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Genome Biol. 2016 Mar 14;17:49. doi: 10.1186/s13059-016-0911-6.

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

Author information

1
Department of Computer Science, Aalto University School of Science, Aalto, FI-00076, Finland.
2
Present address: Simons Center for Data Analysis, Simons Foundation, New York, NY, 10010, USA.
3
La Jolla Institute for Allergy and Immunology, La Jolla, CA, 92037, USA.
4
Sanford Consortium for Regenerative Medicine, La Jolla, CA, 92037, USA.
5
Present address: Institute of Biosciences & Technology, Texas A&M University Health Science Center, 2121 W. Holcombe Blvd, Houston, TX, 77030, USA.
6
Present address: Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, 69120, Germany.
7
La Jolla Institute for Allergy and Immunology, La Jolla, CA, 92037, USA. arao@liai.org.
8
Sanford Consortium for Regenerative Medicine, La Jolla, CA, 92037, USA. arao@liai.org.
9
Department of Pharmacology and Moores Cancer Center, University of California, La Jolla, CA, 92037, USA. arao@liai.org.
10
Department of Signaling and Gene Expression, La Jolla Institute for Allergy and Immunology, 9420 Athena Circle, San Diego, CA, 92037, USA. arao@liai.org.
11
Department of Computer Science, Aalto University School of Science, Aalto, FI-00076, Finland. harri.lahdesmaki@aalto.fi.
12
Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Turku, FI-20520, Finland. harri.lahdesmaki@aalto.fi.

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.

KEYWORDS:

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

PMID:
26975309
PMCID:
PMC4792102
DOI:
10.1186/s13059-016-0911-6
[Indexed for MEDLINE]
Free PMC Article

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