REPIC: A database for exploringN⁶-methyladenosine methylome

Abstract

<jats:title>Abstract</jats:title><jats:p>The REPIC (<jats:underline>R</jats:underline>NA <jats:underline>Epi</jats:underline>transcriptome <jats:underline>C</jats:underline>ollection) database records about 10 million peaks called from publicly available m<jats:sup>6</jats:sup>A-seq and MeRIP-seq data using our unified pipeline. These data were collected from 672 samples of 49 studies, covering 61 cell lines or tissues in 11 organisms. REPIC allows users to query <jats:italic>N</jats:italic><jats:sup>6</jats:sup>-methyladenosine (m<jats:sup>6</jats:sup>A) modification sites by specific cell lines or tissue types. In addition, it integrates m<jats:sup>6</jats:sup>A/MeRIP-seq data with 1,418 histone ChIP-seq and 118 DNase-seq data tracks from the ENCODE project in a modern genome browser to present a comprehensive atlas of m<jats:sup>6</jats:sup>A, histone modification sites and chromatin accessibility regions. REPIC is accessible at <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="http://epicmod.uchicago.edu/repic">http://epicmod.uchicago.edu/repic</jats:ext-link>.</jats:p>

Recent advances in functional annotation and prediction of the epitranscriptome

“…exomePeak and MeTPeak are specifically designed for epitranscriptome peak calling of MeRIP-Seq data. MeTPeak outperforms exomePeak in robustness against data variance and can detect less enriched peaks [90] and exomePeak achieves better motif enrichment than MeTPeak in some cases [91] . Recently, an updated version of exomePeak has been released officially on Bioconductor ( http://www.bioconductor.org/packages/release/bioc/html/exomePeak2.html ), which corrects the GC content bias generated by PCR amplification during the library preparation, a common bias among MeRIP-Seq samples.…”

RMDisease: a database of genetic variants that affect RNA modifications, with implications for epitranscriptome pathogenesis

“…The MODOMICS database concerns mainly RNA modification pathways. MeT-DB ( 44 ), CVm6A ( 45 ) and REPIC ( 46 ) collect and annotate the transcriptome m 6 A sites under different experimental conditions; while RMBase is currently the most comprehensive database containing well annotated sites of multiple types of RNA modifications identified in multiple species. m 6 AVar ( 17 ) and m7GDiseaseDB ( 18 ) contain disease-associated SNPs that can affect m 6 A and internal m 7 G RNA modification, respectively.…”

Dynamics of m6A RNA Methylome on the Hallmarks of Hepatocellular Carcinoma

“…An interactive analysis of epitranscriptomic sequencing for m6A site identification can be performed by databases such as deepEA ( Zhai et al, 2020 ) and iMRM ( Liu and Chen, 2020 ), while RNAWRE ( Nie et al, 2020 ), and M6A2Target ( Deng et al, 2020 ) deposit m6A regulator datasets. Furthermore, comprehensive information on reliable m6A methylation sites and peaks from MeRIP-seq data are summarized in m6A-Atlas ( Tang et al, 2020 ) and REPIC ( Liu et al, 2020b ), respectively. Bioinformatics resources such as RMDisease ( Chen K. et al, 2020 ) and RMVar ( Luo et al, 2020 ) can aid in better understanding the association between various epitranscriptomic modifications and their probable disease relevance.…”