BioinformaticsBioinformaticsPeer-reviewed journal article
Structural Basis of Differential Gene Expression at eQTLs Loci from High-Resolution Ensemble Models of 3D Single-Cell Chromatin Conformations
Abstract
MotivationTechniques such as high-throughput chromosome conformation capture (Hi-C) have provided a wealth of information on the organization of the nucleus and the genome important for understanding gene expression regulation. Additionally, Genome-Wide Association Studies (GWASs) have uncovered thousands of loci related to 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 located in non-coding regions are unclear. Current joint analyses of Hi-C and eQTLs data lack advanced computational tools, limiting what can be learned from these data. ResultIn this work, we developed a computational method for simultaneous analysis of Hi-C and eQTL data. Our method can identify a small set of non-random interactions from all Hi-C interactions. Using these non-random interactions, we reconstruct large ensemble (x105) of high-resolution single-cell 3D chromatin conformations with thorough sampling, which accurately replicate Hi-C measurements. Our results revealed the presence of many-body interactions in chromatin conformation at single-cell level in eQTL locus, offering detailed view into how three-dimensional structures of chromatin form the physical foundation for gene regulation, including how genetic variants of eQTLs affect the expression level of their associated eGenes. Furthermore, our method can deconvolve chromatin heterogeneity and investigate the spatial associations of eQTLs and eGenes at subpopulation level to reveal their regulatory impacts on gene expression. Together, ensemble modeling of thoroughly sampled single cell chromatin conformations from Hi-C, along with eQTL data, helps to decipher how chromatin 3D structures provide the physical basis for gene regulation, expression control, and aid in understanding of the overall structure-function relationships of genome organization. Availability and implementation: It is available at https://github.com/uic-liang-lab/3DChromFolding-eQTL-Loci
- assay: Hi-C
- assay: GWAS summary statistics
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 6
- FWCI
- 1.79
- Field percentile
- top 17%
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