Genome-wide association study on dairy goat milk production traits using three models

Area of Science:

• Animal Genetics
• Dairy Science
• Genomics

Background:

• Identifying genetic markers for economically important traits in dairy goats is crucial for enhancing breeding efficiency and industry value.
• The genetic architecture of key milk production traits in dairy goats remains largely unexplored.

Purpose of the Study:

• To identify significant single nucleotide polymorphisms (SNPs) and candidate genes associated with dairy goat milk production traits.
• To analyze milk yield, fat, protein, lactose, ash percentages, total dry matter, and somatic cell count.

Main Methods:

• Employed three genome-wide association study (GWAS) models: Generalized Linear Model (GLM), Mixed Linear Model (MLM), and FarmCPU.
• Analyzed common dairy goat milk production traits to detect significant SNPs and positional/functional candidate genes.

Main Results:

• Identified 242 significant SNPs (45 genome-wide, 197 suggestive) and 99 positional candidate genes.
• 15 SNP loci and 18 candidate genes were consistently detected across all three GWAS models.
• Detected trait-specific SNPs and candidate genes, proposing novel genes like LCORL, TNFRSF1A, VWF, SPATA6, MAN1C1, MASP1, and BRCA2.

Conclusions:

• The study provides a valuable reference for understanding the genetic basis of dairy goat milk production traits.
• Results facilitate the development of molecular breeding markers for enhancing dairy goat productivity.