Evidence map›Paper›PMID 39891345›Full record

ArticleBioinformatics (Oxford, England)2025

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

Lin Du, Hammad Farooq, Pourya Delafrouz, Jie Liang

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Lin DuCenter for Bioinformatics and Quantitative Biology, Richard and Loan Hill Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL 60612, United States.ORCID 0009-0002-8986-9812
Hammad FarooqCenter for Bioinformatics and Quantitative Biology, Richard and Loan Hill Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL 60612, United States.ORCID 0000-0001-5691-298X
Pourya DelafrouzCenter for Bioinformatics and Quantitative Biology, Richard and Loan Hill Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL 60612, United States.
Jie LiangCenter for Bioinformatics and Quantitative Biology, Richard and Loan Hill Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL 60612, United States.ORCID 0000-0002-2773-6427

Funding

Models and Algorithms for Biological Networks and Polymers: Stochastic Probability Landscape and Chromatin EnsemblesR35GM127084 · NIGMS · UNIVERSITY OF ILLINOIS AT CHICAGO · PI LIANG, JIE · 2018 to 2025
$3.7M
Predicting 3D physical gene-enhancer interactions through integration of GTEx and 4DN dataR03OD036492 · OD · UNIVERSITY OF ILLINOIS AT CHICAGO · PI LIANG, JIE · 2023 to 2023
$298k
Innovative and Novel Computational Impact on Theory and ExperimentNIGMS NIH HHS R35 GM127084NIH HHS 1R03OD032628-01NIH HHS R03 OD036492U.S. Department of Energy
6 · The paper itself

Abstract

motivationTechniques 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.

resultsWe 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.

Indexed as

ChromatinQuantitative Trait LociSingle-Cell AnalysisGene Expression RegulationGenome-Wide Association StudyHumansChromatin

Identifiers

PMID39891345
PMCPMC11835231

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.