QTCC: From Quantitative Trait Correlation to Causation in dairy cattle

QTCC：从奶牛的数量性状相关性到因果关系

• 批准号: 448536632
• 负责人: Professor Dr. Jörn Bennewitz
• 金额: --
• 依托单位: Institut für Tierzucht und Tierhaltung
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/448536632?language=en
• 关键词: QTCC; Quantitative; Trait; Correlation; Causation

The breeding goal in dairy cattle breeding includes performance traits (e.g. milk yield) and fertility and health traits, and longevity. Feed efficiency traits will be part of the breeding goal in the near future. Modern genomic tools applied to large data sets and augmented with external information about genome sequence variants allows for the comprehensive dissection of the genetic architecture of quantitative traits and, beyond that, of the shared architecture of multiple traits. The aim of the project is to analyse the interrelationships of the quantitative traits in dairy cattle beyond global correlations towards local correlation and causations. The traits considered belong to the complexes milk performance traits, fertility traits, health traits, and efficiency traits. In particular (but not exclusive), milk performance and feed efficiency will be contrasted against fertility and health traits. The following hypotheses will be tested. (i) The dissection of global genetic correlations between quantitative traits down to functional and evolutionary relevant genomic regions identifies trait-shared and trait-specific genetic architectures. (ii) The identification of pleiotropic and trait-specific lead variants allows for the separation of common and trait-specific metabolic pathways, and this in turn facilitates the identification of causative relationships between traits. (iii) Milk performance and feed efficiency are significant exposure traits which causally compromise the cow’s fertility and health. These hypotheses will be tested using modern genomic methods, partly augmented with external information, applied to a unique and disruptive observational data sets involving 150K cows with SNP-chip information, imputed whole genome sequence variants, and records for a large panel of quantitative traits. The results are important to understand and dissect the interrelationship and shared genetic architecture of the trait complexes down to single variants levels.

奶牛育种的育种目标包括性能性状（例如产奶量）以及生育力和健康性状，而饲料效率性状将在不久的将来成为育种目标的一部分，并通过大数据集进行增强。有关基因组序列变异的外部信息可以全面剖析数量性状的遗传结构，此外还可以分析多个性状的共享结构。该项目的目的是分析全球范围内奶牛数量性状的相互关系。与当地的相关性所考虑的性状属于综合性状，包括产奶性能、生育力、健康性状和效率性状，特别是（但不排除）产奶性能和饲料效率将与生育力和健康性状进行对比。 (i) 将数量性状之间的全局遗传相关性剖析到功能和进化相关的基因组区域，以确定性状共享和性状特异性遗传结构 (ii) 多效性和性状特异性先导变异的鉴定。共同点和共同点的分离(iii) 产奶性能和饲料效率是影响奶牛生育力和健康的重要暴露性状，这些假设将使用现代基因组方法进行测试。部分用外部信息进行增强，应用于涉及 15 万头奶牛的独特且颠覆性的观察数据集，其中包含 SNP 芯片信息、估算的全基因组序列变异以及大量数量性状的记录。结果对于理解和剖析非常重要。性状复合体的相互关系和共享遗传结构低至单个变异水平。