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

## TL;DR

This study compares traditional and genomic selection methods in Simmental cattle to improve breeding accuracy for milk, reproduction, and growth traits.

## Contribution

The study demonstrates that genomic selection (ssGBLUP) improves breeding value accuracy for milk and reproduction traits in dual-purpose Simmental cattle.

## Key findings

- Heritability estimates for milk, reproduction, and growth traits ranged from low to moderate.
- Genomic selection (ssGBLUP) improved reliability of breeding values for milk and reproduction traits compared to traditional BLUP.
- Improvements in reliability were less consistent for growth traits, especially in smaller populations.

## Abstract

Dual-purpose Simmental cattle are receiving increasing attention, and their performance has improved with the advent of combining advanced breeding techniques with production practices. Therefore, new options are needed to increase the accuracy of genetic selection of dual-purpose Simmental cattle. The objective of this study was to estimate the genetic parameters of milk-production, reproduction, and growth traits and compare the accuracy analysis of the estimated breeding value between the traditional best linear unbiased prediction (BLUP) method and genomic selection, using the single-step genomic BLUP (ssGBLUP) method. Through this research, we found that the heritability of milk-production traits, reproduction traits, and growth traits was generally low to moderate; in the analysis of estimated breeding value accuracy, the ssGBLUP method was superior to the pedigree-based best linear unbiased prediction (PBLUP). These findings demonstrate the feasibility of applying the ssGBLUP method in breeding programs for dual-purpose Simmental cattle populations.

Genomic selection (GS) is a new landmark method in modern animal breeding programs, and it has become a tool for routine genetic evaluation regarding dual-purpose cattle breeding. In this study, we employed data on milk-production, reproduction, and growth measurements of dual-purpose Simmental cows during the period 1987–2022 from two large-scale farms in Northwest China. For this purpose, we used a single-trait model based on the A-array PBLUP and H-array ssGBLUP to perform genetic evaluation of milk-production, reproduction, and growth traits by applying the restricted maximum likelihood (REML) methods. The results revealed that the heritability based on the additive genetic correlation matrix was approximately 0.09–0.31 for milk-production traits, 0.03–0.43 for reproduction traits, and 0.13–0.43 for growth traits. In addition, the heritability based on the genome–pedigree association matrix was similarly 0.09–0.32 for milk-production traits, 0.04–0.44 for reproductive traits, and 0.14–0.43 for growth traits. In the entire population, the reliability of genomic estimated breeding values (GEBVs) increased by 0.6–3.2%, 0.2–2.4%, and 0.5–1.5% for milk-production, reproductive traits, and growth traits, respectively. In the genotyped population, the reliability of GEBV for milk-production and reproduction traits increased by 1.6–4.0% and 0.4–3.6%, respectively, whereas the reliability of GEBV for growth traits decreased by 12.0–17.0%. These results suggest that the construction of an H-matrix with ssGBLUP could improve the heritability and reliability of breeding values for milk-production and reproduction traits. However, the advantage was not evident for growth traits in smaller populations. The present results thus provide a basis for future application of genomic genetic evaluation of dual-purpose Simmental cattle, providing data support for the selection and marketing of excellent breeding bulls, thereby helping to establish a basis for their independently bred breeding bull.