Computational approaches for comparative regulatory genomics to decipher long-range gene regulation

比较调控基因组学的计算方法来破译远程基因调控

• 批准号: 10208923
• 负责人: Sushmita Roy
• 金额: $ 33.29万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-17 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10208923
• 关键词: 3-Dimensional; Address; Affect; Animal Model; Awareness; Basic Science; Binding; Biological; Biological Markers; CRISPR/Cas technology; Cardiovascular Diseases; Cell Line; Cell model; Cells; Chromatin; Comparative Study; Complex; Computing Methodologies; Data; Data Set; Development; Diabetes Mellitus; Dimensions; Disease; Distal; Elements; Endothelial Cells; Enhancers; Gene Expression; Gene Expression Regulation; Genes; Genome; Genomic Segment; Genomics; Goals; Graph; Hi-C; Human; Ice; Individual; Joints; Link; Machine Learning; Malignant Neoplasms; Measurement; Measures; Methods; Modeling; Obesity; Pathway interactions; Performance; Phenotype; Phylogenetic Analysis; Play; Process; Protocols documentation; Psychological Transfer; Publishing; Regulation; Regulator Genes; Regulatory Element; Research Personnel; Resolution; Resources; Role; Signal Transduction; Software Tools; Statistical Models; Technology; Testing; Tissue-Specific Gene Expression; Training; Translational Research; Untranslated RNA; Variant; base; cell type; chromosome conformation capture; comparative; cost; epigenome; epigenomics; experimental study; follow-up; genomic locus; histone modification; human disease; improved; learning classifier; markov model; multi-task learning; multiple datasets; multitask; novel; promoter; tool; trait; transcription factor

Project Abstract/Summary The three-dimensional organization of the genome is a major player in long-range gene regulation, where regulatory elements such as enhancers affect the expression of a gene hundreds of kilobases away. Changes in three-dimensional organization are associated with tissue-specific gene expression and have been implicated in several human diseases including cancer, diabetes and obesity. Advances in chromosome conformation capture (3C) technologies have expanded our repertoire of long-range interactions between enhancers and promoters in model cell lines and have shown that such interactions are established through a complex interplay of chromatin state, transcription factor binding and three-dimensional proximity of genomic regions. However, our current understanding of the dynamics of long-range gene regulation is limited, both across different cell types as well as across different species. This is because of the absence of such datasets in most species and cell types, lack of systematic methods to predict and interpret these interactions, and due to limited approaches to compare both the regions and their interactions across different cell types and especially across species. The overarching goals of this proposal are to develop novel computational methods to jointly identify candidate regulatory elements in multiple species and predict their long- range interactions in new cell types and species where high-throughput 3C datasets are not available or difficult to obtain. In Aim 1, we will develop a phylogenetically aware method of jointly identifying regulatory elements such as enhancers in multiple species. Aim 2 will develop multi-task and transfer learning approaches to predict interactions in new species and cell types by integrating available high-throughput 3C datasets from multiple cell types and 3C platforms. In Aim 3, we will collect a novel multi-species chromatin mark dataset in species-specific endothelial cells to enable a systematic study of long-range gene regulation dynamics. We will apply our computational approaches developed in Aims 1 and 2 on this multi-species epigenomic dataset to identify different regulatory elements and predict long-range interactions in multiple species. We will develop rigorous computational measures to evaluate the quality of predictions from our novel methods and the improvements compared to existing methods based on published 3C datasets. We will further experimentally validate predicted interactions using Capture-HiC in multiple species and using CRISPR/Cas9 experiments. We will examine individual and groups of interactions to identify species-specific, and clade- specific interactions and interpret the corresponding genes in the context of known pathways and curated gene sets associated with cardiovascular diseases. Our methods will be widely applicable to dissect long-range gene regulation in complex phenotypes including diseases. Software tools, resources, original data and experimental protocols developed by this project will be made publicly available.

项目摘要/摘要 基因组的三维结构是远程基因调控的主要参与者， 调节元件如增强子影响几百个碱基以外的基因的表达。变化 与组织特异性基因表达有关， 与包括癌症、糖尿病和肥胖症在内的几种人类疾病有关。染色体研究进展 构象捕获（3C）技术已经扩展了我们的远程相互作用的剧目， 增强子和启动子，并已表明这种相互作用是通过 染色质状态、转录因子结合和基因组三维邻近性的复杂相互作用 地区然而，我们目前对长距离基因调控动力学的理解是有限的， 在不同的细胞类型和不同的物种之间。这是因为缺乏这样的数据集 在大多数物种和细胞类型中，缺乏系统的方法来预测和解释这些相互作用， 有限的方法来比较区域和它们在不同细胞类型之间的相互作用， 尤其是在物种之间。该提案的总体目标是开发新的计算 联合鉴定多个物种中的候选调控元件并预测其长期 在高通量3C数据集不可用的新细胞类型和物种中的范围相互作用 或难以获得。在目标1中，我们将开发一种遗传感知的方法， 调节元件，例如多个物种中的增强子。目标2将开发多任务和迁移学习 通过整合现有的高通量3C技术来预测新物种和细胞类型中相互作用的方法 来自多种细胞类型和3C平台的数据集。在目标3中，我们将收集一种新的多物种染色质 标记物种特异性内皮细胞中的数据集，以便能够系统地研究长距离基因调控 动力学我们将把我们在目标1和2中开发的计算方法应用于这种多物种 表观基因组数据集，以确定不同的调控元件，并预测在多个 物种我们将制定严格的计算措施，以评估我们的小说预测的质量。 方法和改进相比，现有的方法的基础上公布的3C数据集。我们将进一步 在多个物种中使用Capture-HiC和使用CRISPR/Cas9 实验我们将研究个体和群体的相互作用，以确定物种特异性和进化枝- 特定的相互作用，并在已知途径和策划基因的背景下解释相应的基因 与心血管疾病相关的疾病。我们的方法将广泛适用于长距离解剖 复杂表型包括疾病的基因调控。软件工具、资源、原始数据和 该项目制定的实验规程将向公众公布。

项目成果

Competition between transcription and loop extrusion modulates promoter and enhancer dynamics.

转录和环挤出之间的竞争调节启动子和增强子的动态。

• DOI: 10.21203/rs.3.rs-3164817/v1
• 发表时间: 2023
• 期刊: Research square
• 作者: Sexton T

Enabling Studies of Genome-Scale Regulatory Network Evolution in Large Phylogenies with MRTLE.

通过Mrtle的大系统发育中的基因组规模调节网络进化的研究。

• DOI: 10.1007/978-1-0716-2257-5_24
• 发表时间: 2022
• 期刊: Methods in molecular biology (Clifton, N.J.)

Transcriptional regulation and chromatin architecture maintenance are decoupled functions at the Sox2 locus.

• DOI: 10.1101/gad.349489.122
• 发表时间: 2022-06-01
• 期刊: GENES & DEVELOPMENT
• 影响因子: 10.5
• 作者: Taylor, Tiegh;Sikorska, Natalia;Shchuka, Virlana M.;Chahar, Sanjay;Ji, Chenfan;Macpherson, Neil N.;Moorthy, Sakthi D.;de Kort, Marit A. C.;Mullany, Shanelle;Khader, Nawrah;Gillespie, Zoe E.;Langroudi, Lida;Tobias, Ian C.;Lenstra, Tineke L.;Mitchell, Jennifer A.;Sexton, Tom
• 通讯作者: Sexton, Tom