Identification of microsatellites and their effect on economic traits of Texel × Kazakh sheep

Mutton has the advantages of delicious taste, high nutrition, and easy digestion. It is important to improve the production and quality of mutton in mutton sheep breeding. Microsatellite locus marker-assisted breeding is widely used to breed excellent traits of various species. It is important to search for microsatellite markers related to the economic traits (mutton production and fat content) of mutton sheep.

This study aimed to explore the relationship between 11 microsatellite loci of Texel × Kazakh sheep and 12 economic traits and to seek potential loci related to the mutton production (PW: Pre-slaughter weight, CW: Carcass weight, TAW: Total breast and abdomen weight, TLT: Total weight of left anterior tendon, TLL: Total weight of left hip and leg, LD: Longissimus dorsi, OMA: Ocular muscle area) and fat deposition levels (TFW: Tail fat weight, MFW: Mesenteric fat weight, KFW: Kidney fat weight, BFT: Back fat thickness and GR: GR value) of mutton sheep.

Genetic analysis of the 108 Texel × Kazakh sheep hybrid population revealed 81 alleles across all loci, with a mean number of alleles (MNA) of 7.364. The population exhibited moderate observed heterozygosity (Ho = 0.610), high expected heterozygosity (He = 0.785), and substantial polymorphism (polymorphism information content, PIC = 0.759), indicating robust genetic diversity. Notably, the AMEL locus demonstrated significant associations with MFW (η² = 0.319) and KFW (η² = 0.347), while the INRA023 locus influenced CW (η² = 0.260) (adjusted p < 0.05). No other loci showed statistically significant trait correlations after multiple-testing correction. The HH genotype at AMEL and AD genotype at INRA023 emerged as pivotal molecular markers, collectively explaining 26.0-34.7% of phenotypic variance in meat yield traits.

These findings establish a theoretical framework for precision breeding strategies, offering actionable solutions to enhance meat productivity in ovine populations through marker-assisted selection (MAS).