medRxivGenetic & Genomic MedicinePreprint
Long-read sequencing reveals novel isoform-specific eQTLs and regulatory mechanisms of isoform expression
Yuya Nagura, Mihoko ShimadaiD, Ryoji Kuribayashi, Hiroki Kiyose, Arisa IgarashiiD, Tadashi KanameiD, Motoko UnokiiD, Akihiro FujimotoiD
Abstract
Genetic variations linked to changes in gene expression are known as expression quantitative loci (eQTLs). The identification of eQTLs provides a profound understanding of the mechanisms governing gene expression. However, prior studies have primarily utilized short-read sequencing techniques, and the analysis of eQTLs on isoforms has been relatively limited. In this study, we employed long-read sequencing technology (Oxford Nanopore) on B cells from 67 healthy Japanese individuals to explore genetic variations associated with isoform expression levels, referred to as isoform eQTLs (ieQTLs). Our analysis revealed 33,928 ieQTLs, with 69.0% remaining undetected by a gene-level analysis. Additionally, we identified ieQTLs that have significantly different effects on isoform expression levels within a gene. A functional feature analysis demonstrated a significant enrichment of ieQTLs at splice sites and specific histone marks, such as H3K36me3, H3K4me1, H3K4me3, and H3K79me3. Through an experimental validation using genome editing, we observed that a distant genomic region can modulate isoform-specific expression. Moreover, an ieQTL analysis and minigene splicing assays unveiled functionally crucial variants in splicing, which software-based predictions failed to anticipate. A comparison with GWAS data revealed a higher number of colocalizations between ieQTLs and GWAS findings compared to gene eQTLs. These findings highlight the substantial contribution of ieQTLs identified through long-read analysis in our understanding of the functional implications of genetic variations and the regulatory mechanisms governing isoforms.
- organism: human
- assay: long-read sequencing
- research focus: eQTL / molecular QTL mapping
- approach: statistical model
- Citations
- 1
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