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Lookup NU author(s): Dr Daniel Rico RodriguezORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Introns can be extraordinarily large and they account for the majority of the DNA sequence in human genes. However, little is known about their population patterns of structural variation and their functional implication. By combining the most extensive maps of CNVs in human populations, we have found that intronic losses are the most frequent copy number variants (CNVs) in protein-coding genes in human, with 12,986 intronic deletions, affecting 4,147 genes (including 1,154 essential genes and 1,638 disease-related genes). This intronic length variation results in dozens of genes showing extreme population variability in size, with 40 genes with 10 or more different sizes and up to 150 allelic sizes. Intronic losses are frequent in evolutionarily ancient genes that are highly conserved at the protein sequence level. This result contrasts with losses overlapping exons, which are observed less often than expected by chance and almost exclusively affect primate-specific genes. An integrated analysis of CNVs and RNA-seq data showed that intronic loss can be associated with significant differences in gene expression levels in the population (CNV-eQTLs). These intronic CNV-eQTLs regions are enriched for intronic enhancers and can be associated with expression differences of other genes showing long distance intron-promoter 3D interactions. Our data suggests that intronic structural variation of protein-coding genes makes an important contribution to the variability of gene expression and splicing in human populations.
Author(s): Rigau M, Juan D, Valencia A, Rico D
Publication type: Article
Publication status: Published
Journal: PLoS Genetics
Year: 2019
Volume: 15
Issue: 1
Online publication date: 24/01/2019
Acceptance date: 17/12/2018
Date deposited: 02/12/2019
ISSN (print): 1553-7390
ISSN (electronic): 1553-7404
Publisher: Public Library of Science
URL: https://doi.org/10.1371/journal.pgen.1007902
DOI: 10.1371/journal.pgen.1007902
PubMed id: 30677042
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