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Annotation and assessment of functional variants in livestock through epigenomic data

Ruixian Ma Renzhuo Kuang Jingcheng Zhang Jiahao Sun Yueyuan Xu Xinbo Zhou Zheyu Han Mingyang Hu Daoyuan Wang Yuhua Fu Yong Zhang Xinyun Li Mengjin Zhu Shuhong Zhao Tao Xiang Mengwei Shi Yunxia Zhao

Ruixian Ma, Renzhuo Kuang, Jingcheng Zhang, Jiahao Sun, Yueyuan Xu, Xinbo Zhou, Zheyu Han, Mingyang Hu, Daoyuan Wang, Yuhua Fu, Yong Zhang, Xinyun Li, Mengjin Zhu, Shuhong Zhao, Tao Xiang, Mengwei Shi, Yunxia Zhao. Annotation and assessment of functional variants in livestock through epigenomic data[J]. 遗传学报. doi: 10.1016/j.jgg.2025.03.013
引用本文: Ruixian Ma, Renzhuo Kuang, Jingcheng Zhang, Jiahao Sun, Yueyuan Xu, Xinbo Zhou, Zheyu Han, Mingyang Hu, Daoyuan Wang, Yuhua Fu, Yong Zhang, Xinyun Li, Mengjin Zhu, Shuhong Zhao, Tao Xiang, Mengwei Shi, Yunxia Zhao. Annotation and assessment of functional variants in livestock through epigenomic data[J]. 遗传学报. doi: 10.1016/j.jgg.2025.03.013
Ruixian Ma, Renzhuo Kuang, Jingcheng Zhang, Jiahao Sun, Yueyuan Xu, Xinbo Zhou, Zheyu Han, Mingyang Hu, Daoyuan Wang, Yuhua Fu, Yong Zhang, Xinyun Li, Mengjin Zhu, Shuhong Zhao, Tao Xiang, Mengwei Shi, Yunxia Zhao. Annotation and assessment of functional variants in livestock through epigenomic data[J]. Journal of Genetics and Genomics. doi: 10.1016/j.jgg.2025.03.013
Citation: Ruixian Ma, Renzhuo Kuang, Jingcheng Zhang, Jiahao Sun, Yueyuan Xu, Xinbo Zhou, Zheyu Han, Mingyang Hu, Daoyuan Wang, Yuhua Fu, Yong Zhang, Xinyun Li, Mengjin Zhu, Shuhong Zhao, Tao Xiang, Mengwei Shi, Yunxia Zhao. Annotation and assessment of functional variants in livestock through epigenomic data[J]. Journal of Genetics and Genomics. doi: 10.1016/j.jgg.2025.03.013

Annotation and assessment of functional variants in livestock through epigenomic data

doi: 10.1016/j.jgg.2025.03.013
基金项目: 

We thank Dr. Christopher K Tuggle (cktuggle@iastate.edu) at Department of Animal Science, Iowa State University for valuable suggestions to our work. This work was supported by the National Natural Science Foundation of China (32341051), the grant from Department of Agriculture and Rural Affairs of Hubei Province (HBZY2023B006-02), the National Funding (2023ZD04050), the National Natural Science Foundation of China Outstanding Youth (32125035) , and the National Key R&D Young Scientists Project (2022YFD1302000).

详细信息
    通讯作者:

    Tao Xiang,E-mail:Tao.Xiang@mail.hzau.edu.cn

    Mengwei Shi,E-mail:shimengwei@yzwlab.cn

    Yunxia Zhao,E-mail:yxzhao@mail.hzau.edu.cn

Annotation and assessment of functional variants in livestock through epigenomic data

Funds: 

We thank Dr. Christopher K Tuggle (cktuggle@iastate.edu) at Department of Animal Science, Iowa State University for valuable suggestions to our work. This work was supported by the National Natural Science Foundation of China (32341051), the grant from Department of Agriculture and Rural Affairs of Hubei Province (HBZY2023B006-02), the National Funding (2023ZD04050), the National Natural Science Foundation of China Outstanding Youth (32125035) , and the National Key R&D Young Scientists Project (2022YFD1302000).

  • 摘要:

    Understanding genetic variant functionality is essential for advancing animal genomics and precision breeding. However, the lack of comprehensive functional genomic annotations in animals limits the effectiveness of most variant function assessment methods. In this study, we gather 1030 raw epigenomic datasets from 10 animal species and systematically annotate 7 types of key regulatory regions, creating a comprehensive functional annotation map of animal genomic variants. Our findings demonstrate that integrating variants with regulatory annotations can identify tissues and cell types underlying economic traits, underscoring the utility of these annotations in functional variant discovery. Using our functional annotations, we rank the functional potential of genetic variants and classify over 127 million candidate variants into 5 functional confidence categories, with high-confidence variants significantly enriched in eQTLs and trait-associated SNPs. Incorporating these variants into genomic prediction models can improve estimated breeding value (EBV) accuracy, demonstrating their practical utility in breeding programs. To facilitate the use of our results, we develop the Integrated Functional Mutation (IFmut: http://www.ifmutants.com:8212) platform, enabling researchers to explore regulatory annotations and assess the functional potential of animal variants efficiently. Our study provides a robust framework for functional genomic annotations in farm animals, enhancing variant function assessment and breeding precision.

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出版历程
  • 收稿日期:  2024-12-10
  • 录用日期:  2025-03-24
  • 修回日期:  2025-03-22
  • 网络出版日期:  2025-07-11

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