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Leveraging Functional Genomics for Understanding Beef Quality Complexities and Breeding Beef Cattle for Improved Meat Quality.
Tian, Rugang; Mahmoodi, Maryam; Tian, Jing; Esmailizadeh Koshkoiyeh, Sina; Zhao, Meng; Saminzadeh, Mahla; Li, Hui; Wang, Xiao; Li, Yuan; Esmailizadeh, Ali.
Afiliação
  • Tian R; Inner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot 010031, China.
  • Mahmoodi M; Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman P.O. Box 76169-133, Iran.
  • Tian J; Inner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot 010031, China.
  • Esmailizadeh Koshkoiyeh S; Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman P.O. Box 76169-133, Iran.
  • Zhao M; Inner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot 010031, China.
  • Saminzadeh M; Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman P.O. Box 76169-133, Iran.
  • Li H; Inner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot 010031, China.
  • Wang X; Inner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot 010031, China.
  • Li Y; Inner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot 010031, China.
  • Esmailizadeh A; Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman P.O. Box 76169-133, Iran.
Genes (Basel) ; 15(8)2024 Aug 22.
Article em En | MEDLINE | ID: mdl-39202463
ABSTRACT
Consumer perception of beef is heavily influenced by overall meat quality, a critical factor in the cattle industry. Genomics has the potential to improve important beef quality traits and identify genetic markers and causal variants associated with these traits through genomic selection (GS) and genome-wide association studies (GWAS) approaches. Transcriptomics, proteomics, and metabolomics provide insights into underlying genetic mechanisms by identifying differentially expressed genes, proteins, and metabolic pathways linked to quality traits, complementing GWAS data. Leveraging these functional genomics techniques can optimize beef cattle breeding for enhanced quality traits to meet high-quality beef demand. This paper provides a comprehensive overview of the current state of applications of omics technologies in uncovering functional variants underlying beef quality complexities. By highlighting the latest findings from GWAS, GS, transcriptomics, proteomics, and metabolomics studies, this work seeks to serve as a valuable resource for fostering a deeper understanding of the complex relationships between genetics, gene expression, protein dynamics, and metabolic pathways in shaping beef quality.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Cruzamento / Genômica / Estudo de Associação Genômica Ampla / Carne Vermelha Limite: Animals Idioma: En Revista: Genes (Basel) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China País de publicação: Suíça

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Cruzamento / Genômica / Estudo de Associação Genômica Ampla / Carne Vermelha Limite: Animals Idioma: En Revista: Genes (Basel) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China País de publicação: Suíça