Detailed phenotyping identifies genes with pleiotropic effects on body composition

Area of Science:

• Animal Genetics
• Genomics
• Quantitative Trait Loci (QTL) Analysis

Background:

• Genetic variation in fat and muscle composition impacts human health and livestock value.
• Understanding these variations is key for improving meat quality and animal breeding.

Purpose of the Study:

• To identify genes associated with body composition traits in sheep using a multi-trait approach.
• To leverage detailed phenotyping and genetic data for gene discovery.

Main Methods:

• Conducted a multi-trait genome-wide association analysis (GWAS) on 10,613 sheep.
• Analyzed 56 carcass composition traits using 510,174 single nucleotide polymorphisms (SNPs).
• Clustered significant SNPs based on pleiotropic effects across multiple traits.

Main Results:

• Identified 71 significant SNPs, clustered into five groups based on pleiotropy.
• One group of 11 SNPs influenced muscle fatty acid profiles, near genes involved in lipid synthesis.
• Another group of 23 SNPs affected mature size, with associated genes involved in intracellular signaling pathways.

Conclusions:

• Multi-trait analysis significantly increased the power to detect SNP associations with body composition traits compared to single-trait methods.
• Detailed phenotypic data and cross-species comparisons aided in identifying convincing candidate genes.
• This study provides insights into the genetic architecture of body composition in livestock.