본문 바로가기
KERD
논문

Genome-wide association studies to identify quantitative trait loci and positional candidate genes affecting meat quality-related traits in pigs

2

조회

0

다운로드

0

인용

0

참고문헌

키워드

주제분류축산학

초록

Meat quality comprises a set of key traits such as pH, meat color, water-holding capacity, tenderness and marbling. These traits are complex because they are affected by multiple genetic and environmental factors. The aim of this study was to investigate the molecular genetic basis underlying nine meat quality-related traits in a Yorkshire pig population using a genome- wide association study (GWAS) and subsequent biological pathway analysis. In total, 45,926 single nucleotide polymorphism (SNP) markers from 543 pigs were selected for the GWAS after quality control. Data were analyzed using a genome-wide efficient mixed model association (GEMMA) method. This linear mixed model-based approach identified two quantitative trait loci (QTLs) for meat color (b*) on chromosome 2 (SSC2) and one QTL for shear force on chromosome 8 (SSC8). These QTLs acted additively on the two phenotypes and explained 3.92%–4.57% of the phenotypic variance of the traits of interest. The genes encoding HAUS8 on SSC2 and an lncRNA on SSC8 were identified as positional candidate genes for these QTLs. The results of the biological pathway analysis revealed that positional candidate genes for meat color (b*) were enriched in pathways related to muscle development, muscle growth, intramuscular adipocyte differentiation, and lipid accumulation in muscle, whereas positional candidate genes for shear force were overrepresented in pathways related to cell growth, cell differentiation, and fatty acids synthesis. Further verification of these identified SNPs and genes in other independent populations could provide valuable information for understanding the variations in pork quality-related traits.

Abstract

Meat quality comprises a set of key traits such as pH, meat color, water-holding capacity, tenderness and marbling. These traits are complex because they are affected by multiple genetic and environmental factors. The aim of this study was to investigate the molecular genetic basis underlying nine meat quality-related traits in a Yorkshire pig population using a genome- wide association study (GWAS) and subsequent biological pathway analysis. In total, 45,926 single nucleotide polymorphism (SNP) markers from 543 pigs were selected for the GWAS after quality control. Data were analyzed using a genome-wide efficient mixed model association (GEMMA) method. This linear mixed model-based approach identified two quantitative trait loci (QTLs) for meat color (b*) on chromosome 2 (SSC2) and one QTL for shear force on chromosome 8 (SSC8). These QTLs acted additively on the two phenotypes and explained 3.92%–4.57% of the phenotypic variance of the traits of interest. The genes encoding HAUS8 on SSC2 and an lncRNA on SSC8 were identified as positional candidate genes for these QTLs. The results of the biological pathway analysis revealed that positional candidate genes for meat color (b*) were enriched in pathways related to muscle development, muscle growth, intramuscular adipocyte differentiation, and lipid accumulation in muscle, whereas positional candidate genes for shear force were overrepresented in pathways related to cell growth, cell differentiation, and fatty acids synthesis. Further verification of these identified SNPs and genes in other independent populations could provide valuable information for understanding the variations in pork quality-related traits.

참고문헌 (34)

  1. Tomasevic I, "Recent advances in meat color research", Curr Opin Food Sci, 41, pp.81~87 (2021)[DOI]
  2. Suzuki K, "Genetic parameter estimates of meat quality traits in Duroc pigs selected for average daily gain, longissimus muscle area, backfat thickness, and intramuscular fat content", J Anim Sci, 83, pp.2058~2065 (2005)[DOI]
  3. Grunert KG, "Consumer perception of meat quality and implications for product development in the meat sector—a review", Meat Sci, 66, pp.259~272 (2004)[DOI]
  4. Miar Y, "Genetic and phenotypic parameters for carcass and meat quality traits in commercial crossbred pigs", J Anim Sci, 92, pp.2869~2884 (2014)[DOI]
  5. Gao Y, "Application of genomic technologies to the improvement of meat quality of farm animals", Meat Sci, 77, pp.36~45 (2007)[DOI]
  6. Fujii J, "Identification of a mutation in porcine ryanodine receptor associated with malignant hyperthermia", Science, 253, pp.448~451 (1991)[DOI]
  7. Milan D, "A mutation in PRKAG3associated with excess glycogen content in pig skeletal muscle", Science, 288, pp.1248~1251 (2000)[DOI]
  8. Ma J, "A splice mutation in the PHKG1 gene causes high glycogen content and low meat quality in pig skeletal muscle", PLOS Genet, 10, pp.e1004710~ (2014)[DOI]
  9. Cho IC, "A functional regulatory variant of MYH3 influences muscle fiber-type composition and intramuscular fat content in pigs", PLOS Genet, 15, pp.e1008279~ (2019)[DOI]
  10. Fan JB, "Highly parallel genomic assays", Nat Rev Genet, 7, pp.632~644 (2006)[DOI]
  11. Hayes B, "Genome-wide association and genomic selection in animal breeding", Genome, 53, pp.876~883 (2010)[DOI]
  12. J.H. Choe, "Estimation of Pork Quality Traits Using Exsanguination Blood and Postmortem Muscle Metabolites", Animal Bioscience, 28(6), pp.862~869 (2015), 아세아·태평양축산학회[DOI]
  13. Chang CC, "Second-generation PLINK : rising to the challenge of larger and richer datasets", Gigascience, 4, pp.7~ (2015)[DOI]
  14. Zhou X, "Genome-wide efficient mixed-model analysis for association studies", Nat Genet, 44, pp.821~824 (2012)[DOI]
  15. Falconer DS, "Introduction to quantitative genetics" (1996), Longman
  16. Storey JD, "Statistical significance for genomewide studies", Proc Natl Acad Sci USA, 100, pp.9440~9445 (2003)[DOI]
  17. Wang M, "Statistical power in genome-wide association studies and quantitative trait locus mapping", Heredity, 123, pp.287~306 (2019)[DOI]
  18. "The R package ‘CMplot’" (2021)[URL]
  19. Drost HG, "Biomartr : genomic data retrieval with R", Bioinformatics, 33, pp.1216~1217 (2017)[DOI]
  20. Kuleshov MV, "Enrichr : a comprehensive gene set enrichment analysis web server 2016 update", Nucleic Acids Res, 44, pp.W90~W97 (2016)[DOI]
  21. Kanehisa M, "KEGG as a reference resource for gene and protein annotation", Nucleic Acids Res, 44, pp.D457~D462 (2016)[DOI]
  22. Harmegnies N, "Results of a wholegenome quantitative trait locus scan for growth, carcass composition and meat quality in a porcine four-way cross", Anim Genet, 37, pp.543~553 (2006)[DOI]
  23. Hu ZL, "Building a livestock genetic and genomic information knowledgebase through integrative developments of Animal QTLdb and CorrDB", Nucleic Acids Res, 47, pp.D701~D710 (2019)[DOI]
  24. Lu Y, "Genome-wide identification of genes essential for podocyte cytoskeletons based on single-cell RNA sequencing", Kidney Int, 92, pp.1119~1129 (2017)[DOI]
  25. Rinn JL, "Genome regulation by long noncoding RNAs", Annu Rev Biochem, 81, pp.145~166 (2012)[DOI]
  26. Mercer TR, "Structure and function of long noncoding RNAs in epigenetic regulation", Nat Struct Mol Biol, 20, pp.300~307 (2013)[DOI]
  27. Wang S, "Functions and regulatory mechanisms of lncRNAs in skeletal myogenesis, muscle disease and meat production", Cells, 8, pp.1107~ (2019)[DOI]
  28. San J, "Transcriptome analysis identifies signaling pathways related to meat quality in broiler chickens – the extracellular matrix(ECM)receptor interaction signaling pathway", Poult Sci, 100, pp.101135~ (2021)[DOI]
  29. Ardestani A, "Hippo signaling : key emerging pathway in cellular and whole-body metabolism", Trends Endocrinol Metab, 29, pp.492~509 (2018)[DOI]
  30. Velleman SG, "Meat Science and muscle biology symposium : extracellular matrix regulation of skeletal muscle formation", J Anim Sci, 90, pp.936~941 (2012)[DOI]
  31. Liu L, "Effect of divergent selection for intramuscular fat content on muscle lipid metabolism in chickens", Animals, 10, pp.4~ (2019)[DOI]
  32. Heath CM, "Lipid kinases play crucial and multiple roles in membrane trafficking and signaling", Histol Histopathol, 18, pp.989~998 (2003)[DOI]
  33. Sun Y, "Phosphatidylinositol 4, 5-bisphosphate : targeted production and signaling", BioEssays, 35, pp.513~522 (2013)[DOI]
  34. 김병기, "한방생균제가 한우의 체중, 혈액성상, 면역성 및 육량·육질에 미치는 영향", 한국식품영양학회지, 29(6), pp.860~869 (2016), 한국식품영양학회

관련 논문AI추천

Genome-wide Association Study to Identify Quantitative Trait Loci for Meat and Carcass Quality Traits in Berkshire강준모, 김유삼, 김종주, 남기창, 오동엽, 이윤미, 이학교, 정종현, Asif Iqbal, Rajani Rai아세아·태평양축산학회 · Animal Bioscience2015 · 제28권 제11호A Whole Genome Association Study on Meat Quality Traits Using High Density SNP Chips in a Cross between Korean Native Pig and Landrace김관석, 김종주, 이윤미, B.H. Choii, K.-T, Lee, M. Alam, M.R. Parkmrpark, T.H. Kim아세아·태평양축산학회 · Animal Bioscience2012 · 제25권 제11호A genome-wide association study (GWAS) for pH value in the meat of Berkshire pigs박준, Chong-Sam Na, Ja-Yeon Park, Sang-Min Lee한국축산학회 · 한국축산학회지2021 · 제63권 제1호Genome-wide Association Study of Integrated Meat Quality-related Traits of the Duroc Pig Breed강현석, 김성훈, 김희발, 서강석, 신동현, 이학교, 조서애, Taeheon Lee아세아·태평양축산학회 · Animal Bioscience2014 · 제27권 제3호Estimation of Genetic Associations between Production and Meat Quality Traits in Duroc Pigs남기창, 서강석, B.M. Lopez, H.S. Kang, H.S. Kim, J.G. Choi, M. Jang, M.M. Cabling아세아·태평양축산학회 · Animal Bioscience2015 · 제28권 제8호A whole genome sequence association study of muscle fiber traits in a White Duroc×Erhualian F2 resource populationBin Yang, Guorong Yan, Jun Gao, Lusheng Huang, Shijun Xiao, Tianfu Guo, Zhiyan Zhang아세아·태평양축산학회 · Animal Bioscience2020 · 제33권 제5호

이 간행물의 다른 논문 (15건)