权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

The role of the theoretical covariance between SNPs in the design of experiments in genomic evaluations

SNP 之间的理论协方差在基因组评估实验设计中的作用

基本信息

批准号：
320694892
负责人：
Dr. Dörte Wittenburg
金额：
--
依托单位：
Institut für Genetik und Biometrie
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2016
资助国家：
德国
起止时间：
2015-12-31 至 2020-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/320694892?language=en
关键词：
role theoretical covariance between SNPs

项目摘要

In animal breeding, molecular data (e.g., single nucleotide polymorphisms; SNPs) are incorporated as predictor variables in statistical models to reach an improved genomic evaluation of animals. This leads to more precisely estimated breeding values of not-yet phenotyped animals, which is important for breeding purposes, and enables the genetic architecture of some traits to be elucidated. Not only is the position on the genome a relevant parameter but so too is the effect size. Particularly, as with the high-dimensional SNP data that are available today, a causative variant can be pinpointed to a specific base pair on the genome. Due to the curse of dimensionality, the precision of effect estimates can only be approximated with time-consuming computational methods; it is not given in an analytical formula. As precision of estimates influences the outcome of testing for significance, the reliable identification of causative variants is complicated. The project aims to theoretically determine the standard error of SNP-effect estimates and the power of testing their significance, particularly for situations where the number of SNPs exceeds the number of individuals. The theory developed in this project will be validated with simulated and empirical data that are publicly available. Furthermore, when planning new experiments, it is essential to aim at a sufficiently large power to test the SNP effects. Thus, at a second stage, the project will investigate how a minimum required sample size can be determined prior to any genomic evaluation in a target population. The target population may consist of a mixture of half- and/or full-sib families. As genotypic data of target individuals are typically not available a-priori, we will employ the theoretical distribution of genotypes which can be inferred from parental genome information. Criteria for an optimal breeding design will be concluded by taking into account the trait-specific parameters, which have to be stipulated by the experimenter, and population-specific parameters, from which the theoretical distribution of SNPs is derived. The ultimate goal is to provide experimental designs useful for practical applications in which the genetic architecture of selected traits can be elucidated.

在动物育种中，分子数据（例如，单核苷酸多态性; SNP）作为预测变量并入统计模型中以实现动物的改进的基因组评估。这导致更精确地估计尚未表型化的动物的育种值，这对于育种目的是重要的，并且使得能够阐明某些性状的遗传结构。不仅基因组上的位置是一个相关的参数，而且效应大小也是一个相关的参数。特别是，与今天可用的高维SNP数据一样，可以将致病变体精确定位到基因组上的特定碱基对。由于维数灾难，效应估计的精度只能用耗时的计算方法近似;它不是在分析公式中给出的。由于估计值的精确度影响显著性检验的结果，因此致病变异的可靠鉴定是复杂的。该项目旨在从理论上确定SNP效应估计的标准误差和检验其显著性的能力，特别是在SNP数量超过个体数量的情况下。在这个项目中开发的理论将与公开的模拟和经验数据进行验证。此外，在计划新的实验时，必须以足够大的功率为目标来测试SNP效应。因此，在第二阶段，该项目将研究如何在目标人群中进行任何基因组评估之前确定所需的最小样本量。目标群体可以由半同胞和/或全同胞家庭的混合物组成。由于目标个体的基因型数据通常无法先验获得，我们将采用可以从亲本基因组信息推断的基因型的理论分布。最佳育种设计的标准将通过考虑必须由实验者规定的性状特异性参数和群体特异性参数得出结论，从这些参数中推导出SNP的理论分布。最终目标是提供对实际应用有用的实验设计，其中可以阐明选定性状的遗传结构。