Kartenbasierte und Funktionsorientierte genomische Ansätze zur Analyse der Vererbung und Ausprägung von Merkmalen des Wasserbindungsvermögens in kommerziellen Schweinepopulationen

基于图谱和功能导向的基因组方法来分析商品猪群体中水结合性状的遗传和表达

• 批准号: 168151505
• 负责人: Professor Dr. Tosso Leeb
• 金额: --
• 依托单位: Institut für Genetik
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2009
• 资助国家: 德国
• 起止时间: 2008-12-31 至 2013-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/168151505?language=en
• 关键词: Kartenbasierte; und; Funktionsorientierte; genomische; Ans

In this project we will investigate the genes underlying drip loss variation in commercial pig populations. On the one hand, we will continue to analyse candidate genes identified during the initial phase of the DRIP research unit. On the other hand, we will also employ novel cutting edge experimental strategies, which became only available during the last two years. We plan to study the expression of all transcripts including non-coding RNAs in selected regions of the QTL-intervals using tiling microarrays. With this approach we will look for differences in the expression patterns between phenotypically divergent and QTL-genotype divergent pigs. Furthermore, we will perform a genome-wide association analysis to directly identify the causative loci for drip loss in commercial pig populations. Selected candidate genes will be characterised in detail to provide markers for improved breeding programs with respect to meat quality and ideally also to identify the causative mutations themselves.

在这个项目中，我们将研究商品猪群体滴水损失变化背后的基因。一方面，我们将继续分析 DRIP 研究单元初始阶段确定的候选基因。另一方面，我们还将采用最近两年才出现的新颖的前沿实验策略。我们计划使用平铺微阵列研究 QTL 区间选定区域中所有转录物（包括非编码 RNA）的表达。通过这种方法，我们将寻找表型趋异猪和 QTL 基因型趋异猪之间表达模式的差异。此外，我们将进行全基因组关联分析，以直接识别商业猪群滴水损失的致病位点。选定的候选基因将被详细表征，以便为改善肉质育种计划提供标记，并且理想情况下还可以识别致病突变本身。

项目成果

A Genome-Wide Association Study to Detect QTL for Commercially Important Traits in Swiss Large White Boars

检测瑞士大白公猪商业重要性状 QTL 的全基因组关联研究

• DOI: 10.1371/journal.pone.0055951
• 发表时间: 2013
• 期刊: PLoS ONE
• 影响因子: 3.7
• 作者: Becker D;Wimmers K;Luther H;Hofer A;Leeb T
• 通讯作者: Leeb T