A Whole Genome Association Study on Meat Palatability in Hanwoo

Hyeong, KiEun; Lee, Y.-M.; Kim, Y.-S.; Nam, Ki-Chang; Jo, Cheor-Lae; Lee, K.-H.; Lee, J.-E.; Kim, J.-J.

doi:10.5713/ajas.2014.14258

Cited by 7 publications

(5 citation statements)

References 35 publications

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“…A genome-wide association study (GWAS) was performed using a mixed linear model implemented in GCTA v.1.91.4 beta3 [39]. Farm (1419), birth year (2006-2016), birth month (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12), slaughter year (2008-2018), slaughter month (1-12), age (17-62 months), slaughter place (53), sire (324), and dam (8331) were tested for fixed effects. Fixed effects that were significant for all the traits were fitted in the model; this included farm, birth year, slaughter year, slaughter place, age, and sire.…”

Section: Genome-wide Association Analysis Heritability and Variancementioning

confidence: 99%

“…A genome-wide association study (GWAS) is an affordable and powerful tool to discover candidate genes and loci associated with quantitative traits [7]. GWASs in livestock, including in Hanwoo [8][9][10][11], have resulted in remarkable insights into the genetic architecture of carcass traits. Genetic variation in complex traits such as carcass and meat quality traits are, however, due to the contribution of many mutations with small effects [1,12] (polygenic effect).…”

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confidence: 99%

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A Gene-Set Enrichment and Protein–Protein Interaction Network-Based GWAS with Regulatory SNPs Identifies Candidate Genes and Pathways Associated with Carcass Traits in Hanwoo Cattle

Srikanth

Lee

Chung³

et al. 2020

Genes

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Non-synonymous SNPs and protein coding SNPs within the promoter region of genes (regulatory SNPs) might have a significant effect on carcass traits. Imputed sequence level data of 10,215 Hanwoo bulls, annotated and filtered to include only regulatory SNPs (450,062 SNPs), were used in a genome-wide association study (GWAS) to identify loci associated with backfat thickness (BFT), carcass weight (CWT), eye muscle area (EMA), and marbling score (MS). A total of 15, 176, and 1 SNPs were found to be significantly associated (p < 1.11 × 10 −7 ) with BFT, CWT, and EMA, respectively. The significant loci were BTA4 (CWT), BTA6 (CWT), BTA14 (CWT and EMA), and BTA19 (BFT). BayesR estimated that 1.1%~1.9% of the SNPs contributed to more than 0.01% of the phenotypic variance. So, the GWAS was complemented by a gene-set enrichment (GSEA) and protein-protein interaction network (PPIN) analysis in identifying the pathways affecting carcass traits. At p < 0.005 (~2,261 SNPs), 25 GO and 18 KEGG categories, including calcium signaling, cell proliferation, and folate biosynthesis, were found to be enriched through GSEA. The PPIN analysis showed enrichment for 81 candidate genes involved in various pathways, including the PI3K-AKT, calcium, and FoxO signaling pathways. Our finding provides insight into the effects of regulatory SNPs on carcass traits.Genes 2020, 11, 316 2 of 22 and eye muscle area (EMA) [4]. Though substantial improvement in carcass and meat quality have been achieved, due to market requirement for higher quality, and for improving the economic value of Hanwoo, continuous improvement of economically important trait is required [5,6]. A genome-wide association study (GWAS) is an affordable and powerful tool to discover candidate genes and loci associated with quantitative traits [7]. GWASs in livestock, including in Hanwoo [8][9][10][11], have resulted in remarkable insights into the genetic architecture of carcass traits. Genetic variation in complex traits such as carcass and meat quality traits are, however, due to the contribution of many mutations with small effects [1,12] (polygenic effect). Though some of these mutations have been successfully identified through GWASs, the high significance thresholds required to correct for the multiple testing problem results in the identification of only SNPs with a large effect size [7,12]. Further, a GWAS does not make use of the fact that genes work together in a network, and multi-allelic QTL might not be captured due to the bi-allelic nature of SNPs [13]. Moreover, epistasis is an important genetic component underlying phenotypic variation that also accounts for missing heritability [14]. Therefore, a GWAS alone might result in only limited understanding of the nature of complex traits [13]. Suggested solutions to overcome this limitation and understand the genetic complexities regulating complex traits are to complement a GWAS with gene-set enrichment, a protein-protein interaction network (PPIN), and pathway analyses [15][16][17][18]. In GSEA and pathway analysis, a g...

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Section: Genome-wide Association Analysis Heritability and Variancementioning

confidence: 99%

mentioning

confidence: 99%

A Gene-Set Enrichment and Protein–Protein Interaction Network-Based GWAS with Regulatory SNPs Identifies Candidate Genes and Pathways Associated with Carcass Traits in Hanwoo Cattle

Srikanth

Lee

Chung³

et al. 2020

Genes

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“…To meet the consumers’ demands, the selection of the Hanwoo breed has been focused on individuals with high intramuscular fat content (Lee et al, 2014). Few GWAS studies have been reported in Hanwoo cattle for traits like marbling, meat quality and sensory traits (Lee et al, 2010; Kim et al, 2011; Hyeong et al, 2014); however, no studies have examined the meat quality traits such as fat color, meat color and meat texture. Similarly, there is no published study, which uses imputed WGS data for these meat quality traits.…”

Section: Introductionmentioning

confidence: 99%

Genome-Wide Association Study of Meat Quality Traits in Hanwoo Beef Cattle Using Imputed Whole-Genome Sequence Data

et al. 2019

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The discovery of single nucleotide polymorphisms (SNP) and the subsequent genotyping of large numbers of animals have enabled large-scale analyses to begin to understand the biological processes that underpin variation in animal populations. In beef cattle, genome-wide association studies using genotype arrays have revealed many quantitative trait loci (QTL) for various production traits such as growth, efficiency and meat quality. Most studies regarding meat quality have focused on marbling, which is a key trait associated with meat eating quality. However, other important traits like meat color, texture and fat color have not commonly been studied. Developments in genome sequencing technologies provide new opportunities to identify regions associated with these traits more precisely. The objective of this study was to estimate variance components and identify significant variants underpinning variation in meat quality traits using imputed whole genome sequence data. Phenotypic and genomic data from 2,110 Hanwoo cattle were used. The estimated heritabilities for the studied traits were 0.01, 0.16, 0.31, and 0.49 for fat color, meat color, meat texture and marbling score, respectively. Marbling score and meat texture were highly correlated. The genome-wide association study revealed 107 significant SNPs located on 14 selected chromosomes (one QTL region per selected chromosome). Four QTL regions were identified on BTA2, 12, 16, and 24 for marbling score and two QTL regions were found for meat texture trait on BTA12 and 29. Similarly, three QTL regions were identified for meat color on BTA2, 14 and 24 and five QTL regions for fat color on BTA7, 10, 12, 16, and 21. Candidate genes were identified for all traits, and their potential influence on the given trait was discussed. The significant SNP will be an important inclusion into commercial genotyping arrays to select new breeding animals more accurately.

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“…Some GWAS studies have been performed in Korean Hanwoo cattle 30 , Korean beef cattle 31 , and Australian taurine and indicine cattle 4 to detect SNPs associated with carcass and meat quantity traits. However, none of these reports focused on pathways in beef cattle.…”

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confidence: 99%

Pathway-Based Genome-Wide Association Studies for Two Meat Production Traits in Simmental Cattle

Fan

Zhou

et al. 2015

Sci Rep

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Most single nucleotide polymorphisms (SNPs) detected by genome-wide association studies (GWAS), explain only a small fraction of phenotypic variation. Pathway-based GWAS were proposed to improve the proportion of genes for some human complex traits that could be explained by enriching a mass of SNPs within genetic groups. However, few attempts have been made to describe the quantitative traits in domestic animals. In this study, we used a dataset with approximately 7,700,000 SNPs from 807 Simmental cattle and analyzed live weight and longissimus muscle area using a modified pathway-based GWAS method to orthogonalise the highly linked SNPs within each gene using principal component analysis (PCA). As a result, of the 262 biological pathways of cattle collected from the KEGG database, the gamma aminobutyric acid (GABA)ergic synapse pathway and the non-alcoholic fatty liver disease (NAFLD) pathway were significantly associated with the two traits analyzed. The GABAergic synapse pathway was biologically applicable to the traits analyzed because of its roles in feed intake and weight gain. The proposed method had high statistical power and a low false discovery rate, compared to those of the smallest P-value and SNP set enrichment analysis methods.

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A Whole Genome Association Study on Meat Palatability in Hanwoo

Cited by 7 publications

References 35 publications

A Gene-Set Enrichment and Protein–Protein Interaction Network-Based GWAS with Regulatory SNPs Identifies Candidate Genes and Pathways Associated with Carcass Traits in Hanwoo Cattle

A Gene-Set Enrichment and Protein–Protein Interaction Network-Based GWAS with Regulatory SNPs Identifies Candidate Genes and Pathways Associated with Carcass Traits in Hanwoo Cattle

Genome-Wide Association Study of Meat Quality Traits in Hanwoo Beef Cattle Using Imputed Whole-Genome Sequence Data

Pathway-Based Genome-Wide Association Studies for Two Meat Production Traits in Simmental Cattle

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