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数量遗传学

发布时间：2023-06-06

  1. Huang, Q., Zhou, L., Xue, Y., Du, H., Zhuo, Y., Mao, R., ... & Liu, J. (2024). GOplan: an R package for animal breeding program design via integrating Gene Flow and Bayesian Optimization methods. G3: Genes, Genomes, Genetics, jkae284. https://doi.org/10.1093/g3journal/jkae284. （通讯）

  2. Li, W., Zhang, M., Du, H., Wu, J., Zhou, L., & Liu, J. (2024). Multi-Trait Bayesian Models Enhance the Accuracy of Genomic Prediction in Multi-Breed Reference Populations. Agriculture, 14(4), 626. （通讯）

  3. Jiang S, Zhang G, Shen Z, Zhong P, Tan J, Liu J. Pig Weight Estimation Method Based on a Framework Combining Mask R-CNN and Ensemble Regression Model. Animals (2024);14:2122. https://doi.org/10.3390/ani14142122.（共同通讯）

  4. Yue Zhuo, Heng Du, ChenGuang Diao, WeiNing Li, Lei Zhou, Li Jiang, JiCai Jiang, JianFeng Liu, MAGE: Metafounders assisted genomic estimation of breeding value, a novel Additive-Dominance Single-Step model in crossbreeding systems, Bioinformatics, 2024;, btae044, https://doi.org/10.1093/bioinformatics/btae044

  5. Heng Du, Chenguang Diao, Yue Zhuo, Xianrui Zheng, Zhengzheng Hu, Shiyu Lu, Wenjiao Jin, Lei Zhou, Jian-Feng Liu. Assembly of novel sequences for Chinese domestic pigs reveals new genes and regulatory variants providing new insights into their diversity. Genomics, 110782,.https://doi.org/10.1016/j.ygeno.2024.110782

  6. Siqian Chen, Shuli Liu, Shaolei Shi, Hongwei Yin, Yongjie Tang, Jinning Zhang, Wenlong Li, Gang Liu, Kaixing Qu, Xiangdong Ding, Yachun Wang, Jianfeng Liu, Shengli Zhang, Lingzhao Fang, Ying Yu, Cross-species comparative DNA methylation reveals novel insights into complex traits genetics among cattle, sheep and goats, Molecular Biology and Evolution, 2024;, msae003, https://doi.org/10.1093/molbev/msae003

  7. Junjian Wang, Huawei Yang, Shaokang Chen, Weining Li, Jian Yu, Zhengzheng Hu, Yue Zhuo, Qianqian Huang, Zhen Liu, Lei Zhou, Jianliang Wu, Zhaojun Wang, Feng Guo, Peng Yun, Xiaofeng Wang, Jian-Feng Liu, (2023). Genome‐wide association study reveals candidate genes for pollution excreta traits in pigs. Animal Genetics,https://doi.org/10.1111/age.13323

  8. Benmeng Liang, Tianyou Bai, Yuhetian Zhao, Jiangang Han, Xiaohong He, Yabin Pu, Chunxin Wang, Wujun Liu, Qing Ma, Kechuan Tian, Wenxin Zheng, Nan Liu, Jianfeng Liu, Yuehui Ma, Lin Jiang,Two mutations at KRT74 and EDAR synergistically drive the fine-wool production in Chinese sheep,Journal of Advanced Research,2023,ISSN 2090-1232,https://doi.org/10.1016/j.jare.2023.04.0122

  9. Wang, Y., Diao, C., Kang, H., Hao, W., Mrode, R., Chen, J.,Liu, JF., Zhou, L. (2022). A random regression model based on a single-step method for improving the genomic prediction accuracy of residual feed intake in pigs. Frontiers in Genetics, 12, 769849 https://doi.org/10.3389/fgene.2021.769849

  10. Wenjing Yang,Jian Yu,Yuelin Yao,Siqian Chen,Bingru Zhao,Shuli Liu,Lei Zhou,Lingzhao Fang,Jianfeng Liu. Comparative immune-relevant transcriptome reveals the evolutionary basis of complex traits[J]. Iscience, 2022, 25(12).https://doi.org/10.1016/j.isci.2022.105572

  11. Li. W., Z. Wang, S. Luo, J. Wu and L. Zhou et al., 2022 Genome-Wide Association Analysis and Genetic Parameters for Feed Efficiency and Related Traits in Yorkshire and Duroc Pigs. Animals 12: 1902.https://doi.org/10.3390/ani12151902

  12. Xue Y, Liu S, Li W, Mao R, Zhuo Y, Xing W, Liu J, Wang C, Zhou L, Lei M, Liu JF. (2022). Genome-Wide Association Study Reveals Additive and Non-Additive Effects on Growth Traits in Duroc Pigs. Genes 13 (8):1454.（共同通讯）, IF=4.474https://doi.org/10.3390/genes13081454

  13. Zhang Y, Zhuo Y, Ning C, Zhou L, Liu JF. (2022). Estimate of inbreeding depression on growth and reproductive traits in a Large White pig population. G3 ():1. （共同通讯）, IF=3.545https://doi.org/10.1093/g3journal/jkac118

  14. Yang W, Liu Z, Zhao Q, Du H, Yu J, Wang H, Liu X, Liu H, Jing X, Yang H, Shi G, Zhou L, Liu JF. Population Genetic Structure and Selection Signature Analysis of Beijing Black Pig. Front Genet. 2022 Mar 24;13:860669. doi: 10.3389/fgene.2022.860669.https://doi.org/10.3389/fgene.2022.860669

  15. Hu Z, Li Y, Du H, Ren J, Zheng X, Wei K, Jian-Feng Liu. Transcriptome analysis reveals modulation of the STAT family in PEDV-infected IPEC-J2 cells. BMC Genomics. 2020;21(1):891. （通讯）https://doi.org/10.1186/s12864-020-07306-2

  16. Yang W, Wu J, Yu J, Zheng X, Kang H, Wang Z, Zhang S, Zhou L, Liu J. A genome-wide association study reveals additive and dominance effects on growth and fatness traits in large white pigs. Anim Genet. 2021 Oct;52(5):749-753. doi: 10.1111/age.13131. Epub 2021 Aug 17. PMID: 34403536. 3.058https://doi.org/10.1111/age.13131

  17. Ye Wang, Chenguang Diao, Huimin Kang, Wenjie Hao, Raphael Mrode, Junhai Chen, Jianfeng Liu1*, Lei Zhou1* A random regression model based on a single-step method for improving the genomic prediction accuracy of residual feed intake in pigs. Frontiers in Genetics https://doi.org/10.3389/fgene.2021.769849

  18. Zhou, L. , Wang, Y. , Yu, J. , Yang, H. , & Liu, J. . (2019). Improving genomic prediction for two yorkshire populations with a limited size using the single‐step method. Animal Genetics, 50(4). （通讯）https://doi.org/10.1111/age.12806

  19. Kang, H, Ning, C, Zhou, L, Zhang, S, Lin, Q, and Liu J.F. (2018). Short communication: Single-step genomic evaluation of milk production traits using multiple-trait random regression model in Chinese Holsteins. J. Dairy Sci. 101(12), 11143-11149. （通讯）https://doi.org/10.3168/jds.2018-15090

  20. Kang, H, Ning, C, Zhou, L, Zhang, S, Yang, N, and Liu J.F. (2018). PIBLUP: High-Performance Software for Large-Scale Genetic Evaluation of Animals and Plants. Front. Genet. 9, 226. （通讯）https://doi.org/10.3389/fgene.2018.00226

  21. Zhao P., Yu Y, Feng W, Du H, Yu J, Kang H., Zheng X., Wang Z., L George, W Catherine, Liu J.F.(2018). Evidence of evolutionary history and selective sweep in the genome of meishan pig reveals its genetic and phenotypic characterization.GigaScience 7, 1–12.（通讯）https://doi.org/10.1093/gigascience/giy058

  22. Zhou L, Raphael Mrode, Zhang S., Zhang Q., Li B., Liu J.F. (2017). Factors affecting GEBV accuracy with single-step Bayesian models. Heredity 120, 100-109. （通讯）https://doi.org/10.1093/gigascience/giy058

  23. Kang H., Lei Z. & Liu J.F. (2017). Statistical considerations for genomic selection. Front. Agr. Sci. Eng. 4, 268-278. （通讯）https://doi.org/10.15302/J-FASE-2017164

  24. 邢凯, 周磊, 刘丑生, 张桂香, 刘振, 卓越, 张美琳, 邱小田, 刘剑锋. 《国家生猪核心育种场年度遗传评估报告（2022年度）》解读[J]. 中国畜牧杂志, 2023, 59 (12): 370-375.（共同通讯）

  25. 杨华威,黄千千,方铎,冯文,卓越,周磊 刘剑锋.(2023).系谱错误对猪基因组选择准确性的影响.中国畜牧杂志(08),273-277.doi:10.19556/j.0258-7033.20220913-04.

  26. 黄千千,张宇,倪俊卿,王贵江,罗文学,骆菲,刘廷玉,李赛,周磊,杜恒,张军辉,刘剑锋.(2023).深县猪群体遗传多样性分析及SNP特征位点挖掘.中国畜牧杂志(06),95-100.doi:10.19556/j.0258-7033.20220620-01.

  27. 余健,杨文静,王晔,周磊,王楚端,刘剑锋.多个场联合遗传评估提高基因组选择准确性[J/OL].中国畜牧杂志:1-8[2021-09-29].https://doi.org/10.19556/j.0258-7033.20210616-10.

  28. 周磊,王晔,毛瑞涵,李佳芮,刘剑锋.国外生猪育种体系简析及对我国生猪育种的几点思考[J/OL].中国畜牧杂志:1-11[2020 1215]

  29. 王俊健，王晓凤，李伟宁，余健，胡蒸蒸，陈少康，李爽，郑美丽，郭峰，郑瑞峰，刘剑锋. 北京地区生长育肥猪采食、排泄及生长性状间的典型相关分析[J]，中国畜牧杂志，2019.

  30. 周磊,杨华威,赵祖凯,杨红杰,刘剑锋.基因组选择在我国种猪育种中应用的探讨[J].中国畜牧杂志,2018,54(03):4-8.

  31. 杨文静,王晔,闫青霞,麻柱,刘剑锋,张胜利.应用随机回归模型对北京地区荷斯坦牛产奶性状的遗传分析[J].中国畜牧杂志,2021,57(06):141-145.DOI:10.19556/j.0258-7033.20200706-07.