Defining interaction quantitative trait loci (iQTLs) in the human genome

定义人类基因组中的相互作用数量性状位点 (iQTL)

基本信息

批准号：
9980439
负责人：
Ferhat Ay
金额：
$ 44.96万
依托单位：
LA JOLLA INSTITUTE FOR IMMUNOLOGY
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-08-01 至 2023-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9980439
关键词：
3-Dimensional Address Affect Asthma Binding Biological Biological Assay Cell physiology Chromatin Chromatin Structure Code Collaborations Computer Analysis Computing Methodologies DNA DNA Sequence Dependence Dimensions Disease Disease susceptibility Distal Experimental Designs Expression Profiling Gene Expression Gene Expression Regulation Gene Structure Genes Genetic Genetic Variation Genotype Goals Human Human Genome Immune Institutes Knowledge Laboratories Machine Learning Molecular Biology Techniques Population Positioning Attribute Predisposition Quantitative Trait Loci Research Resources Role Sampling Specificity Susceptibility Gene Uncertainty Untranslated RNA Variant Work base cell type chromosome conformation capture genetic variant genome wide association study genome-wide genome-wide analysis graph theory histone modification novel predictive modeling programs promoter statistics transcription factor

项目摘要

Abstract My research aims to understand the role of three-dimensional (3D) chromatin structure in gene regulation. This involves studying associations among genotype, histone modifications, transcription factor binding, non-coding RNAs, chromatin interactions and gene expression. In order to transform this genome-wide information into new biological discoveries, my laboratory develops scalable and interpretable computational methods based on statistics, graph theory and machine learning. Our recent focus is to address an important gap in the current knowledge of the role of 3D chromatin structure in gene regulation. That is, we aim to define how genotypic variation affects 3D organization of gene promoters, and in turn, their expression. To achieve this at a genome- wide scale is an ambitious goal, because it requires having at a minimum, genotype, gene expression and chromatin interaction profiles in pure populations of specific cell types from a large number of donors. However, my laboratory is uniquely positioned to perform this research because: i) we are involved in a study at the La Jolla Institute (LJI-R24AI108564) that has already genotyped ~100 donors and expression-profiled more than 15 different pure populations of human immune cell types, and we have access to the same samples for chromatin interaction mapping, ii) in collaboration with other groups at LJI, we have already discovered a prototypical example of an interaction quantitative trait locus (iQTL) that alters and rewires interactions from the promoter of a specific gene that is associated with asthma susceptibility, iii) we have the necessary expertise and proven track record in experimental design and computational analyses of various chromatin conformation capture assays. Leveraging the resources available at LJI and our expertise in the field, we will build a unique research program around the novel concept of iQTLs. The emerging set of three main questions we propose to address within the next five years are: Q1) How do we define cell-type-specific iQTLs for common genetic variants? Q2) What is the extent of overlap between iQTLs and GWAS SNPs? Q3) Can we build predictive models for the cell-type specificity of chromatin interactions and iQTLs? Although we propose to define iQTLs only in two abundant, easily accessible, and highly disease-relevant immune cell types, the concept of iQTLs is equally important in other cell types implicated in diseases with a genetic component. Hence, the proof-of-concept developed by this work, without a doubt, will open up a new field in studying a previously uncharacterized role for disease-susceptibility variants, specifically non-coding SNPs, from genome-wide association studies (GWAS) in gene regulation.

抽象的我的研究旨在了解三维 (3D) 染色质结构在基因调控中的作用。这涉及研究基因型、组蛋白修饰、转录因子结合、非编码之间的关联 RNA、染色质相互作用和基因表达。为了将这种全基因组信息转化为新的生物学发现，我的实验室开发了基于可扩展和可解释的计算方法统计学、图论和机器学习。我们最近的重点是解决当前的一个重要差距了解 3D 染色质结构在基因调控中的作用。也就是说，我们的目标是定义基因型如何变异影响基因启动子的 3D 组织，进而影响其表达。为了在基因组上实现这一目标- 大规模是一个雄心勃勃的目标，因为它需要至少具有基因型、基因表达和来自大量供体的特定细胞类型的纯群体中的染色质相互作用谱。然而，我的实验室具有独特的优势来开展这项研究，因为： i) 我们参与了一项研究拉霍亚研究所 (LJI-R24AI108564) 已对约 100 名捐赠者进行了基因分型并进行了表达谱分析超过 15 种不同的纯人类免疫细胞类型群体，我们可以获得相同的染色质相互作用图谱样本，ii) 与 LJI 的其他小组合作，我们已经发现了一个相互作用数量性状基因座（iQTL）的典型例子，它会改变和重新连接与哮喘易感性相关的特定基因启动子的相互作用，iii) 我们有各种实验设计和计算分析中必要的专业知识和良好的记录染色质构象捕获测定。利用 LJI 的可用资源和我们在在这一领域，我们将围绕 iQTL 的新颖概念建立一个独特的研究项目。新兴的三人组我们建议在未来五年内解决的主要问题是： Q1) 我们如何定义细胞类型特异性常见遗传变异的 iQTL？ Q2) iQTL 和 GWAS SNP 之间的重叠程度是多少？ Q3) 我们能否为染色质相互作用和 iQTL 的细胞类型特异性建立预测模型？虽然我们建议仅在两种丰富、易于获取且与疾病高度相关的免疫细胞中定义 iQTL 类型中，iQTL 的概念对于与遗传性疾病有关的其他细胞类型同样重要。成分。因此，这项工作所开发的概念验证无疑将开辟一个新的领域研究疾病易感性变异的先前未表征的作用，特别是非编码 SNP，来自基因调控的全基因组关联研究（GWAS）。