Large-scale methylation studies using nanopore sequencing

Abstract We demonstrate that CpG methylation detection from 7,179 nanopore-sequenced DNA samples is highly accurate and consistent with 132 oxidative bisulfite-sequenced samples, isolated from the same blood draws. We introduce quality filters for CpGs that further enhance the accuracy of the methylation detection from nanopore-sequenced DNA. Using haplotype-specific methylation rates of 15.3 million high-quality CpG units, we identify 189,178 methylation-depleted sequences. A total of 77,789 methylation-depleted sequences (~41%) were associated with 80,503 cis-acting sequence variants, which we termed allele-specific methylation quantitative trait loci (ASM-QTLs). RNA sequencing of 896 samples from the same blood draws used to perform nanopore sequencing showed that the ASM-QTL, that is, DNA sequence variability, drives most of the correlation found between gene expression and CpG methylation. ASM-QTLs were among sequence variants associated with hematological traits, demonstrating that ASM-QTLs are important functional units in the non-coding genome. Biography Brynja Sigurpálsdóttir is a research scientist at deCODE genetics (a subsidiary of Amgen), concurrently pursuing a PhD at Reykjavík University. Brynja’s academic journey began with a BSc in Biomedical Engineering from Reykjavík University, during which she undertook an internship with deCODE genetics, Iceland. In 2019, Brynja completed an MSc in Bioinformatics from ETH, Zürich, with her thesis on defining the methylation patterns of Kabuki and Wiederman-Steiner syndromes using nanopore sequencing data.