Systematic benchmarking of tools for CpG methylation detection from nanopore sequencing

Abstract

DNA methylation plays a fundamental role in the control of gene expression and genome integrity. Although there are multiple tools that enable its detection from Nanopore sequencing, their accuracy remains largely unknown. Here, we present a systematic benchmarking of tools for the detection of CpG methylation from Nanopore sequencing using individual reads, control mixtures of methylated and unmethylated reads, and bisulfite sequencing. We found that tools have a tradeoff between false positives and false negatives and present a high dispersion with respect to the expected methylation frequency values. We described various strategies to improve the accuracy of these tools, including a consensus approach, METEORE (https://github.com/comprna/METEORE), based on the combination of the predictions from two or more tools that shows improved accuracy over individual tools. Snakemake pipelines are also provided for reproducibility and to enable the systematic application of our analyses to other datasets.

Nanopore Single-Molecule Sequencing for Mitochondrial DNA Methylation Analysis: Investigating Parkin-Associated Parkinsonism as a Proof of Concept

“…Additionally, the training strategy and the data sets themselves used to train these tools could contribute to the lower per-site concordance. A recent benchmark study investigated the strength and limitations of the widest used state-of-the-art tools to detect CpG methylation from Nanopore sequencing data, including Megalodon and Nanopolish (Yuen et al, 2021 ). The results from Megalodon were found to be more consistent with whole-genome bisulfite sequencing data compared to Nanopolish.…”

DNA methylation-calling tools for Oxford Nanopore sequencing: a survey and human epigenome-wide evaluation

“…Specifically, the electric current patterns, also known as "squiggles," resulting from the passage of modified bases through the pores differs from the patterns produced by the passage of unmodified bases [26,30]. The difference can be determined after nanopore read basecalling and alignment by (1) statistical tests comparing the electric current pattern to an in silico reference or the pattern from a nonmodified control sample [20,31]; (2) pre-trained supervised learning models, e.g., neural network [23,[32][33][34][35][36][37], machine learning model [38], and Hidden Markov Models (HMM) [9,39]. However, DNA-methylation detection using nanopore sequencing presents a methodological challenge, i.e., the capacity to detect modifications in different CpGs that are in close proximity to one another on a DNA fragment (i.e., nonsingleton), as it is assumed that all CpGs within a 10-bp region share the same methylation status.…”

“…However, DNA-methylation detection using nanopore sequencing presents a methodological challenge, i.e., the capacity to detect modifications in different CpGs that are in close proximity to one another on a DNA fragment (i.e., nonsingleton), as it is assumed that all CpGs within a 10-bp region share the same methylation status. Twelve methylation-calling tools have been developed for various DNA modifications (e.g., 4mC, 5mC, 5hmC, and 6 mA) and for different nanopore pore versions (e.g., R7, R9, and R10) (Table 1 [9,20,23,[31][32][33][34][35][36][37][38][39]), but DNA-methylation detection for non-singletons containing both methylated and unmethylated CpGs remains difficult [9,35]. Moreover, DNA methylation levels are not linearly distributed across the genome, and CpG density is dependent on genomic context [40][41][42].…”

Precise Characterization of Bombyx mori Fibroin Heavy Chain Gene Using Cpf1-Based Enrichment and Oxford Nanopore Technologies

“…Since FibH is long and contains many repeat units, the classic bisulfite method cannot detect methylation, and hence, there is no report on FibH methylation in B. mori . ONT not only has a long read length, but can also recognize modified bases, which is widely used to study base modifications in the genome [ 22 , 60 , 61 , 62 , 63 ]. To identify the presence of base modifications on FibH , we performed a methylation analysis on the sequencing data obtained by CEO using Nanopolish.…”

“…Since the invention of Sanger sequencing in 1977, new sequencing technologies have emerged. Third-generation sequencing not only allows long-read lengths but also provides more information on DNA methylation and is therefore preferred by researchers over other techniques [ 19 , 20 , 21 , 22 ]. Third-generation sequencing includes two sequencing platforms, PacBio (PB) and Oxford Nanopore Technologies (ONT).…”