ArticleBMC genomics2018
METHimpute: imputation-guided construction of complete methylomes from WGBS data.
Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Mapping genetic modifiers of epimutation rates identifies VIM2/4 as dosage-sensitive negative regulators of CG methylation maintenance.Nature plants · 2026Article
- Convergence and divergence of DNA methylation and gene expression patterns in neopolyploid Arabidopsis kamchatica.Nature communications · 2026Article
- slideimp: efficient imputation of DNA methylation data.Bioinformatics (Oxford, England) · 2026Article
- Epigenetic biomarkers in inflammatory bowel diseases-computational challenges and opportunities.Journal of Crohn's & colitis · 2026Review
- Centromeres are hotspots of cytosine methylation epimutations in a filamentous fungus.bioRxiv : the preprint server for biology · 2026Article
- Integrative methylome and transcriptome analysis reveals genotype and sequence context-specific responses to aluminum stress in rice.Frontiers in plant science · 2026Article
- Nanorate sequencing reveals theProceedings of the National Academy of Sciences of the United States of America · 2025Article
- Accelerated growth increases the somatic epimutation rate in trees.Nature communications · 2025Article
- Methylomes Reveal Recent Evolutionary Changes in Populations of Two Plant Species.Genome biology and evolution · 2025Article
- DNA methylation in breast cancer: early detection and biomarker discovery through current and emerging approaches.Journal of translational medicine · 2025Review
- Article
- Epigenetic variation in early and late flowering plants of the rubber-producing Russian dandelion Taraxacum koksaghyz provides insights into the regulation of flowering time.Scientific reports · 2024Article
- Warmer temperature during asexual reproduction induce methylome, transcriptomic, and lasting phenotypic changes inHorticulture research · 2023Article
- Recall DNA methylation levels at low coverage sites using a CNN model in WGBS.PLoS computational biology · 2023Article
- Computational Methods for Single-cell DNA Methylome Analysis.Genomics, proteomics & bioinformatics · 2023Review
- Methylome Imputation by Methylation Patterns.Methods in molecular biology (Clifton, N.J.) · 2023Article
- The DNA dioxygenase Tet1 regulates H3K27 modification and embryonic stem cell biology independent of its catalytic activity.Nucleic acids research · 2022Article
- Molecular properties of epimutation hotspots.Nature plants · 2022Article
- BSImp: Imputing Partially Observed Methylation Patterns for Evaluating Methylation Heterogeneity.Frontiers in bioinformatics · 2022Review
- Heterochromatin is a quantitative trait associated with spontaneous epiallele formation.Nature communications · 2021Article
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Authors and funding
6 authors.
Funding
Abstract
backgroundWhole-genome bisulfite sequencing (WGBS) has become the standard method for interrogating plant methylomes at base resolution. However, deep WGBS measurements remain cost prohibitive for large, complex genomes and for population-level studies. As a result, most published plant methylomes are sequenced far below saturation, with a large proportion of cytosines having either missing data or insufficient coverage.
resultsHere we present METHimpute, a Hidden Markov Model (HMM) based imputation algorithm for the analysis of WGBS data. Unlike existing methods, METHimpute enables the construction of complete methylomes by inferring the methylation status and level of all cytosines in the genome regardless of coverage. Application of METHimpute to maize, rice and Arabidopsis shows that the algorithm infers cytosine-resolution methylomes with high accuracy from data as low as 6X, compared to data with 60X, thus making it a cost-effective solution for large-scale studies.
conclusionsMETHimpute provides methylation status calls and levels for all cytosines in the genome regardless of coverage, thus yielding complete methylomes even with low-coverage WGBS datasets. The method has been extensively tested in plants, but should also be applicable to other species. An implementation is available on Bioconductor.
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