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：
9576241
负责人：
Ferhat Ay
金额：
$ 44.98万
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/9576241
关键词：
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节中的作用。这涉及研究基因型之间的关联，组蛋白修饰，转录因子结合，非编码 RNA，染色质相互作用和基因表达。为了将此全基因组信息转换为我的新生物学发现，我的实验室基于可扩展和可解释的计算方法开发关于统计，图理论和机器学习。我们最近的重点是解决当前的重要差距了解3D染色质结构在基因调节中的作用。也就是说，我们旨在定义基因型如何变异会影响基因启动子的3D组织，进而影响其表达。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纯种群中的染色质相互作用曲线。但是，我的实验室在执行这项研究方面具有独特的位置，因为：i）我们参与了一项研究在La Jola Institute（LJI-R24AI108564）上，已经构成了〜100个捐助者和表达方式超过15种不同的人类免疫细胞类型种群，我们可以使用相同染色质相互作用映射的样本，ii）与LJI的其他组合作，我们已经发现了一个变化和重新布线的相互作用定量性状基因座（IQTL）的原型示例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的必要专业知识和良好的记录染色质构象捕获测定法。利用LJI可用的资源以及我们的专业知识领域，我们将围绕IQTL的新颖概念构建一个独特的研究计划。三个新兴我们建议在未来五年内提出的主要问题是：Q1）我们如何定义细胞类型常见遗传变异的IQTL？ Q2）IQTL和GWAS SNP之间的重叠程度是多少？ Q3）我们可以为染色质相互作用和IQTL的细胞类型特异性建立预测模型吗？虽然我们建议仅在两个丰富的，易于访问且与疾病的免疫细胞中定义IQTL 类型，IQTL的概念在与遗传性疾病有关的其他细胞类型中同样重要成分。因此，毫无疑问，由这项工作开发的概念证明将在研究以前未表征的疾病敏感性变体的作用，特别是非编码SNP，来自基因调节中全基因组关联研究（GWAS）。