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Abstract Long single-molecular sequencing technologies, such as PacBio circular consensus sequencing (CCS) and nanopore sequencing, are advantageous in detecting DNA 5-methylcytosine in CpGs (5mCpGs), especially in repetitive genomic regions. However, existing methods for detecting 5mCpGs using PacBio CCS are less accurate and robust. Here, we present ccsmeth, a deep-learning method to detect DNA 5mCpGs using CCS reads. We sequence polymerase-chain-reaction treated and M.SssI-methyltransferase treated DNA of one human sample using PacBio CCS for training ccsmeth. Using long (≥10 Kb) CCS reads, ccsmeth achieves 0.90 accuracy and 0.97 Area Under the Curve on 5mCpG detection at single-molecule resolution. At the genome-wide site level, ccsmeth achieves >0.90 correlations with bisulfite sequencing and nanopore sequencing using only 10× reads. Furthermore, we develop a Nextflow pipeline, ccsmethphase, to detect haplotype-aware methylation using CCS reads, and then sequence a Chinese family trio to validate it. ccsmeth and ccsmethphase can be robust and accurate tools for detecting DNA 5-methylcytosines.
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This content will become publicly available on March 1, 2026
SMAC: identifying DNA N6-methyladenine (6mA) at the single-molecule level using SMRT CCS data
Abstract DNA modifications, such as N6-methyladenine (6mA), play important roles in various processes in eukaryotes. Single-molecule, real-time (SMRT) sequencing enables the direct detection of DNA modifications without requiring special sample preparation. However, most SMRT-based studies of 6mA rely on ensemble-level consensus by combining multiple reads covering the same genomic position, which misses the single-molecule heterogeneity. While recent methods have aimed at single-molecule level detection of 6mA, limitations in sequencing platforms, resolution, accuracy, and usability restrict their application in comprehensive epigenetic studies. Here, we present SMAC (single-molecule 6mA analysis of CCS reads), a novel framework for accurately detecting 6mA at the single-molecule level using SMRT circular consensus sequencing (CCS) data from the Sequel II system. It is an automated method that streamlines the entire workflow by packaging both existing softwares and built-in scripts, with user-defined parameters to allow easy adaptation for various studies. By utilizing the statistical distribution characteristics of enzyme kinetic indicators on single DNA molecules rather than a fixed cutoff, SMAC significantly improves 6mA detection accuracy at the single-nucleotide and single-molecule levels. It simplifies analysis by providing comprehensive information, including quality control, statistical analysis, and site visualization, directly from raw sequencing data. SMAC is a powerful new tool that enables de novo detection of 6mA and empowers investigation of its functions in modulating physiological processes.
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- Award ID(s):
- 2435178
- PAR ID:
- 10653713
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Briefings in Bioinformatics
- Volume:
- 26
- Issue:
- 2
- ISSN:
- 1467-5463
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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