Integrating genome structure information and statistical analysis of co-segregation of rare genetic variants with phenotypes in families

在家族遗传学研究中，具有感兴趣表型的亲属共享稀有遗传变异(RV)是推断RV参与表型的关键信息。我带头开发了在远亲对象之间分享房车的概率，作为将房车与一种表型联系起来的基础。将这种方法应用于全基因组测序研究面临着一些挑战：1)目前还没有一种有效的方法来分组基因间变异，预计这些变异对基因调控有类似的影响；2)RV的丰富意味着在需要精确描绘的小基因组区域内，多个RV出现在同一单倍型上；以及3)由于表面上不相关的家庭成员之间的未知关系，RV共享的概率可能被低估。我建议在我的研究计划中通过以下具体目标来解决这些挑战：*1.基于3D染色体接触定义稀有变异簇，并开发基于家庭的统计数据来测试这些簇与全基因组序列数据中的二分表型之间的联系。*为此，RV簇将从高通量染色体构象捕获实验产生的3D接触矩阵衍生而来，因为密切接触的区域涉及相同的基因调控过程。房车共享统计数据将在3D联系人的域内和跨不同域的簇上开发。*2.准确推断远亲之间的重组事件，以改进稀有变异单倍型推断。*将通过结合来自家庭中的遗传传播和来自人群单倍型频率的信息来实现这一目标。*3.更准确地模拟家庭成员之间的未知关系。*将合作者开发的远距离亲缘关系估计整合到房车共享方法中。*4.开发一个软件工具，将稀有变异统计数据与3D联系人数据库链接起来。***提出的方法将作为BioConductor项目的一个包来实现，以扩展现有的R包RVSharing。*实际DNA序列，表型和家庭结构数据将用于训练模型、测试方法和软件，以及校准模拟以评估统计特性。这项研究计划将为研究人员进行家族遗传学研究提供新的工具，并在有这样的研究人员参与的环境中培训研究生生物统计学和生物信息学。

In familial genetic studies, sharing of rare genetic variants (RVs) by relatives with a phenotype of interest is a key piece of information to infer the involvement of the RVs in the phenotype. I have spearheaded the development of RV sharing probabilities among distantly related subjects as basis to link RVs to a phenotype. The application of this approach to whole genome sequencing studies presents a number of challenges: 1) there is currently no validated approach to group intergenic variants expected to have a similar impact on gene regulation; 2) the abundance of RVs implies that multiple RVs occur on the same haplotype within small genomic regions which need to be precisely delineated and 3) RV sharing probabilities may be underestimated due to unknown relationships among apparently unrelated family members. I propose to address these challenges in my research program through the following specific objectives:******1. Define clusters of rare variants based on 3D chromosomal contacts and develop family-based statistics to test the link between these clusters and dichotomous phenotypes in whole genome sequence data.***To this end, clusters of RVs will be derived from 3D contact matrices produced by high-throughput chromosome conformation capture experiments, as regions in close contact are involved in the same gene regulation processes. RV sharing statistics will be developed over clusters within domains of 3D contacts and across distinct domains.******2. Accurately infer recombination events between distant relatives to improve rare variant haplotype inference.***This aim will be achieved by combining information from genetic transmission in families and from population haplotype frequencies.******3. Model more accurately unknown relationships among family members.***Estimates of distant relatedness developed by collaborators will be integrated in the RV sharing approach.******4. Develop a software tool linking rare variant statistics and 3D contact databases.***The proposed methods will be implemented as a package for the Bioconductor project expanding the existing R package RVsharing.******Actual DNA sequence, phenotype and family structure data will be used for training models, testing methods and software and calibrating simulations for evaluating statistical properties. This research program will provide new tools for researchers conducting familial genetic studies and train graduate students in biostatistics and bioinformatics in an environment involving such researchers.