Expression Quantitative Trait Loci (eQTLs) Associated with Retrotransposons Demonstrate their Modulatory Effect on the Transcriptome

Author:

Koks SulevORCID,Pfaff Abigail L.ORCID,Bubb Vivien J.ORCID,Quinn John P.ORCID

Abstract

Transposable elements (TEs) are repetitive elements that belong to a variety of functional classes and have an important role in shaping genome evolution. Around 50% of the human genome contains TEs, and they have been termed the “dark matter” of the genome because relatively little is known about their function. While TEs have been shown to participate in aberrant gene regulation and the pathogenesis of diseases, only a few studies have explored the systemic effect of TEs on gene expression. In the present study, we analysed whole genome sequences and blood whole transcriptome data from 570 individuals within the Parkinson’s Progressive Markers Initiative (PPMI) cohort to identify expression quantitative trait loci (eQTL) regulating genome-wide gene expression associated with TEs. We identified 2132 reference TEs that were polymorphic for their presence or absence in our study cohort. The presence or absence of the TE element could change the expression of the gene or gene clusters from zero to tens of thousands of copies of RNA. The main finding is that many TEs possess very strong regulatory effects, and they have the potential to modulate large genetic networks with hundreds of target genes over the genome. We illustrate the plethora of regulatory mechanisms using examples of their action at the HLA gene cluster and data showing different TEs’ convergence to modulate WFS1 gene expression. In conclusion, the presence or absence of polymorphisms of TEs has an eminent genome-wide regulatory function with large effect size at the level of the whole transcriptome. The role of TEs in explaining, in part, the missing heritability for complex traits is convincing and should be considered.

Publisher

MDPI AG

Subject

Inorganic Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Computer Science Applications,Spectroscopy,Molecular Biology,General Medicine,Catalysis

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