Contribution of variants in non-protein coding regions of the genome to human health and disease

该项目的目的是揭示基因组非编码区域的变异对人类遗传疾病的贡献。目的与方法：理解规则组可变性的景观：学生将通过整合公开可用的表观基因组，调控和转录组数据来定义一系列人体组织的“规则组”。然后，这些规则组中最缺乏人类遗传变异的区域将使用群体变异频率进行排序，并与进化保护数据相结合。我们假设，这将预测患者的致病变异富集的规则组区域。2. 确定规则组中的人类致病变异：学生将询问来自患者的全基因组数据库（例如100,000基因组计划），以确定目标1中规划的规则组关键区域内的变异。与临床特征的相关性、来自家族内变异分离的信息以及调控区域的预测/已知功能将用于优先考虑极有可能导致患者疾病的变异。3. 研究致病调节变异的功能影响：根据变异的预测影响，将使用患者样本或细胞系进行靶向（如QPCR）或高通量（如RNASeq， Hi-C, dropSeq）测定。这将允许对变体进行功能性询问。最后，这些结果将与临床数据联系起来。结果：我们期望这个项目对我们理解非编码基因组中变异对人类健康和疾病的作用做出重大贡献。该项目预计将产生高影响力的出版物。

The aim of this project is to reveal the contribution of variants in the non-coding regions of the genome to human genetic disorders. Objectives and methods: 1. Understanding the landscape of variability of the regulome: The student will define 'regulomes' for a range of human tissues by integrating publicly available epigenomic, regulatory, and transcriptomic data. Then areas of the these regulomes that are most depleted for genetic variations in the humans will be ranked using population variant frequencies and integrated with evolutionary conservation data. We hypothesise that this will predict regions of the regulomes enriched for disease-causing variants in patients. 2. Identifying human disease-causing variants in the regulome: The student will interrogate whole genome databases from patients (e.g. the 100,000 Genomes project) to identify variants within the critical regions of the regulome curated in Objective 1. Correlations with clinical features, information from the segregation of the variants within families and the predicted/known functions of the regulatory region will be used to prioritise the variants that are highly likely to be responsible for the patients' diseases. 3. Studying the functional impact of disease-causing regulatory variants: Depending on the predicted impact of the variant, targeted (e.g. QPCR) or high-throughput (e.g. RNASeq, Hi-C, dropSeq) assays will be performed either using patient samples or cell lines. This will allow functional interrogation of the variants. Finally these results will be linked back with the clinical data. Outcome: We expect this project to make major contributions to our understanding of the role of variants in the non-coding genome on human health and disease. The project is expected to result in high-impact publication(s).