来自三维单细胞染色质构象高分辨率整合模型的eQTL位点差异基因表达的结构基础。

Structural basis of differential gene expression at eQTLs loci from high-resolution ensemble models of 3D single-cell chromatin conformations.

作者信息

Du Lin, Farooq Hammad, Delafrouz Pourya, Liang Jie

机构信息

Center for Bioinformatics and Quantitative Biology, Richard and Loan Hill Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL 60612, United States.

出版信息

Bioinformatics. 2025 Feb 4;41(2). doi: 10.1093/bioinformatics/btaf050.

DOI:10.1093/bioinformatics/btaf050

PMID:39891345

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11835231/

Abstract

MOTIVATION

Techniques such as high-throughput chromosome conformation capture (Hi-C) have provided a wealth of information on nucleus organization and genome important for understanding gene expression regulation. Genome-Wide Association Studies have identified numerous loci associated with complex traits. Expression quantitative trait loci (eQTL) studies have further linked the genetic variants to alteration in expression levels of associated target genes across individuals. However, the functional roles of many eQTLs in noncoding regions remain unclear. Current joint analyses of Hi-C and eQTLs data lack advanced computational tools, limiting what can be learned from these data.

RESULTS

We developed a computational method for simultaneous analysis of Hi-C and eQTL data, capable of identifying a small set of nonrandom interactions from all Hi-C interactions. Using these nonrandom interactions, we reconstructed large ensembles (×105) of high-resolution single-cell 3D chromatin conformations with thorough sampling, accurately replicating Hi-C measurements. Our results revealed many-body interactions in chromatin conformation at the single-cell level within eQTL loci, providing a detailed view of how 3D chromatin structures form the physical foundation for gene regulation, including how genetic variants of eQTLs affect the expression of associated eGenes. Furthermore, our method can deconvolve chromatin heterogeneity and investigate the spatial associations of eQTLs and eGenes at subpopulation level, revealing their regulatory impacts on gene expression. Together, ensemble modeling of thoroughly sampled single-cell chromatin conformations combined with eQTL data, helps decipher how 3D chromatin structures provide the physical basis for gene regulation, expression control, and aid in understanding the overall structure-function relationships of genome organization.

AVAILABILITY AND IMPLEMENTATION

It is available at https://github.com/uic-liang-lab/3DChromFolding-eQTL-Loci.

摘要

动机

诸如高通量染色体构象捕获（Hi-C）等技术已经提供了大量关于细胞核组织和基因组的信息，这对于理解基因表达调控非常重要。全基因组关联研究已经确定了许多与复杂性状相关的基因座。表达定量性状基因座（eQTL）研究进一步将遗传变异与个体间相关靶基因表达水平的改变联系起来。然而，许多非编码区域中eQTL的功能作用仍不清楚。目前对Hi-C和eQTL数据的联合分析缺乏先进的计算工具，限制了从这些数据中所能学到的东西。

结果

我们开发了一种用于同时分析Hi-C和eQTL数据的计算方法，该方法能够从所有Hi-C相互作用中识别出一小部分非随机相互作用。利用这些非随机相互作用，我们通过全面采样重建了大量（×105）高分辨率单细胞3D染色质构象集合，准确地复制了Hi-C测量结果。我们的结果揭示了eQTL基因座内单细胞水平染色质构象中的多体相互作用，详细展示了3D染色质结构如何为基因调控形成物理基础，包括eQTL的遗传变异如何影响相关e基因的表达。此外，我们的方法可以解卷积染色质异质性，并在亚群体水平上研究eQTL和e基因的空间关联，揭示它们对基因表达的调控影响。总之，对全面采样的单细胞染色质构象进行集合建模并结合eQTL数据，有助于解读3D染色质结构如何为基因调控、表达控制提供物理基础，并有助于理解基因组组织的整体结构-功能关系。