ArticleBriefings in bioinformatics2021
A new approach to decode DNA methylome and genomic variants simultaneously from double strand bisulfite sequencing.
Article in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 11 citations in OpenAlex.
- Methylation array signals are predictive of chronological age without bisulfite conversion.GeroScience · 2026Article
- Fast and efficient method for parallel construction of targeted exome and methylome single-stranded DNA sequencing libraries.Scientific reports · 2025Article
- Simultaneous assessment of human genome and methylome data in a single experiment using limited deamination of methylated cytosine.Genome research · 2024Article
- bsgenova: an accurate, robust, and fast genotype caller for bisulfite-sequencing data.BMC bioinformatics · 2024Article
- Methyl-SNP-seq reveals dual readouts of methylome and variome at molecule resolution while enabling target enrichment.Genome researchArticle
Corrections and comments
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Authors and funding
9 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genetic and epigenetic contributions to various diseases and biological processes have been well-recognized. However, simultaneous identification of single-nucleotide variants (SNVs) and DNA methylation levels from traditional bisulfite sequencing data is still challenging. Here, we develop double strand bisulfite sequencing (DSBS) for genome-wide accurate identification of SNVs and DNA methylation simultaneously at a single-base resolution by using one dataset. Locking Watson and Crick strand together by hairpin adapter followed by bisulfite treatment and massive parallel sequencing, DSBS simultaneously sequences the bisulfite-converted Watson and Crick strand in one paired-end read, eliminating the strand bias of bisulfite sequencing data. Mutual correction of read1 and read2 can estimate the amplification and sequencing errors, and enables our developed computational pipeline, DSBS Analyzer (https://github.com/tianguolangzi/DSBS), to accurately identify SNV and DNA methylation. Additionally, using DSBS, we provide a genome-wide hemimethylation landscape in the human cells, and reveal that the density of DNA hemimethylation sites in promoter region and CpG island is lower than that in other genomic regions. The cost-effective new approach, which decodes DNA methylome and genomic variants simultaneously, will facilitate more comprehensive studies on numerous diseases and biological processes driven by both genetic and epigenetic variations.
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