Literature DB >> 31844073

MeinteR: A framework to prioritize DNA methylation aberrations based on conformational and cis-regulatory element enrichment.

Andigoni Malousi1, Sofia Kouidou2, Maria Tsagiopoulou3, Nikos Papakonstantinou3, Emmanouil Bouras4, Elisavet Georgiou2, Georgios Tzimagiorgis2, Kostas Stamatopoulos3.   

Abstract

DNA methylation studies have been reformed with the advent of single-base resolution arrays and bisulfite sequencing methods, enabling deeper investigation of methylation-mediated mechanisms. In addition to these advancements, numerous bioinformatics tools address important computational challenges, covering DNA methylation calling up to multi-modal interpretative analyses. However, contrary to the analytical frameworks that detect driver mutational signatures, the identification of putatively actionable epigenetic events remains an unmet need. The present work describes a novel computational framework, called MeinteR, that prioritizes critical DNA methylation events based on the following hypothesis: critical aberrations of DNA methylation more likely occur on a genomic substrate that is enriched in cis-acting regulatory elements with distinct structural characteristics, rather than in genomic "deserts". In this context, the framework incorporates functional cis-elements, e.g. transcription factor binding sites, tentative splice sites, as well as conformational features, such as G-quadruplexes and palindromes, to identify critical epigenetic aberrations with potential implications on transcriptional regulation. The evaluation on multiple, public cancer datasets revealed significant associations between the highest-ranking loci with gene expression and known driver genes, enabling for the first time the computational identification of high impact epigenetic changes based on high-throughput DNA methylation data.

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Year:  2019        PMID: 31844073      PMCID: PMC6915744          DOI: 10.1038/s41598-019-55453-8

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  67 in total

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5.  Bis-SNP: combined DNA methylation and SNP calling for Bisulfite-seq data.

Authors:  Yaping Liu; Kimberly D Siegmund; Peter W Laird; Benjamin P Berman
Journal:  Genome Biol       Date:  2012-07-11       Impact factor: 13.583

6.  Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications.

Authors:  Felix Krueger; Simon R Andrews
Journal:  Bioinformatics       Date:  2011-04-14       Impact factor: 6.937

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Authors:  Eugene Andres Houseman; John Molitor; Carmen J Marsit
Journal:  Bioinformatics       Date:  2014-01-21       Impact factor: 6.937

8.  eFORGE v2.0: updated analysis of cell type-specific signal in epigenomic data.

Authors:  Charles E Breeze; Alex P Reynolds; Jenny van Dongen; Ian Dunham; John Lazar; Shane Neph; Jeff Vierstra; Guillaume Bourque; Andrew E Teschendorff; John A Stamatoyannopoulos; Stephan Beck
Journal:  Bioinformatics       Date:  2019-11-01       Impact factor: 6.937

9.  A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data.

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Journal:  Bioinformatics       Date:  2012-11-21       Impact factor: 6.937

10.  DNA methylation age of human tissues and cell types.

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Journal:  Genome Biol       Date:  2013       Impact factor: 13.583

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2.  In silico structural analysis of sequences containing 5-hydroxymethylcytosine reveals its potential as binding regulator for development, ageing and cancer-related transcription factors.

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  2 in total

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