31 research outputs found

    Assessing the efficiency and significance of Methylated DNA Immunoprecipitation (MeDIP) assays in using in vitro methylated genomic DNA

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    <p>Abstract</p> <p>Background</p> <p>DNA methylation contributes to the regulation of gene expression during development and cellular differentiation. The recently developed Methylated DNA ImmunoPrecipitation (MeDIP) assay allows a comprehensive analysis of this epigenetic mark at the genomic level in normal and disease-derived cells. However, estimating the efficiency of the MeDIP technique is difficult without previous knowledge of the methylation status of a given cell population. Attempts to circumvent this problem have involved the use of <it>in vitro </it>methylated DNA in parallel to the investigated samples. Taking advantage of this stratagem, we sought to improve the sensitivity of the approach and to assess potential biases resulting from DNA amplification and hybridization procedures using MeDIP samples.</p> <p>Findings</p> <p>We performed MeDIP assays using <it>in vitro </it>methylated DNA, with or without previous DNA amplification, and hybridization to a human promoter array. We observed that CpG content at gene promoters indeed correlates strongly with the MeDIP signal obtained using <it>in vitro </it>methylated DNA, even when lowering significantly the amount of starting material. In analyzing MeDIP products that were subjected to whole genome amplification (WGA), we also revealed a strong bias against CpG-rich promoters during this amplification procedure, which may potentially affect the significance of the resulting data.</p> <p>Conclusion</p> <p>We illustrate the use of <it>in vitro </it>methylated DNA to assess the efficiency and accuracy of MeDIP procedures. We report that efficient and reproducible genome-wide data can be obtained via MeDIP experiments using relatively low amount of starting genomic DNA; and emphasize for the precaution that must be taken in data analysis when an additional DNA amplification step is required.</p

    TFregulomeR reveals transcription factors' context-specific features and functions

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    10.1093/nar/gkz1088Nucleic Acids Research482563759

    Whole genome DNA methylation: Beyond genes silencing

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    10.18632/oncotarget.13562Oncotarget835629-563

    miREM: An expectation-maximization approach for prioritizing miRNAs associated with gene-set

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    10.1186/s12859-018-2292-1BMC Bioinformatics19129
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