ArticleGenome biology2020
Contiguous and stochastic CHH methylation patterns of plant DRM2 and CMT2 revealed by single-read methylome analysis.
Article in Genome biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Article
- Homeostasis of DNA Hemi-Methylation in Arabidopsis through Methylation Maintenance, DNA Replication, and Nucleosome Positioning Mechanisms.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Reprogramming of DNA methylation and changes of gene expression in graftedFrontiers in plant science · 2024Article
- Estimating genome-wide DNA methylation heterogeneity with methylation patterns.Epigenetics & chromatin · 2023Article
- The chromatin determinants and Ph1 gene effect at wheat sites with contrasting recombination frequency.Journal of advanced research · 2023Article
- On the prediction of non-CG DNA methylation using machine learning.NAR genomics and bioinformatics · 2023Article
- Re-analysis of publicly available methylomes using signal detection yields new information.Scientific reports · 2023Article
- Unravelling Differential DNA Methylation Patterns in Genotype Dependent Manner under Salinity Stress Response in Chickpea.International journal of molecular sciences · 2023Article
- Methylome Imputation by Methylation Patterns.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Identification of Putative Markers of Non-infectious Bud Failure in Almond [Frontiers in plant science · 2022Article
- BSImp: Imputing Partially Observed Methylation Patterns for Evaluating Methylation Heterogeneity.Frontiers in bioinformatics · 2022Review
- Grafting vigour is associated with DNA de-methylation in eggplant.Horticulture research · 2021Article
- Perspectives for epigenetic editing in crops.Transgenic research · 2021Review
- DNA methylation mutants inProceedings of the National Academy of Sciences of the United States of America · 2020Article
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Authors and funding
2 authors.
Funding
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Abstract
Cytosine methylome data is commonly generated through next-generation sequencing, with analyses averaging methylation states of individual reads. We propose an alternative method of analysing single-read methylome data. Using this method, we identify patterns relating to the mechanism of two plant non-CG-methylating enzymes, CMT2 and DRM2. CMT2-methylated regions show higher stochasticity, while DRM2-methylated regions have higher variation among cells. Based on these patterns, we develop a classifier that predicts enzyme activity in different species and tissues. To facilitate further single-read analyses, we develop a genome browser, SRBrowse, optimised for visualising and analysing sequencing data at single-read resolution.
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