Evidence map›Paper›PMID 40646859›Full record

ArticleAnimals : an open access journal from MDPI2025

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

Xiaoxue Zhang, Dan Wang, Menghua Zhang, Lei Xu, Xixia Huang, Yachun Wang

Abstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Xiaoxue ZhangCollege of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
Dan WangCollege of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
Menghua ZhangCollege of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
Lei XuCollege of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
Xixia HuangCollege of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
Yachun WangKey Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China.ORCID 0000-0003-3629-2802

Funding

The earmarked fund for the Xinjiang Agriculture Research System XJARS-10The National Modern Agriculture Industrial System Project Grant No. CARS-36
6 · The paper itself

Abstract

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.

Indexed as

Chinese Simmental cattlegrowth traitsmilk-production traitsreproduction traitssingle-step GBLUP

Identifiers

PMID40646859
PMCPMC12249443

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