Genomic selection in dairy cattle

基因组选择涉及到基因组的密集标记图和应用统计模型来同时估计每个标记或标记之间的间隔的影响。对牛基因组的测序导致了数千种遗传标记的检测。最近，利用全基因组密集单核苷酸多态(SNP)标记图谱预测动物总遗传值的方法已经被开发出来。基于这些预测基因组值的选择预计将对育种计划产生巨大影响，但需要进一步发展才能成功地将这项技术应用于家畜。对每个标记或标记间间隔效应的估计也可以用来确定影响性状的潜在基因的位置。虽然模拟表明基因组选择具有提高遗传获得率的巨大潜力，但实际数据的结果显示出的反应比预期的要低。在实际应用中仍有几个关键问题需要进一步研究，如标记或染色体片段效应的最佳估计所需的标记密度和数据结构，以及如何改变育种计划以最大限度地提高基因组选择的收益。这项提议将增加对影响估计过程和基因组选择实施的准确性的因素的了解，从而为这项新技术带来最佳的育种策略。该提案的总体目标是加强奶牛基因组选择的方法，提高基因组育种价值预测的准确性，并通过基因组选择优化奶牛育种策略。

Genomic selection involves a dense marker map of the genome and the application of a statistical model to simultaneously estimate the effects of every marker or interval between markers. The sequencing of the bovine genome has resulted in the detection of many thousands of genetic markers. Recently, methods have been developed to predict total genetic value of animals using whole-genome dense single nucleotide polymorphism (SNP) marker maps. Selection based on these predicted genomic values is expected to have an enormous impact on breeding programs, but further development is needed to successfully apply this technology to livestock. The estimates of the effects of every marker or interval between markers can also be used to determine the location of potential genes affecting a trait. While simulations demonstrate genomic selection has huge potential to increase rates of genetic gain, results with real data have shown lower response than the prospects. Several key questions remain regarding practical implementation and they should be further investigated, such as density of markers and data structure required for optimum estimation of the effects of markers or chromosome segments, and how the breeding programs should be altered to maximize the gains from genomic selection. This proposal will increase the knowledge about the factors that influence the accuracy of the estimation process and the implementation of genome selection, leading to optimal breeding strategies for this new technology. The overall objectives of the proposal are enhancing methods of genomic selection in dairy cattle, increasing the accuracy of predictions of genomic breeding values, and optimizing dairy cattle breeding strategies through genomic selection.