利用紧缩线性模型和贝叶斯模型对猪总产仔数和产活仔数性状的全基因组关联研究

doi:10.3724/SP.J.1005.2012.01261

遗传 ›› 2012, Vol. 34 ›› Issue (10): 1261-1270.doi: 10.3724/SP.J.1005.2012.01261

利用紧缩线性模型和贝叶斯模型对猪总产仔数和产活仔数性状的全基因组关联研究

刘小磊¹, 杨松柏¹, Max F Rothschild², ZHANG Zhi-Wu³, 樊斌¹

1. 华中农业大学, 农业动物遗传育种与繁殖教育部重点实验室, 武汉430070 2. Department of Animal Science, Iowa State University, Ames IA 50011 3. Institute for Genomic Diversity, Cornell University, Ithaca NY 14853

收稿日期:2012-06-18 修回日期:2012-07-27 出版日期:2012-10-20 发布日期:2012-10-25
通讯作者: 樊斌 E-mail:fanbin@mail.hzau.edu.cn
基金资助:
国家自然科学基金项目(编号：31072009), 教育部新世纪人才支持计划项目(编号：NCET-11-0646)和中央高校基本科研业务费专项资金(编号：2010PY008)资助

Genome-wide association study of total number born and number born alive in pigsusing both compressed mixed linear model and Bayes model

LIU Xiao-Lei¹, YANG Song-Bai¹, Max F Roths-child², ZHANG Zhi-Wu³, FAN Bin¹

1. Key Laboratory of AgriculturalAnimal Genetics, Breeding and Reproduction, Ministry of Education, Wuhan 430070, China 2. Department of Animal Science, Iowa State University, Ames IA 50011, USA 3. Institute for Genomic Diversity, Cornell University, Ithaca NY 14853, USA

Received:2012-06-18 Revised:2012-07-27 Online:2012-10-20 Published:2012-10-25
Contact: Bin Fan E-mail:fanbin@mail.hzau.edu.cn

摘要/Abstract

摘要： 全基因组关联分析策略已逐渐成为家畜重要经济性状研究的强有力工具。文章使用猪60K SNP芯片对一个具多胎繁殖性状记录的商业母猪群(n=820)进行分型检测, 共计57 814个SNP通过设定质控标准。主成分分析显示群体内不存在显著的群体分层现象, 而后分别运用两种统计模型Compressed Mixed Linear Model (GAPIT 程序包)、Bayes CPi(GenSel软件)进行第1和第2胎次总产仔数和产活仔数性状的全基因组关联分析。从两种分析方法所得结果中各取最显著的50个SNP位点进行比较：对于第1胎次总产仔数, 两种方法分析结果存在31个重合SNP位点, 对于第1胎次产活仔数, 有20个重合SNP位点; 且两种统计分析结果中最显著的SNP位点都在另一方法中得到验证。与第1胎次总产仔数显著关联的SNP位于1、2、3、7、13、16和18号染色体, 与第1胎次产活仔数显著关联的SNP位于1、3、4、13和16号染色体上的11个区域内。在1、3、13和16染色体上共有5个区域同时与这两个性状显著关联。与第2胎次总产仔数和产活仔数显著关联的区域主要位于7、10、12、13、14和16号染色体的6个重叠区域内。

关键词: 全基因组关联, 总产仔数, 产活仔数, SNP芯片, 猪

Abstract: GWAS(Genome-wide association study) strategy has been extensively used for identification of economical trait loci in livestock animals. Using Illumina’s PorcineSNP60 BeadChip, a GWA study of 820 commercial pigs with reproductive traits recorded was performed. The PCA analysis showed that there was no significant population stratification. Two different statistical models Compressed Mixed Linear Model(GAPIT program package)and Bayes CPi (GenSel software) were used to implement GWAS on total number born and number born alive of the first and second parity. To compare the most significant 50 SNPs from each method, a total of 31 and 20 coincided SNPs for total number born in the first parity were identified, and there were 20 coincided SNPs for number born alive in the first parityinthe results of bothmethods. The most significant SNPs were also significant in the results of the other method. The most significantly associated regions for total number born in the first parity were located on SSC1, 2, 3, 7, 13, 16, and 18. The most significantly associated regions for number born alive in the first parity were locatedon SSC1, 3, 4, 13, and 16. There were 5 common regions significantly associated with bothtraits on SSC1, 3, 13, and 16. The most significantly associated regions forbothtotal number born and number born alive for the second parity were mainly located on six common regions on SSC7, 10, 12, 13, 14, and 16.

Key words: GWAS, total number born, number born alive, SNP chip, pig

刘小磊，杨松柏，Max F Rothschild，ZHANG Zhi-Wu，樊斌. 利用紧缩线性模型和贝叶斯模型对猪总产仔数和产活仔数性状的全基因组关联研究[J]. 遗传, 2012, 34(10): 1261-1270.

LIU Xiao-Lei, YANG Song-Bai, Max F Roths-child, ZHANG Zhi-Wu, FAN Bin. Genome-wide association study of total number born and number born alive in pigsusing both compressed mixed linear model and Bayes model[J]. HEREDITAS, 2012, 34(10): 1261-1270.

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利用紧缩线性模型和贝叶斯模型对猪总产仔数和产活仔数性状的全基因组关联研究

Genome-wide association study of total number born and number born alive in pigsusing both compressed mixed linear model and Bayes model

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