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Leveraging Functional Genomics for Understanding Beef Quality Complexities and Breeding Beef Cattle for Improved Meat Quality

文献类型： 外文期刊

作者： Tian, Rugang 1 ; Mahmoodi, Maryam 2 ; Tian, Jing 1 ; Koshkoiyeh, Sina Esmailizadeh 2 ; Zhao, Meng 1 ; Saminzadeh, Mahla 2 ; Li, Hui 1 ; Wang, Xiao 1 ; Li, Yuan 1 ; Esmailizadeh, Ali 2 ;

作者机构： 1.Inner Mongolia Acad Agr & Anim Husb Sci, Hohhot 010031, Peoples R China

2.Shahid Bahonar Univ Kerman, Dept Anim Sci, Fac Agr, POB 76169133, Kerman, Iran

关键词： beef cattle; functional genomics; genomic selection; GWAS; meat quality; molecular breeding; omics technologies

期刊名称：GENES （ 影响因子：2.8； 五年影响因子：3.2 ）

ISSN：

年卷期： 2024 年 15 卷 8 期

页码：

收录情况： SCI

摘要： 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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