Application of GWAS and mGWAS in Livestock and Poultry Breeding
Author:
Ren Jing12, Gao Zhendong2, Lu Ying2, Li Mengfei2, Hong Jieyun2, Wu Jiao2, Wu Dongwang2, Deng Weidong2ORCID, Xi Dongmei2, Chong Yuqing2
Affiliation:
1. Key Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, Guizhou University, Guiyang 550025, China 2. Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
Abstract
In recent years, genome-wide association studies (GWAS) and metabolome genome-wide association studies (mGWAS) have emerged as crucial methods for investigating complex traits in animals and plants. These have played pivotal roles in research on livestock and poultry breeding, facilitating a deeper understanding of genetic diversity, the relationship between genes, and genetic bases in livestock and poultry. This article provides a review of the applications of GWAS and mGWAS in animal genetic breeding, aiming to offer reference and inspiration for relevant researchers, promote innovation in animal genetic improvement and breeding methods, and contribute to the sustainable development of animal husbandry.
Funder
Foundation of the Key Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, Guizhou University Open Fund of the Key Laboratory of Animal Nutrition and Feed Science of Yunnan Provincial Major Science and Technology Projects in Yunnan Province “Xingdian Talent” Industry Innovation Talent Program in Yunnan Province
Reference72 articles.
1. Freebern, E., Santos, D.J.A., Fang, L., Jiang, J., Parker Gaddis, K.L., Liu, G.E., VanRaden, P.M., Maltecca, C., Cole, J.B., and Ma, L. (2020). GWAS and Fine-Mapping of Livability and Six Disease Traits in Holstein Cattle. BMC Genom., 21. 2. Puig-Oliveras, A., Revilla, M., Castelló, A., Fernández, A.I., Folch, J.M., and Ballester, M. (2016). Expression-Based GWAS Identifies Variants, Gene Interactions and Key Regulators Affecting Intramuscular Fatty Acid Content and Composition in Porcine Meat. Sci. Rep., 6. 3. Baron, C., Cherkaoui, S., Therrien-Laperriere, S., Ilboudo, Y., Poujol, R., Mehanna, P., Garrett, M.E., Telen, M.J., Ashley-Koch, A.E., and Bartolucci, P. (2023). Gene-Metabolite Annotation with Shortest Reactional Distance Enhances Metabolite Genome-Wide Association Studies Results. bioRxiv. 4. Zhang, Y., Lyu, Y., Chen, L., Cao, K., Chen, J., He, C., Lyu, X., Jiang, Y., Xiang, J., and Liu, B. (2023). Exploring the Prognosis-Related Genetic Variation in Gastric Cancer Based on mGWAS. Int. J. Mol. Sci., 24. 5. The Pathway of Melatonin Biosynthesis in Common Wheat (Triticum aestivum);Chen;J. Pineal Res.,2023
|
|