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

Area of Science:

• Animal Genomics
• Food Science
• Molecular Biology

Background:

• Consumer perception of beef quality is crucial for the cattle industry.
• Genomic approaches offer potential for improving key beef quality traits.

Purpose of the Study:

• To provide a comprehensive overview of omics technologies in beef quality research.
• To highlight findings from genome-wide association studies (GWAS), genomic selection (GS), transcriptomics, proteomics, and metabolomics.

Main Methods:

• Utilizing genomic selection (GS) and genome-wide association studies (GWAS) to identify genetic markers.
• Applying transcriptomics, proteomics, and metabolomics to understand underlying genetic mechanisms.
• Integrating omics data to uncover functional variants influencing beef quality.

Main Results:

• Omics technologies provide insights into genetic mechanisms affecting beef quality traits.
• GWAS and GS identify genetic markers and causal variants for improved beef quality.
• Functional genomics approaches complement GWAS data for a deeper understanding.

Conclusions:

• Leveraging omics technologies can optimize beef cattle breeding for enhanced quality.
• Understanding the interplay of genetics, gene expression, and metabolism is key to meeting high-quality beef demand.
• This review serves as a resource for advancing beef quality research through functional genomics.