Disentangling genetic effects on transcriptional and post-transcriptional gene regulation through integrating exon and intron expression QTLs.

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Version: Final published version
License: CC BY 4.0
Serval ID
serval:BIB_D3A95CE7F2D1
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Disentangling genetic effects on transcriptional and post-transcriptional gene regulation through integrating exon and intron expression QTLs.
Journal
Nature communications
Author(s)
Brümmer A., Bergmann S.
ISSN
2041-1723 (Electronic)
ISSN-L
2041-1723
Publication state
Published
Issued date
06/05/2024
Peer-reviewed
Oui
Volume
15
Number
1
Pages
3786
Language
english
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't
Publication Status: epublish
Abstract
Expression quantitative trait loci (eQTL) studies typically consider exon expression of genes and discard intronic RNA sequencing reads despite their information on RNA metabolism. Here, we quantify genetic effects on exon and intron levels of genes and their ratio in lymphoblastoid cell lines, revealing thousands of cis-QTLs of each type. While genetic effects are often shared between cis-QTL types, 7814 (47%) are not detected as top cis-QTLs at exon levels. We show that exon levels preferentially capture genetic effects on transcriptional regulation, while exon-intron-ratios better detect those on co- and post-transcriptional processes. Considering all cis-QTL types substantially increases (by 71%) the number of colocalizing variants identified by genome-wide association studies (GWAS). It further allows dissecting the potential gene regulatory processes underlying GWAS associations, suggesting comparable contributions by transcriptional (50%) and co- and post-transcriptional regulation (46%) to complex traits. Overall, integrating intronic RNA sequencing reads in eQTL studies expands our understanding of genetic effects on gene regulatory processes.
Keywords
Quantitative Trait Loci, Humans, Introns/genetics, Exons/genetics, Genome-Wide Association Study, Gene Expression Regulation, Transcription, Genetic, Cell Line, Sequence Analysis, RNA/methods, Polymorphism, Single Nucleotide
Pubmed
Open Access
Yes
Create date
10/05/2024 13:37
Last modification date
11/05/2024 8:07
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