Sellner E M, Kim J W, McClure M C, Taylor K H, Schnabel R D, Taylor J F
Division of Animal Sciences, University of Missouri, Columbia 65211, USA.
J Anim Sci. 2007 Dec;85(12):3148-58. doi: 10.2527/jas.2007-0291. Epub 2007 Aug 20.
The availability of whole genome sequences for individual species will change the landscape for livestock genomic research. Animal scientists will have access to whole-genome sequence-based technologies such as high-throughput SNP genotyping assays, gene expression profiling, methylation profiling, RNA interference, and genome resequencing that will revolutionize the scale upon which research will be conducted. These technologies will also alter the ways we think about addressing industry and scientific problems. In this review, we discuss the scientific bases for these emerging technologies and present recent highlights of their application in human, model species, and livestock as well as their potential for future applications in livestock. Additionally, we discuss strategies for their use in the genetic improvement and management of livestock. In particular, we present a strategy for the simultaneous identification of causal mutations underlying phenotypic traits in livestock and discuss issues that will arise in the application of whole genome selection for the prediction of genetic merit in livestock. We also point out that the statistical analysis that underlies the whole genome selection methodology is a sophisticated enhancement of single marker association mapping analysis to allow the entire genome to be simultaneously analyzed.
单个物种全基因组序列的可得性将改变家畜基因组研究的局面。动物科学家将能够使用基于全基因组序列的技术,如高通量SNP基因分型检测、基因表达谱分析、甲基化谱分析、RNA干扰和基因组重测序,这些技术将彻底改变研究开展的规模。这些技术还将改变我们思考解决行业和科学问题的方式。在本综述中,我们讨论这些新兴技术的科学基础,并介绍它们在人类、模式物种和家畜中的应用近况以及它们未来在家畜中应用的潜力。此外,我们讨论在牲畜遗传改良和管理中使用这些技术的策略。特别是,我们提出了一种同时鉴定家畜表型性状潜在因果突变的策略,并讨论在应用全基因组选择预测家畜遗传价值时将出现的问题。我们还指出,全基因组选择方法所依据的统计分析是对单标记关联图谱分析的复杂改进,以便能够同时分析整个基因组。