一、研究方向

　　1、重要经济性状深度遗传解析与功能标记筛选

　　基于芯片及填充测序数据的GWAS研究新候选位点的挖掘；开展Bin model和机器学习算法、多性状、拷贝数变异为基础的关联分析，提高检测关联分析效率与准确性，丰富新的候选变异；开展主导群体不同组织、不同发育时期多组学研究，建立多组学的数据库，开发及优化基于多组学关联分析平台及统计方法，构建经济性状功能变异多维信息整合及利用的研究体系，有效利用基因组多维信息提高基因组预测准确性。

　　2、肉牛基因组选择技术体系完善与芯片优化设计

　　针对主导肉牛群体开展多群体及多性状基因组选择方法与策略优化；开发并优化基于Bayes的基因组选择算法以及一步法在多群体、多性状的应用，提高基因组育种值估计的准确性。以主导品种为基础，逐步形成以主要群体带动重要及特色肉牛品种的辐射型资源利用及芯片研发的技术体系，建立完善肉牛重要经济性状的芯片优化设计方法，育种及资源鉴定专门化芯片设计方案。

　　3、肉牛遗传评估方面与国家肉牛遗传评估中心建设

　　完善数据收集、传输、处理、分析、存储及综合应用的一体化信息管理系统的软硬件建设以及肉牛全基因组选择技术平台，使肉牛主导品种主要经济性状育种值评估准确度不低于55%；修订中国肉牛选择指数CBI和中国肉牛基因组选择指数GCBI；开发具有自主知识产权的遗传参数估计、育种值估计软件系统和适合我国主要肉牛品种的低密度商业化芯片；针对不同的生产和育种目标，提供个性化育种及选配方案制定服务。

　　二、代表性成果

　　1、Hu X, Xing YS, Ren L, Wang YH, Li Q, Fu X, Yang YQ, Xu LY, Willems L, Li JY, Zhang LP. Bta-miR-24-3p Controls the Myogenic Differentiation and Proliferation of Fetal, Bovine, Skeletal Muscle-Derived Progenitor Cells by Targeting ACVR1B. Animals：2076-2615.2019.

　　2、An BX, Gao X, Chang T,P Xia JW, Wang XQ, Miao J, Xu L, Zhang LP, Chen Y, Li JY, Xu SZ, Gao HJ. Genome-wide association studies using binned genotypes. Heredity: 0018-067X.2019.

　　3、Xu L, Wang ZZ, Zhu B, Liu Y, Li HW, Bordbar F, Chen Y, Zhang LP, Gao X, Gao HJ, Zhang SL, Xu LY, Li JY. Theoretical Evaluation of Multi-Breed Genomic Prediction in Chinese Indigenous Cattle. Animals:2076-2615.2019.

　　4、Bordbar F, Jensen J, Zhu B, Wang ZZ, Xu L, Chang TP, Xu L, Du M, Zhang LP, Gao HJ, Xu LY, Li JY. Identification of muscle-specific candidate genes in Simmental beef cattle using imputed next generation sequencing. PLoS One:1932-6203.2019.

　　5、Xu LY, Yang L, Zhu B, Zhang WG, Wang ZZ, Chen Y, Zhang LP, Gao X, Gao HJ, Liu GE, Li JY. Genome-wide scan reveals genetic divergence and diverse adaptive selection in Chinese local cattle. BMC Genomics. :1471-2164.2019.

　　6、Zhang R, Miao J, Song YX, Zhang WG, Xu LY, Chen Y, Zhang LP, Gao HJ, Zhu B, Li JY, Gao X. Genome-wide association study identifies the PLAG1-OXR1 region on BTA14 for carcass meat yield in cattle. Physiol Genomics:1094-8341.2019.

　　7、Wang ZZ, Zhu B, Niu H, Zhang WG, Xu L, Xu L, Chen Y, Zhang LP, Gao X, Gao HJ, Zhang SL, Xu LY, Li JY. Genome wide association study identifies SNPs associated with fatty acid composition in Chinese Wagyu cattle. J Anim Sci Biotechnol:2049-1891.2019.

　　8、Wang XQ, Miao J, Chang TP, Xia JW, An BX, Li Y, Xu LY, Zhang LP, Gao X, Li JY, Gao HJ. Evaluation of GBLUP, BayesB and elastic net for genomic prediction in Chinese Simmental beef cattle. PLoS One:1932-6203.2019.

　　9、Xu LY, Yang L, Wang L, Zhu B, Chen Y, Gao HJ, Gao X, Zhang LP, Liu GE, Li JY. Probe-based association analysis identifies several deletions associated with average daily gain in beef cattle. BMC Genomics:1471-2164.2019.

　　10、Zhang WG, Gao X, Zhang Y, Zhao YM, Zhang JB, Jia YT, Zhu B, Xu LY, Zhang LP, Gao HJ, Li JY, Chen Y. Genome-wide assessment of genetic diversity and population structure insights into admixture and introgression in Chinese indigenous cattle. BMC Genet.:1471-2165.2018.

　　11、Zhang T, Guo LP, Shi MY, Xu LY, Chen Y, Zhang LP, Gao HJ, Li JY, Gao X. Selection and effectiveness of informative SNPs for paternity in Chinese Simmental cattle based on a high-density SNP array. Gene:0378-1119.2018.

　　12、Guo P, Zhu B, Niu H, Wang ZZ, Liang YH, Chen Y, Zhang PL, Ni H, Guo Y, Hay EHA, Gao X, Gao HH, Wu XL, Xu LY, Li J. Fast genomic prediction of breeding values using parallel Markov chain Monte Carlo with convergence diagnosis. BMC Bioinformatics:1871-1413.2019.

　　13、Zhu B, Niu H, Zhang WG, Wang ZZ, Liang YH, Guan L, Guo P, Chen Y, Zhang LP, Guo Y, Ni HM, Gao X, Gao HJ, Xu LY, Li JY. Genome wide association study and genomic prediction for fatty acid composition in Chinese Simmental beef cattle using high density SNP array. BMC Genomics:1471-2164.2017.

　　14、Guan L, Hu X, Liu L, Xing YS, Zhou KZ, Liang XW, Yang QY, Jin SY, Bao JS, Gao HJ, Du M, Li JY, Zhang LP. bta-miR-23a involves in adipogenesis of progenitor cells derived from fetal bovine skeletal muscle. Scientific Reports:2045-2322.2017.

　　15、Zhang WG, Li JY, Guo Y, Zhang L, Xu LY, Gao X, Zhu B, Gao HJ, Ni HM, Chen Y. Multi-strategy genome-wide association studies identify the DCAF16-NCAPG region as a susceptibility locus for average daily gain in cattle. Journal of Animal Breeding and Genetics :0931-2668.2016.

　　16、Zhu B, Zhu M, Jiang J, Niu H, Wang YH, Wu Y, Xu LY, Chen Y, Zhang LP, Gao X, Gao HJ, Liu JF, Li JY. The Impact of Variable Degrees of Freedom and Scale Parameters in Bayesian Methods for Genomic Prediction in Chinese Simmental Beef Cattle. PLoS One:1932-6203.2016.

　　三、创新团队成员

团队首席：李俊雅

骨干：高会江、高雪、张路培、陈燕

助理：朱波、王泽昭