4.7 Article

Long reads capture simultaneous enhancer-promoter methylation status for cell-type deconvolution

期刊

BIOINFORMATICS
卷 37, 期 -, 页码 I327-I333

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OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btab306

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资金

  1. European Research Council Consolidator grant [817811]
  2. NIH National Center for Advancing Translational Sciences [UL1TR001876]
  3. NIH National Human Genome Research Institute [R21HG011424]
  4. Israel Science Foundation [715/18]

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This study explored the methylation status of enhancer-promoter pairs using long-read optical methylome data, and developed various analysis approaches for deconvolving cell-type mixtures. Results showed that these pairs can be used for detecting rare cancerous transformations in a given cell population, with accurate estimates obtained through promoter methylation and enhancer-promoter pairwise methylation analysis. Additionally, the analysis can be applied to resolve different cell populations of the same cell type in subtle scenarios.
Motivation: While promoter methylation is associated with reinforcing fundamental tissue identities, the methylation status of distant enhancers was shown by genome-wide association studies to be a powerful determinant of cell-state and cancer. With recent availability of long reads that report on the methylation status of enhancer-promoter pairs on the same molecule, we hypothesized that probing these pairs on the single-molecule level may serve the basis for detection of rare cancerous transformations in a given cell population. We explore various analysis approaches for deconvolving cell-type mixtures based on their genome-wide enhancer-promoter methylation profiles. Results: To evaluate our hypothesis we examine long-read optical methylome data for the GM12878 cell line and myoblast cell lines from two donors. We identified over 100 000 enhancer-promoter pairs that co-exist on at least 30 individual DNA molecules. We developed a detailed methodology for mixture deconvolution and applied it to estimate the proportional cell compositions in synthetic mixtures. Analysis of promoter methylation, as well as enhancer-promoter pairwise methylation, resulted in very accurate estimates. In addition, we show that pairwise methylation analysis can be generalized from deconvolving different cell types to subtle scenarios where one wishes to resolve different cell populations of the same cell-type.

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