家畜育种中的基因组特征分析  

Analysis of Genomic Features in Animal Breeding

作　　者：梅步俊[1,2] 王志华[3] 

机构地区：[1]河套学院农学系,巴彦淖尔015000 [2]爱荷华州立大学动物科学系,爱荷华州埃姆斯50010 [3]河套学院土木工程系,巴彦淖015000

出　　处：《基因组学与应用生物学》2016年第4期788-796,共9页Genomics and Applied Biology

基　　金：国家自然科学基金(项目批准号:31460594);河套学院教学研究项目(项目批准号:HTXYJZ14005);国家留学基金委项目(项目批准号:201308155140)共同资助

摘　　要：基因组测序技术的发展为我们提供了研究家畜重要经济性状遗传基础的契机。家畜和人类医学中的全基因组关联分析表明单个数量性状基因座(QTL)的效应是非常微小的。这一结论促使利用高密度单核苷酸多态性(SNP)信息进行基因组选择方法的研究。结合新的统计学方法,并检测基因组数据的特征无疑是进行基因组研究和实验设计的基础。准确的掌握基因组数据的特征可以为QTL检测和研究数量性状的遗传基础提供坚实的研究基础。但是,海量的基因组数据量加大了研究基因组数据特征的难度。本文中,我们讨论了研究基因组时代动物育种研究中基因组数据基本特征及其必要的统计学基础。此外,我们还提供了分析基因组特征的简单示例和Julia语言代码。在此基础上,我们讨论了在全基因组测序数据和系统分析等情况下,基因组数据基本特征分析所面临的挑战。The utility of genomic technology has the potential to supply precious insight into the mechanisms of various important production traits in the animal production industry. Contributions of genome-wide association studies in animal and human has drawn the conclusion that the effect of single quantitative trait loci（QTL） on quantitative traits is just possible to be trivial. This has promoted the development of alternative tool, genomic selection, for using high-density single nucleotide polymorphism（SNP） information. Testing for genomic features of different sets, combined with novel statistical methods, is undoubtedly a fundamental task in genomics research and experimental design. And it also provides a sound basis to detect QTL and to uncover the genetic architecture of quantitative traits. However, researches for assessing these features are usually complicated by the enormous datasets. Here, we discuss the basic concepts and related essential statistical infrastructure for animal breeding studies in the genomics era. We also present a simple example and Julia language codes for implementing analysis of genomic features in animal breeding. On the basis of the above content, future challenges discussed include using whole genome sequence data and systems analysis.

关 键 词：动物育种 计算生物学 全基因组关联 基因组选择 数量遗传学 Julia语言 

分 类 号：S813[农业科学—畜牧学]