Genome‐wide association study reveals five nucleotide sequence variants for carcass traits in beef cattle

Kim, Y.; Ryu, Jihye; Woo, Jiyoung; Kim, J. B.; Kim, C. Y.; Lee, Chaeyoung

doi:10.1111/j.1365-2052.2010.02156.x

Cited by 36 publications

(42 citation statements)

References 11 publications

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“…For detecting genetic variations associated with beef carcass traits and meat quantity traits, GWAS have been conducted in Korean Hanwoo cattle (Lee et al, 2010), Korean beef cattle (Kim et al, 2011) and Australian taurine and indicine cattle (Bolormaa et al, 2011). Many significant SNPs were identified using the simple linear regression and stepwise regression procedures.…”

Section: Discussionmentioning

confidence: 99%

Multiple-trait genome-wide association study based on principal component analysis for residual covariance matrix

Gao

Jiang

et al. 2014

Heredity

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Given the drawbacks of implementing multivariate analysis for mapping multiple traits in genome-wide association study (GWAS), principal component analysis (PCA) has been widely used to generate independent 'super traits' from the original multivariate phenotypic traits for the univariate analysis. However, parameter estimates in this framework may not be the same as those from the joint analysis of all traits, leading to spurious linkage results. In this paper, we propose to perform the PCA for residual covariance matrix instead of the phenotypical covariance matrix, based on which multiple traits are transformed to a group of pseudo principal components. The PCA for residual covariance matrix allows analyzing each pseudo principal component separately. In addition, all parameter estimates are equivalent to those obtained from the joint multivariate analysis under a linear transformation. However, a fast least absolute shrinkage and selection operator (LASSO) for estimating the sparse oversaturated genetic model greatly reduces the computational costs of this procedure. Extensive simulations show statistical and computational efficiencies of the proposed method. We illustrate this method in a GWAS for 20 slaughtering traits and meat quality traits in beef cattle. Heredity (2014) 113, 526-532; doi:10.1038/hdy.2014.57; published online 2 July 2014 INTRODUCTIONWith the advance of high-throughput genotyping technology, the paradigm of mapping quantitative trait locus (QTL) based on the linkage analysis of sparse genetic markers has gradually shifted to genome-wide association studies (GWAS) based on thousands and thousands of single-nucleotide polymorphisms (SNPs). On the other hand, association studies tend to involve more than one quantitative traits or complex diseases located in different regions of chromosomes, allowing the investigation of common genetic risk factors underlying multiple traits. Although these traits could be analyzed separately with univariate genetic model, statistical methods and algorithms have been developed for simultaneously analyzing multiple

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Section: Discussionmentioning

confidence: 99%

Multiple-trait genome-wide association study based on principal component analysis for residual covariance matrix

Gao

Jiang

et al. 2014

Heredity

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“…According with Kim et al (2011) a high level of restriction, limiting the identification of markers associated with productive traits. In many situations with multiple tests, the FDR with more appropriate correction criterion could be least conservative (Weller et al, 1998).…”

Section: Resultsmentioning

confidence: 99%

Association between single-nucleotide polymorphisms and milk production traits in buffalo

Venturini¹,

Cardoso²,

Baldi³

et al. 2014

Genet. Mol. Res.

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ABSTRACT. The aim of this study was to identify single-nucleotide polymorphisms (SNPs) in buffaloes associated with milk yield and content, in addition to somatic cell scores based on the cross-species transferability of SNPs from cattle to buffalo. A total of 15,745 SNPs were analyzed, of which 1562 showed 1% significance and 4742 with 5% significance, which were associated for all traits studied. After application of Bonferroni's correction for multiple tests of the traits analyzed, we found 2 significant SNPs placed on cattle chromosomes BTA15 and BTA20, which are homologous to buffalo chromosomes BBU16 and BBU19, respectively. In this genome association study, we found several significant SNPs affecting buffalo milk production and quality. Furthermore, the use of the high-density bovine BeadChip was suitable for genomic analysis in buffaloes. Although extensive chromosome arm homology was described between cattle and buffalo, the exact chromosomal position of SNP GWAS for milk production traits in buffalo markers associated with these economically important traits in buffalo can be determined only through buffalo genome sequencing.

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“…As a result, a total of seven intragenic markers have been discovered to be associated with MS at selection signals of Korean cattle. The post-selection signal association analyses were more efficient than the genome-wide association analysis (Kim et al, 2011), which revealed only one nucleotide marker (rs109593638, human immunodeficiency virus type I enhance binding protein 3 (HIVEP3) intron 2, P < 1.01 × 10 −6 ) associated with MS. This is practical evidence that intensive directional selection for MS has resulted in selection signals on the bovine genome by augmenting allele frequencies of functional variants and their proximity variants.…”

Section: Discussionmentioning

confidence: 99%

“…A larger MS score signifies more abundant intramuscular fat. We used genotypes of 309 Korean cattle from a previous GWAS (Kim et al, 2011). Tissue samples of longissimus muscle were consecutively collected from the other 102 Korean cattle and genotyped in the current study.…”

Section: Phenotypesmentioning

confidence: 99%

“…Genetic markers were discovered within candidate genes encoding mitogenactivated protein kinase 6, peroxisomal proliferatoractivated receptor -γ coactivator-1α and sterol regulatory element binding factor 1 (P < 0.05; Ryu et al, 2012;Lee et al, 2013). Genetic association was examined more intensively through a genomewide association study (GWAS), but rs109593638 was the only nucleotide variant associated with MS (P < 1.27 × 10 −6 ; Kim et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

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Genetic association of marbling score with intragenic nucleotide variants at selection signals of the bovine genome

Ryu

Lee

2016

animal

Self Cite

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Selection signals of Korean cattle might be attributed largely to artificial selection for meat quality. Rapidly increased intragenic markers of newly annotated genes in the bovine genome would help overcome limited findings of genetic markers associated with meat quality at the selection signals in a previous study. The present study examined genetic associations of marbling score (MS) with intragenic nucleotide variants at selection signals of Korean cattle. A total of 39 092 nucleotide variants of 407 Korean cattle were utilized in the association analysis. A total of 129 variants were selected within newly annotated genes in the bovine genome. Their genetic associations were analyzed using the mixed model with random polygenic effects based on identical-by-state genetic relationships among animals in order to control for spurious associations produced by population structure. Genetic associations of MS were found ( P < 3.88 × 10 −4 ) with six intragenic nucleotide variants on bovine autosomes 3 (cache domain containing 1, CACHD1), 5 (like-glycosyltransferase, LARGE), 16 (cell division cycle 42 binding protein kinase alpha, CDC42BPA) and 21 (snurportin 1, SNUPN; protein tyrosine phosphatase, non-receptor type 9, PTPN9; chondroitin sulfate proteoglycan 4, CSPG4). In particular, the genetic associations with CDC42BPA and LARGE were confirmed using an independent data set of Korean cattle. The results implied that allele frequencies of functional variants and their proximity variants have been augmented by directional selection for greater MS and remain selection signals in the bovine genome. Further studies of fine mapping would be useful to incorporate favorable alleles in marker-assisted selection for MS of Korean cattle.

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Genome‐wide association study reveals five nucleotide sequence variants for carcass traits in beef cattle

Cited by 36 publications

References 11 publications

Multiple-trait genome-wide association study based on principal component analysis for residual covariance matrix

Multiple-trait genome-wide association study based on principal component analysis for residual covariance matrix

Association between single-nucleotide polymorphisms and milk production traits in buffalo

Genetic association of marbling score with intragenic nucleotide variants at selection signals of the bovine genome

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