the largest number (n = 688), and the number of ROH in SSC12 was the lowest (n = 215). Thirteen ROH islands were detected in our study, and 86 genes were found within those regions. Some of these genes were correlated with economically important traits, such as meat quality (ECI1, LRP12, NDUFA4L2, GIL1, and LYZ), immunity capacity (IL23A, STAT2, STAT6, TBK1, IFNG, and ITH2), production (DCSTAMP, RDH16, and GDF11), and reproduction (ODF1 and CDK2). A total of six significant Gene Ontology terms and nine significant Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were identified, most of which were correlated with disease resistance and biosynthesis processes, and one KEGG pathway was related to lipid metabolism. In addition, we aligned all of the ROH islands to the pig quantitative trait loci (QTL) database and finally found eight QTL related to the intramuscular fat trait. These results may help us understand the characteristics of Laiwu pigs and provide insight for future breeding strategies.

Genomic inbreeding and selection signatures in the local dairy breed Icelandic Cattle.

Icelandic Cattle is the only dairy cattle breed native to Iceland. It currently numbers ca. 26000 breeding females. We used 50k genotypes of over 8000 Icelandic Cattle to estimate genomic and pedigree-based inbreeding and to detect selection signatures using the integrated haplotype score. We used 47 Icelandic bulls genotyped with a 770k SNP chip to estimate LD decay for comparison with other Nordic dairy cattle breeds. We detected ROHs on the autosomes and computed ROH-based autosomal inbreeding coefficients. Average inbreeding coefficients according to pedigree and ROHs were 0.0621 and 0.101. Effective population sizes for the years 2009-2017 according to pedigree, ROHs, genomic relationship matrix, excess of homozygosity and individual increase in inbreeding were 81, 65, 60, 58 and 92 respectively. We identified three regions and six candidate genes that showed a signature of selection according to the integrated haplotype score (P<0.05) on chromosomes 1, 16 and 23. The LD structure of Icelandic Cattle is shaped by a long period of isolation and a small founder population. The estimate of LD at distances closer than 0.3Mb is lower in Icelandic Cattle than in Danish Jersey, but is higher than in Danish Holstein and Red Nordic Dairy Cattle breeds. Our findings show that inbreeding rates in Icelandic Cattle currently are sustainable according to FAO guidelines, and our results do not indicate severe historical inbreeding.

Shared Ancestry and Signatures of Recent Selection in Gotland Sheep.

Gotland sheep, a breed native to Gotland, Sweden (an island in the Baltic Sea), split from the Gute sheep breed approximately 100 years ago, and since, has probably been crossed with other breeds. This breed has recently gained popularity, due to its pelt quality. This study estimates the shared ancestors and identifies recent selection signatures in Gotland sheep using 600 K single nucleotide polymorphism (SNP) genotype data. Admixture analysis shows that the Gotland sheep is a distinct breed, but also has shared ancestral genomic components with Gute (~50%), Karakul (~30%), Romanov (~20%), and Fjällnäs (~10%) sheep breeds. Two complementary methods were applied to detect selection signatures: A Bayesian population differentiation FST and an integrated haplotype homozygosity score (iHS). Our results find that seven significant SNPs (q-value < 0.05) using the FST analysis and 55 significant SNPs (p-value < 0.0001) using the iHS analysis. Of the candidate genes that contain significant markers, or are in proximity to them, we identify several belongings to the keratin genes, RXFP2, ADCY1, ENOX1, USF2, COX7A1, ARHGAP28, CRYBB2, CAPNS1, FMO3, and GREB1. These genes are involved in wool quality, polled and horned phenotypes, fertility, twining rate, meat quality, and growth traits. In summary, our results provide shared founders of Gotland sheep and insight into genomic regions maintained under selection after the breed was formed. These results contribute to the detection of candidate genes and QTLs underlying economic traits in sheep.

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 FST, to detect selection signatures. A total of 179, 56, and 231 regions revealed 518, 277, and 267 candidate genes identified by iHS, ROH, and FST 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 for response to Aleutian mink disease virus infection in American mink

Aleutian disease (AD) is the most significant health issue for farmed American mink. The objective of this study was to identify the genomic regions subjected to selection for response to infection with Aleutian mink disease virus (AMDV) in American mink using genotyping by sequencing (GBS) data. A total of 225 black mink were inoculated with AMDV and genotyped using a GBS assay based on the sequencing of ApeKI-digested libraries. Five AD-characterized phenotypes were used to assign animals to pairwise groups. Signatures of selection were detected using integrated measurement of fixation index (FST) and nucleotide diversity (θπ), that were validated by haplotype-based (hap-FLK) test. The total of 99 putatively selected regions harbouring 63 genes were detected in different groups. The gene ontology revealed numerous genes related to immune response (e.g. TRAF3IP2, WDR7, SWAP70, CBFB, and GPR65), liver development (e.g. SULF2, SRSF5) and reproduction process (e.g. FBXO5, CatSperβ, CATSPER4, and IGF2R). The hapFLK test supported two strongly selected regions that contained five candidate genes related to immune response, virus–host interaction, reproduction and liver regeneration. This study provided the first map of putative selection signals of response to AMDV infection in American mink, bringing new insights into genomic regions controlling the AD phenotypes.

Concordance rate in cattle and sheep between genotypes differing in Illumina GenCall quality score.

Proper quality control of data prior to downstream analyses is fundamental to ensure integrity of results; quality control of genomic data is no exception. While many metrics of quality control of genomic data exist, the objective of the present study was to quantify the genotype and allele concordance rate between called single nucleotide polymorphism (SNP) genotypes differing in GenCall (GC) score; the GC score is a confidence measure assigned to each Illumina genotype call. This objective was achieved using Illumina beadchip genotype data from 771 cattle (12428767 genotypes in total post-editing) and 80 sheep (1557360 SNPs genotypes in total post-editing) each genotyped in duplicate. The called genotype with the lowest associated GC score was compared to the genotype called for the same SNP in the same duplicated animal sample but with a GC score of >0.90 (assumed to represent the true genotype). The mean genotype concordance rate for a GC score of <0.300, 0.300-0.549, and ≥0.550 in the cattle (sheep in parenthesis) was 0.9467 (0.9864), 0.9707 (0.9953), and 0.9994 (0.99997) respectively; the respective allele concordance rate was 0.9730 (0.9930), 0.9849 (0.9976), and 0.9997 (0.99998). Hence, concordance eroded as the GC score of the called genotype reduced, albeit the impact was not dramatic and was not very noticeable until a GC score of <0.55. Moreover, the impact was greater and more consistent in the cattle population than in the sheep population. Furthermore, an impact of GC score on genotype concordance rate existed even for the same SNP GenTrain value; the GenTrain value is a statistical score that depicts the shape of the genotype clusters and the relative distance between the called genotype clusters.

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 scan for selection signatures for litter size in goat breeds of Kerala

Genome-wide search to detect selection signatures harbouring candidate prolificacy genes was carried out in low prolific Attappady Black and high prolific Malabari goat breeds of Kerala. Selective sweep regions were identified by analysing the genotypic data generated by Illumina Goat SNP 50 Bead Chip sequencing of 48 animals (24 each of two breeds) using Out FLANK statistical method based on FST outlier approach. There were 2844 outlier SNPs at genome-wide significance level of P<0.01 and 595 protein coding genes linked to these outlier SNPs. Further analysis showed 16 candidate prolificacy genes inclusive of BMPR, PRLR, INHBB, ESR1, GHR, IGF1, LHCGR, LEPR, SMAD4, BMP2, NR5A2, MTNR1A, GRIA2, MEF2A and MFGE8 located in selection signals. Gene enrichment analysis showed significantly (P<0.05) over-represented 37 gene ontology (GO) biological processes, 14 GO molecular functions and 7 KEGG (Kyoto Encyclopaedia of Genes and Genomes) pathways. The information concerning candidate genes could be further utilised for association analysis for onward utilisation in the genetic improvement of litter size in goats.