Back to Search Start Over

A hidden layer of structural variation in transposable elements reveals potential genetic modifiers in human disease-risk loci

Authors :
van Bree, Elisabeth J. (author)
Guimarães, Rita L.F.P. (author)
Lundberg, Mischa (author)
Blujdea, Elena R. (author)
Rosenkrantz, Jimi L. (author)
White, Fred T.G. (author)
Reinders, M.J.T. (author)
Holstege, H. (author)
Jacobs, Frank M.J. (author)
van Bree, Elisabeth J. (author)
Guimarães, Rita L.F.P. (author)
Lundberg, Mischa (author)
Blujdea, Elena R. (author)
Rosenkrantz, Jimi L. (author)
White, Fred T.G. (author)
Reinders, M.J.T. (author)
Holstege, H. (author)
Jacobs, Frank M.J. (author)
Publication Year :
2022

Abstract

Genome-wide association studies (GWAS) have been highly informative in discovering disease-associated loci but are not designed to capture all structural variations in the human genome. Using long-read sequencing data, we discovered widespread structural variation within SINE-VNTR-Alu (SVA) elements, a class of great ape-specific transposable elements with gene-regulatory roles, which represents a major source of structural variability in the human population. We highlight the presence of structurally variable SVAs (SV-SVAs) in neurological disease-associated loci, and we further associate SV-SVAs to disease-associated SNPs and differential gene expression using luciferase assays and expression quantitative trait loci data. Finally, we genetically deleted SV-SVAs in the BIN1 and CD2AP Alzheimer's disease-associated risk loci and in the BCKDK Parkinson's disease-associated risk locus and assessed multiple aspects of their gene-regulatory influence in a human neuronal context. Together, this study reveals a novel layer of genetic variation in transposable elements that may contribute to identification of the structural variants that are the actual drivers of disease associations of GWAS loci.<br />Pattern Recognition and Bioinformatics<br />Intelligent Systems

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1327983415
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.1101.gr.275515.121