Dataset Information

Genome-wide association study between CNVs and milk production traits in Valle del Belice sheep.

ABSTRACT: Copy number variation (CNV) is a major source of genomic structural variation. The aim of this study was to detect genomic CNV regions (CNVR) in Valle del Belice dairy sheep population and to identify those affecting milk production traits. The GO analysis identified possible candidate genes and pathways related to the selected traits. We identified CNVs in 416 individuals genotyped using the Illumina OvineSNP50 BeadChip array. The CNV association using a correlation-trend test model was examined with the Golden Helix SVS 8.7.0 tool. Significant CNVs were detected when their adjusted p-value was <0.01 after false discovery rate (FDR) correction. We identified 7,208 CNVs, which gave 365 CNVRs after aggregating overlapping CNVs. Thirty-one CNVRs were significantly associated with one or more traits included in the analysis. All CNVRs, except those on OAR19, overlapped with quantitative trait loci (QTL), even if they were not directly related to the traits of interest. A total of 222 genes were annotated within the significantly associated CNVRs, most of which played important roles in biological processes related to milk production and health-related traits. Identification of the genes in the CNVRs associated with the studied traits will provide the basis for further investigation of their role in the metabolic pathways related to milk production and health traits.

SUBMITTER: Di Gerlando R

PROVIDER: S-EPMC6478285 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Genome-wide association study between CNVs and milk production traits in Valle del Belice sheep.

Di Gerlando Rosalia R Sutera Anna Maria AM Mastrangelo Salvatore S Tolone Marco M Portolano Baldassare B Sottile Gianluca G Bagnato Alessandro A Strillacci Maria Giuseppina MG Sardina Maria Teresa MT

PloS one 20190423 4

Copy number variation (CNV) is a major source of genomic structural variation. The aim of this study was to detect genomic CNV regions (CNVR) in Valle del Belice dairy sheep population and to identify those affecting milk production traits. The GO analysis identified possible candidate genes and pathways related to the selected traits. We identified CNVs in 416 individuals genotyped using the Illumina OvineSNP50 BeadChip array. The CNV association using a correlation-trend test model was examine ...[more]

PMID: 31013280

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Project description:BackgroundBecause very large numbers of single nucleotide polymorphisms (SNPs) are now available throughout the genome, they are particularly suitable for the detection of genomic regions where a reduction in heterozygosity has occurred and they offer new opportunities to improve the accuracy of inbreeding ([Formula: see text]) estimates. Runs of homozygosity (ROH) are contiguous lengths of homozygous segments of the genome where the two haplotypes inherited from the parents are identical. Here, we investigated the occurrence and distribution of ROH using a medium-dense SNP panel to characterize autozygosity in 516 Valle del Belice sheep and to identify the genomic regions with high ROH frequencies.ResultsWe identified 11,629 ROH and all individuals displayed at least one ROH longer than 1 Mb. The mean value of [Formula: see text] estimated from ROH longer than1 Mb was 0.084 ± 0.061. ROH that were shorter than 10 Mb predominated. The highest and lowest coverages of Ovis aries chromosomes (OAR) by ROH were on OAR24 and OAR1, respectively. The number of ROH per chromosome length displayed a specific pattern, with higher values for the first three chromosomes. Both number of ROH and length of the genome covered by ROH varied considerably between animals. Two hundred and thirty-nine SNPs were considered as candidate markers that may be under directional selection and we identified 107 potential candidate genes. Six genomic regions located on six chromosomes, corresponding to ROH islands, are presented as hotspots of autozygosity, which frequently coincided with regions of medium recombination rate. According to the KEGG database, most of these genes were involved in multiple signaling and signal transduction pathways in a wide variety of cellular and biochemical processes. A genome scan revealed the presence of ROH islands in genomic regions that harbor candidate genes for selection in response to environmental stress and which underlie local adaptation.ConclusionsThese results suggest that natural selection has, at least partially, a role in shaping the genome of Valle del Belice sheep and that ROH in the ovine genome may help to detect genomic regions involved in the determinism of traits under selection.

Project description:BackgroundSomatic cell score (SCS) has been promoted as a selection criterion to improve mastitis resistance. However, SCS from healthy and infected animals may be considered as separate traits. Moreover, imperfect sensitivity and specificity could influence animals' classification and impact on estimated variance components. This study was aimed at: (1) estimating the heritability of bacteria negative SCS, bacteria positive SCS, and infection status, (2) estimating phenotypic and genetic correlations between bacteria negative and bacteria positive SCS, and the genetic correlation between bacteria negative SCS and infection status, and (3) evaluating the impact of imperfect diagnosis of infection on variance component estimates.MethodsData on SCS and udder infection status for 1,120 ewes were collected from four Valle del Belice flocks. The pedigree file included 1,603 animals. The SCS dataset was split according to whether animals were infected or not at the time of sampling. A repeatability test-day animal model was used to estimate genetic parameters for SCS traits and the heritability of infection status. The genetic correlation between bacteria negative SCS and infection status was estimated using an MCMC threshold model, implemented by Gibbs Sampling.ResultsThe heritability was 0.10 for bacteria negative SCS, 0.03 for bacteria positive SCS, and 0.09 for infection status, on the liability scale. The genetic correlation between bacteria negative and bacteria positive SCS was 0.62, suggesting that they may be genetically different traits. The genetic correlation between bacteria negative SCS and infection status was 0.51. We demonstrate that imperfect diagnosis of infection leads to underestimation of differences between bacteria negative and bacteria positive SCS, and we derive formulae to predict impacts on estimated genetic parameters.ConclusionsThe results suggest that bacteria negative and bacteria positive SCS are genetically different traits. A positive genetic correlation between bacteria negative SCS and liability to infection was found, suggesting that the approach of selecting animals for decreased SCS should help to reduce mastitis prevalence. However, the results show that imperfect diagnosis of infection has an impact on estimated genetic parameters, which may reduce the efficiency of selection strategies aiming at distinguishing between bacteria negative and bacteria positive SCS.

Project description:Natural selection and domestication have shaped modern sheep populations into a vast range of phenotypically diverse breeds. Among these breeds, dairy sheep have a smaller population than meat sheep and wool sheep, and less research is performed on them, but the lactation mechanism in dairy sheep is critically important for improving animal-production methods. In this study, whole-genome sequences were generated from 10 sheep breeds, including 57 high-milk-yield sheep and 44 low-milk-yield sheep, to investigate the genetic signatures of milk production in dairy sheep, and 59,864,820 valid SNPs (Single Nucleotide Polymorphisms) were kept after quality control to perform population-genetic-structure analyses, gene-detection analyses, and gene-function-validation analyses. For the population-genetic-structure analyses, we carried out PCA (Principal Component Analysis), as well as neighbor-joining tree and structure analyses to classify different sheep populations. The sheep used in our study were well distributed in ten groups, with the high-milk-yield-group populations close to each other and the low-milk-yield-group populations showing similar classifications. To perform an exact signal-selection analysis, we used three different methods to find SNPs to perform gene-annotation analyses within the 995 common regions derived from the fixation index (FST), nucleotide diversity (Ɵπ), and heterozygosity rate (ZHp) results. In total, we found 553 genes that were located in these regions. These genes mainly participate in the protein-binding pathway and the nucleoplasm-interaction pathway, as revealed by the GO- and KEGG-function-enrichment analyses. After the gene selection and function analyses, we found that FCGR3A, CTSK, CTSS, ARNT, GHR, SLC29A4, ROR1, and TNRC18 were potentially related to sheep-milk-production traits. We chose the strongly selected genes, FCGR3A, CTSK, CTSS, and ARNT during the signal-selection analysis to perform a RT-qPCR (Reale time Quantitative Polymerase Chain Reaction) experiment to validate their expression-level relationship with milk production, and the results showed that FCGR3A has a significant negative relationship with sheep-milk production, while other three genes did not show any positive or negative relations. In this study, it was discovered and proven that the candidate gene FCGR3A potentially contributes to the milk production of dairy sheep and a basis was laid for the further study of the genetic mechanism underlying the strong milk-production traits of sheep.

Project description:Milk fatty acids are essential for many dairy product productions, while intramuscular fat (IMF) is associated with the quality of meat. The triacylglycerols (TAGs) are the major components of IMF and milk fat. Therefore, understanding the polymorphisms and genes linked to fat synthesis is important for animal production. Identifying quantitative trait loci (QTLs) and genes associated with milk and meat production traits has been the objective of various mapping studies in the last decade. Consistently, the QTLs on chromosomes 14, 15, and 9 have been found to be associated with milk and meat production traits in cattle, goat, and buffalo and sheep, respectively. Diacylglycerol O-acyltransferase 1 (DGAT1) gene has been reported on chromosomes 14, 15, and 9 in cattle, goat, and buffalo and sheep, respectively. Being a key role in fat metabolism and TAG synthesis, the DGAT1 has obtained considerable attention especially in animal milk production. In addition to milk production, DGAT1 has also been a subject of interest in animal meat production. Several polymorphisms have been documented in DGAT1 in various animal species including cattle, buffalo, goat, and sheep for their association with milk production traits. In addition, the DGAT1 has also been studied for their role in meat production traits in cattle, sheep, and goat. However, very limited studies have been conducted in cattle for association of DGAT1 with meat production traits in cattle. Moreover, not a single study reported the association of DGAT1 with meat production traits in buffalo; thus, further studies are warranted to fulfill this huge gap. Keeping in view the important role of DGAT1 in animal production, the current review article was designed to highlight the major development and new insights on DGAT1 effect on milk and meat production traits in cattle, buffalo, sheep, and goat. Moreover, we have also highlighted the possible future contributions of DGAT1 for the studied species.

Dataset Information

Genome-wide association study between CNVs and milk production traits in Valle del Belice sheep.

Publications

Genome-wide association study between CNVs and milk production traits in Valle del Belice sheep.

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