A probabilistic generative model for quantification of DNA modifications enables analysis of demethylation pathways

Tarmo Äijö, Yun Huang, Henrik Mannerström, Lukas Chavez, Ageliki Tsagaratou, Anjana Rao*, Harri Lähdesmäki

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

11 Citations (Scopus)
183 Downloads (Pure)

Abstract

We present a generative model, Lux, to quantify DNA methylation modifications from any combination of bisulfite sequencing approaches, including reduced, oxidative, TET-assisted, chemical-modification assisted, and methylase-assisted bisulfite sequencing data. Lux models all cytosine modifications (C, 5mC, 5hmC, 5fC, and 5caC) simultaneously together with experimental parameters, including bisulfite conversion and oxidation efficiencies, as well as various chemical labeling and protection steps. We show that Lux improves the quantification and comparison of cytosine modification levels and that Lux can process any oxidized methylcytosine sequencing data sets to quantify all cytosine modifications. Analysis of targeted data from Tet2-knockdown embryonic stem cells and T cells during development demonstrates DNA modification quantification at unprecedented detail, quantifies active demethylation pathways and reveals 5hmC localization in putative regulatory regions.

Original languageEnglish
Article number49
Pages (from-to)1-22
JournalGENOME BIOLOGY
Volume17
Issue number1
DOIs
Publication statusPublished - 14 Mar 2016
MoE publication typeA1 Journal article-refereed

Keywords

  • 5-methylcytosine oxidation
  • Bayesian analysis
  • Bisulfite sequencing
  • BS-seq/oxBS-seq/TAB-seq/fCAB-seq/CAB-seq/redBS-seq/MAB-seq
  • DNA methylation
  • Hierarchical modeling
  • TET proteins

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