Integrating multi-layered biological priors to improve genomic prediction accuracy in beef cattle
Our findings suggest that integrating biological prior information from multiple layers can enhance our understanding of the genetic architecture underlying complex traits and further improve genomic prediction in beef cattle.
Authors
- Junya Li (ORCID: https://orcid.org/0000-0001-8051-050X)
- Qunhao Niu (ORCID: https://orcid.org/0000-0003-1386-9074)
- Jiayuan Wu
- Huijiang Gao (ORCID: https://orcid.org/0000-0002-5502-2528)
- Lupei Zhang (ORCID: https://orcid.org/0000-0001-7701-2331)
- Tianyi Wu (ORCID: https://orcid.org/0009-0001-9154-418X)
- Lingyang Xu (ORCID: https://orcid.org/0000-0002-8463-6668)
- Zezhao Wang (ORCID: https://orcid.org/0000-0003-1224-681X)
- Xueyuan Xie
- Xue Gao (ORCID: https://orcid.org/0009-0006-4127-3808)
- Bo Zhu (ORCID: https://orcid.org/0000-0001-7348-1843)
- Zhida Zhao
Institutions
- Animal Husbandry & Veterinary (IN)
- Inner Mongolia Academy of Agricultural & Animal Husbandry Sciences (CN)
- Chinese Academy of Agricultural Sciences (CN)
- Institute of Animal Sciences (CN)
- Ministry of Agriculture and Rural Affairs (CN)
Publication Details
- Journal
- Biology Direct
- Published
- 2024-12-31
- DOI
- https://doi.org/10.1186/s13062-024-00574-y
- Citations
- 1
- Primary Topic
- Genetic and phenotypic traits in livestock
- Type
- article
- Field-Weighted Citation Impact
- 0.55
Funders
- National Natural Science Foundation of China
- Chinese Academy of Agricultural Sciences
- National Key Research and Development Program of China
- Agricultural Science and Technology Innovation Program
- National Beef Cattle Industrial Technology System