Integrative analysis of epigenetics data identifies gene-specific regulatory elements

  • Understanding how epigenetic variation in non-coding regions is involved in distal gene-expression regulation is an important problem. Regulatory regions can be associated to genes using large-scale datasets of epigenetic and expression data. However, for regions of complex epigenomic signals and enhancers that regulate many genes, it is difficult to understand these associations. We present StitchIt, an approach to dissect epigenetic variation in a gene-specific manner for the detection of regulatory elements (REMs) without relying on peak calls in individual samples. StitchIt segments epigenetic signal tracks over many samples to generate the location and the target genes of a REM simultaneously. We show that this approach leads to a more accurate and refined REM detection compared to standard methods even on heterogeneous datasets, which are challenging to model. Also, StitchIt REMs are highly enriched in experimentally determined chromatin interactions and expression quantitative trait loci. We validated several newly predicted REMs using CRISPR-Cas9 experiments, thereby demonstrating the reliability of StitchIt. StitchIt is able to dissect regulation in superenhancers and predicts thousands of putative REMs that go unnoticed using peak-based approaches suggesting that a large part of the regulome might be uncharted water.

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Metadaten
Author:Florian SchmidtORCiD, Alexander MarxORCiD, Nina BaumgartenORCiDGND, Marie Hebel, Martin WegnerORCiD, Manuel KaulichORCiD, Matthias LeisegangORCiDGND, Ralf BrandesORCiDGND, Jonathan GökeORCiDGND, Jilles VreekenORCiD, Marcel Holger SchulzORCiDGND
URN:urn:nbn:de:hebis:30:3-734293
DOI:https://doi.org/10.1093/nar/gkab798
ISSN:0305-1048
Pubmed Id:https://pubmed.ncbi.nlm.nih.gov/34508352
Parent Title (English):Nucleic Acids Research
Publisher:Oxford Univ. Press
Place of publication:Oxford
Document Type:Article
Language:English
Date of Publication (online):2021/09/11
Date of first Publication:2021/09/11
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2024/08/09
Volume:49
Issue:18
Page Number:22
First Page:10397
Last Page:10418
HeBIS-PPN:521813190
Institutes:Medizin
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Sammlungen:Universitätspublikationen
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International