A probabilistic generative model for quantification of DNA modifications enables analysis of demethylation pathways
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE68576 | GEO | 2016/01/01
SECONDARY ACCESSION(S): PRJNA283126
REPOSITORIES: GEO
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Project description: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.
| S-EPMC4792102 | biostudies-literature
Project description:To characterize the largely unknown functions of oxidised methylcytosines (oxi-mC; 5hmC/5fC/5caC) in DNA, several sequencing protocols have been recently developed. Quantitative analysis is complicated because DNA methylation modifications need to be deconvoluted from the data which is affected by several experimental parameters, including e.g. imperfect bisulphite conversion, oxidation efficiencies, various chemical labeling and protection steps, and sequencing errors. Here, we present a hierarchical generative model, Lux, for integrative analysis of any combination of BS-seq and “oxi-mC”-seq (BS-seq/oxBS-seq/TAB-seq/fCAB-seq/CAB-seq/redBS-seq/MAB-seq) data. We show that Lux improves quantification and comparison of methylation levels over existing methods and that Lux can easily process any oxi-mC-seq data sets to quantify all cytosine modifications simultaneously together with their experimental parameters. Application of Lux to targeted data from Tet2 knockdown ESCs and T cells during development demonstrates DNA modification quantification at unprecedented detail, quantifies active demethylation pathway and reveals 5hmC localization in putative regulatory regions.
2016-01-01 | GSE68574 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2016-07-03 | E-GEOD-68576 | biostudies-arrayexpress
Project description:To characterize the largely unknown functions of oxidised methylcytosines (oxi-mC; 5hmC/5fC/5caC) in DNA, several sequencing protocols have been recently developed. Quantitative analysis is complicated because DNA methylation modifications need to be deconvoluted from the data which is affected by several experimental parameters, including e.g. imperfect bisulphite conversion, oxidation efficiencies, various chemical labeling and protection steps, and sequencing errors. Here, we present a hierarchical generative model, Lux, for integrative analysis of any combination of BS-seq and “oxi-mC”-seq (BS-seq/oxBS-seq/TAB-seq/fCAB-seq/CAB-seq/redBS-seq/MAB-seq) data. We show that Lux improves quantification and comparison of methylation levels over existing methods and that Lux can easily process any oxi-mC-seq data sets to quantify all cytosine modifications simultaneously together with their experimental parameters. Application of Lux to targeted data from Tet2 knockdown ESCs and T cells during development demonstrates DNA modification quantification at unprecedented detail, quantifies active demethylation pathway and reveals 5hmC localization in putative regulatory regions.
2016-01-01 | GSE68575 | GEO
Project description:To characterize the largely unknown functions of oxidised methylcytosines (oxi-mC; 5hmC/5fC/5caC) in DNA, several sequencing protocols have been recently developed. Quantitative analysis is complicated because DNA methylation modifications need to be deconvoluted from the data which is affected by several experimental parameters, including e.g. imperfect bisulphite conversion, oxidation efficiencies, various chemical labeling and protection steps, and sequencing errors. Here, we present a hierarchical generative model, Lux, for integrative analysis of any combination of BS-seq and âoxi-mCâ-seq (BS-seq/oxBS-seq/TAB-seq/fCAB-seq/CAB-seq/redBS-seq/MAB-seq) data. We show that Lux improves quantification and comparison of methylation levels over existing methods and that Lux can easily process any oxi-mC-seq data sets to quantify all cytosine modifications simultaneously together with their experimental parameters. Application of Lux to targeted data from Tet2 knockdown ESCs and T cells during development demonstrates DNA modification quantification at unprecedented detail, quantifies active demethylation pathway and reveals 5hmC localization in putative regulatory regions. Examine the distribution of C, 5mC, and 5hmC in ES and Tet2 knock-down cells within selected loci. Half of the samples are measured using the traditional bisulphite-seq protocol but the other half is measured using the oxidative bisulphite-seq protocol (oxBS-seq).
2016-07-03 | E-GEOD-68574 | biostudies-arrayexpress
Project description:To characterize the largely unknown functions of oxidised methylcytosines (oxi-mC; 5hmC/5fC/5caC) in DNA, several sequencing protocols have been recently developed. Quantitative analysis is complicated because DNA methylation modifications need to be deconvoluted from the data which is affected by several experimental parameters, including e.g. imperfect bisulphite conversion, oxidation efficiencies, various chemical labeling and protection steps, and sequencing errors. Here, we present a hierarchical generative model, Lux, for integrative analysis of any combination of BS-seq and âoxi-mCâ-seq (BS-seq/oxBS-seq/TAB-seq/fCAB-seq/CAB-seq/redBS-seq/MAB-seq) data. We show that Lux improves quantification and comparison of methylation levels over existing methods and that Lux can easily process any oxi-mC-seq data sets to quantify all cytosine modifications simultaneously together with their experimental parameters. Application of Lux to targeted data from Tet2 knockdown ESCs and T cells during development demonstrates DNA modification quantification at unprecedented detail, quantifies active demethylation pathway and reveals 5hmC localization in putative regulatory regions. Examine the distribution of C, 5mC, and 5hmC in DP, CD4 SP, and naïve CD4 T cells within selected loci. Half of the samples are measured using the traditional bisulphite-seq protocol but the other half is measured using the oxidative bisulphite-seq protocol (oxBS-seq).
2016-07-03 | E-GEOD-68575 | biostudies-arrayexpress
Project description:A probabilistic generative model for quantification of DNA modifications enables analysis of demethylation pathways
| PRJNA283126 | ENA
Project description:Motivation5-methylcytosine (5mC) is a widely studied epigenetic modification of DNA. The ten-eleven translocation (TET) dioxygenases oxidize 5mC into oxidized methylcytosines (oxi-mCs): 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC) and 5-carboxylcytosine (5caC). DNA methylation modifications have multiple functions. For example, 5mC is shown to be associated with diseases and oxi-mC species are reported to have a role in active DNA demethylation through 5mC oxidation and DNA repair, among others, but the detailed mechanisms are poorly understood. Bisulphite sequencing and its various derivatives can be used to gain information about all methylation modifications at single nucleotide resolution. Analysis of bisulphite based sequencing data is complicated due to the convoluted read-outs and experiment-specific variation in biochemistry. Moreover, statistical analysis is often complicated by various confounding effects. How to analyse 5mC and oxi-mC data sets with arbitrary and complex experimental designs is an open and important problem.ResultsWe propose the first method to quantify oxi-mC species with arbitrary covariate structures from bisulphite based sequencing data. Our probabilistic modeling framework combines a previously proposed hierarchical generative model for oxi-mC-seq data and a general linear model component to account for confounding effects. We show that our method provides accurate methylation level estimates and accurate detection of differential methylation when compared with existing methods. Analysis of novel and published data gave insights into to the demethylation of the forkhead box P3 (Foxp3) locus during the induced T regulatory cell differentiation. We also demonstrate how our covariate model accurately predicts methylation levels of the Foxp3 locus. Collectively, LuxGLM method improves the analysis of DNA methylation modifications, particularly for oxi-mC species.Availability and implementationAn implementation of the proposed method is available under MIT license at https://github.org/tare/LuxGLM/ CONTACT: taijo@simonsfoundation.org or harri.lahdesmaki@aalto.fiSupplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC5013920 | biostudies-literature
Project description:Apart from the four canonical nucleobases, DNA molecules carry a number of natural modifications. Substantial evidence shows that DNA modifications can regulate diverse biological processes. Dynamic and reversible modifications of DNA are critical for cell differentiation and development. Dysregulation of DNA modifications is closely related to many human diseases. The research of DNA modifications is a rapidly expanding area and has been significantly stimulated by the innovations of analytical methods. With the recent advances in methods and techniques, a series of new DNA modifications have been discovered in the genomes of prokaryotes and eukaryotes. Deciphering the biological roles of DNA modifications depends on the sensitive detection, accurate quantification, and genome-wide mapping of modifications in genomic DNA. This review provides an overview of the recent advances in analytical methods and techniques for both the quantification and genome-wide mapping of natural DNA modifications. We discuss the principles, advantages, and limitations of these developed methods. It is anticipated that new methods and techniques will resolve the current challenges in this burgeoning research field and expedite the elucidation of the functions of DNA modifications.
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Project description:PurposemiRNAs can act as oncomirs or tumor-suppressor miRs in cancer. This study was undertaken to investigate the status and role of miR-34b in prostate cancer.Experimental designProfiling of miR-34b was carried out in human prostate cancer cell lines and clinical samples by quantitative real-time PCR and in situ hybridization. Statistical analyses were done to assess diagnostic/prognostic potential. Biological significance was elucidated by carrying out a series of experiments in vitro and in vivo.ResultsWe report that miR-34b is silenced in human prostate cancer and the mechanism is through CpG hypermethylation. miR-34b directly targeted methyltransferases and deacetylases resulting in a positive feedback loop inducing partial demethylation and active chromatin modifications. miR-34b expression could predict overall and recurrence-free survival such that patients with high miR-34b levels had longer survival. Functionally, miR-34b inhibited cell proliferation, colony formation, migration/invasion, and triggered G(0)/G(1) cell-cycle arrest and apoptosis by directly targeting the Akt and its downstream proliferative genes. miR-34b caused a decline in the mesenchymal markers vimentin, ZO1, N-cadherin, and Snail with an increase in E-cadherin expression, thus inhibiting epithelial-to-mesenchymal transition. Finally we showed the antitumor effect of miR-34b in vivo. MiR-34b caused a dramatic decrease in tumor growth in nude mice compared with cont-miR.ConclusionThese findings offer new insight into the role of miR-34b in the inhibition of prostate cancer through demethylation, active chromatin modification, and Akt pathways and may provide a rationale for the development of new strategies targeting epigenetic regulation of miRNAs for the treatment of prostate cancer.
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