Genomic Selection for Economically Important Traits in Dual-Purpose Simmental Cattle

Area of Science:

• Animal Genetics
• Quantitative Genetics
• Animal Breeding

Background:

• Genomic selection (GS) is a key tool in modern animal breeding for genetic evaluation.
• Dual-purpose cattle breeding programs increasingly utilize GS for routine genetic assessments.
• Simmental cattle in Northwest China represent a significant population for breeding research.

Purpose of the Study:

• To evaluate the effectiveness of genomic selection using A-array PBLUP and H-array ssGBLUP methods.
• To assess genetic parameters and the reliability of genomic estimated breeding values (GEBVs) for milk production, reproduction, and growth traits.
• To determine the impact of H-matrix construction on genetic evaluation in dual-purpose Simmental cattle.

Main Methods:

• Employed restricted maximum likelihood (REML) methods for genetic evaluation.
• Utilized single-trait models with A-array PBLUP and H-array ssGBLUP.
• Analyzed milk production, reproduction, and growth data from Simmental cows (1987-2022).

Main Results:

• Heritability estimates ranged from 0.09-0.31 for milk, 0.03-0.43 for reproduction, and 0.13-0.43 for growth traits.
• GEBV reliability increased by 0.6-3.2% (milk), 0.2-2.4% (reproduction), and 0.5-1.5% (growth) in the entire population.
• H-matrix ssGBLUP improved GEBV reliability for milk (1.6-4.0%) and reproduction (0.4-3.6%), but decreased it for growth traits (-12.0-17.0%) in genotyped populations.

Conclusions:

• H-matrix ssGBLUP enhances heritability and GEBV reliability for milk production and reproduction traits in Simmental cattle.
• The benefits of H-matrix ssGBLUP were less evident for growth traits, particularly in smaller populations.
• Findings support the application of genomic genetic evaluation for Simmental cattle breeding, aiding selection and marketing of superior breeding stock.