Leveraging identity-by-descent information in large-scale population sequencing

描述（由申请人提供）：该项目旨在开发方法，其中特定染色体片段的共享祖先基因流模式可以在无血缘关系的个体之间推断，并用于分析通过测序发现的罕见突变，与精神分裂症等疾病的相关性。血统同一性（IBD）意味着两个或更多个个体各自携带一段延伸的单倍体序列，该序列是单个祖先单倍型的直接拷贝或后代，该单倍型存在于（或曾经存在于）这些个体的最近共同祖先中。在大量样本中，我们经常会发现成千上万个看似无关的个体，在基因组的某个部分上，与父母和后代的关系一样密切。在对罕见和常见遗传变异进行的大规模、基于人群的研究的背景下，我们提出，在测序的罕见突变和多态性数据集之上分层绘制个体内IBD共享地图，可以帮助应对将遗传变异与常见疾病风险联系起来的艰巨挑战。具体来说，我们建议在测序研究中使用IBD共享信息，以1）识别可能的从头和最近（私人）突变，2）优先考虑 罕见变异体可能的功能影响，以及3）允许额外的未测序样品根据它们与测序个体共享IBD的因果关系的可能性来优先考虑罕见等位基因。我们将把这里开发的方法应用于两个大型的精神分裂症测序研究，其中包括6,000多个个体的全外显子组数据和14000多个全基因组SNP数据。这里开发的统计方法将作为PLINK/Seq软件包的一部分实施和分发。

DESCRIPTION (provided by applicant): This project aims to develop ways in which the patterns of shared ancestral gene-flow for specific chromosomal segments can be inferred between seemingly-unrelated individuals and used to empower analyses of rare mutations discovered by sequencing, with respect to association with diseases such as schizophrenia. Identity-by-descent (IBD) implies that two or more individuals each carry an extended stretch of haploid sequence that is a direct copy, or descendant, of a single, ancestral haplotype that resides (or once resided) in a recent common ancestor of those individuals. In large samples it is not unusual to find many thousands of instances in which seemingly unrelated individuals are, for some fraction of their genome, related exactly as closely as are parent and offspring. In the context of large, population-based studies of rare and common genetic variation, we propose that layering a map of intra-individual IBD sharing on top of datasets of rare mutation and polymorphism from sequencing can help in the daunting challenge of relating genetic variation to risk for common disease. Specifically, we propose to use IBD sharing information in sequencing studies to 1) identify likely de novo and very recent (private) mutations, 2) prioritize rare variants for likely functional impact and 3) allow additional un-sequenced samples to prioritize rare alleles according to the likelihood they are causal given their IBD sharing with sequenced individuals. We will apply the methods developed here to two large schizophrenia sequencing studies, with whole-exome data on over 6,000 individuals and genome-wide SNP data on over 14,000. The statistical approaches developed here will be implemented and distributed as part of the PLINK/Seq software package.