ArticleGenome biology2020
Identification of cell type-specific methylation signals in bulk whole genome bisulfite sequencing data.
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 21 papers.
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Who cites it
21 citing papers in PubMed.
- Uncovering alterations in cancer epigenetics via trans-dimensional Markov chain Monte Carlo and hidden Markov models.Journal of the Royal Statistical Society. Series C, Applied statistics · 2026Article
- MPCI: A novel metric for quantifying DNA methylation patterns in NGS data.PLoS computational biology · 2026Article
- Conserved DNA methylation signatures in the prefrontal cortex of female newborn and juvenile guinea pigs following antenatal betamethasone exposure.Journal of neuroendocrinology · 2025Article
- The response to influenza vaccination is associated with DNA methylation-driven regulation of T cell innate antiviral pathways.Clinical epigenetics · 2024Article
- Systemic interindividual DNA methylation variants in cattle share major hallmarks with those in humans.Genome biology · 2024Article
- The response to influenza vaccination is associated with DNA methylation-driven regulation of T cell innate antiviral pathways.Research square · 2024Article
- Computational deconvolution of DNA methylation data from mixed DNA samples.Briefings in bioinformatics · 2024Review
- Challenges and perspectives in computational deconvolution of genomics data.Nature methods · 2024Review
- Alterations to DNA methylation patterns induced by chemotherapy treatment are associated with negative impacts on the olfactory pathway.Breast cancer research : BCR · 2023Article
- Article
- Methylome Imputation by Methylation Patterns.Methods in molecular biology (Clifton, N.J.) · 2023Article
- A machine learning approach utilizing DNA methylation as an accurate classifier of COVID-19 disease severity.Scientific reports · 2022Article
- Sex-specific epigenetic development in the mouse hypothalamic arcuate nucleus pinpoints human genomic regions associated with body mass index.Science advances · 2022Article
- Systematic evaluation of cell-type deconvolution pipelines for sequencing-based bulk DNA methylomes.Briefings in bioinformatics · 2022Article
- Age and sex effects on DNA methylation sites linked to genes implicated in severe COVID-19 and SARS-CoV-2 host cell entry.PloS one · 2022Article
- BSImp: Imputing Partially Observed Methylation Patterns for Evaluating Methylation Heterogeneity.Frontiers in bioinformatics · 2022Review
- Low variability in the underlying cellular landscape adversely affects the performance of interaction-based approaches for conducting cell-specific analyses of DNA methylation in bulk samples.Statistical applications in genetics and molecular biology · 2021Article
- Analyzing Modern Biomolecules: The Revolution of Nucleic-Acid Sequencing - Review.Biomolecules · 2021Review
- Introduction to Single-Cell DNA Methylation Profiling Methods.Biomolecules · 2021Review
- Investigating Different DNA Methylation Patterns at the Resolution of Methylation Haplotypes.Frontiers in genetics · 2021Article
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8 authors.
Funding
Abstract
backgroundThe traditional approach to studying the epigenetic mechanism CpG methylation in tissue samples is to identify regions of concordant differential methylation spanning multiple CpG sites (differentially methylated regions). Variation limited to single or small numbers of CpGs has been assumed to reflect stochastic processes. To test this, we developed software, Cluster-Based analysis of CpG methylation (CluBCpG), and explored variation in read-level CpG methylation patterns in whole genome bisulfite sequencing data.
resultsAnalysis of both human and mouse whole genome bisulfite sequencing datasets reveals read-level signatures associated with cell type and cell type-specific biological processes. These signatures, which are mostly orthogonal to classical differentially methylated regions, are enriched at cell type-specific enhancers and allow estimation of proportional cell composition in synthetic mixtures and improved prediction of gene expression. In tandem, we developed a machine learning algorithm, Precise Read-Level Imputation of Methylation (PReLIM), to increase coverage of existing whole genome bisulfite sequencing datasets by imputing CpG methylation states on individual sequencing reads. PReLIM both improves CluBCpG coverage and performance and enables identification of novel differentially methylated regions, which we independently validate.
conclusionsOur data indicate that, rather than stochastic variation, read-level CpG methylation patterns in tissue whole genome bisulfite sequencing libraries reflect cell type. Accordingly, these new computational tools should lead to an improved understanding of epigenetic regulation by DNA methylation.
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