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

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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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2016-03-14

Department

Tietojenkäsittelytieteen laito
Department of Computer Science

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Language

en

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Genome Biology, Volume 17, issue 1, pp. 1-22

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.

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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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DOI

10.1186/s13059-016-0911-6

Citation

Äijö, T, Huang, Y, Mannerström, H, Chavez, L, Tsagaratou, A, Rao, A & Lähdesmäki, H 2016, 'A probabilistic generative model for quantification of DNA modifications enables analysis of demethylation pathways', Genome Biology, vol. 17, no. 1, 49, pp. 1-22. https://doi.org/10.1186/s13059-016-0911-6

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https://urn.fi/URN:NBN:fi:aalto-201705114047

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[article-cris] Perustieteiden korkeakoulu / SCI