Systematic classification of non-coding RNAs by epigenomic similarity

BMC Bioinformatics. 2013;14 Suppl 14(Suppl 14):S2. doi: 10.1186/1471-2105-14-S14-S2. Epub 2013 Oct 9.

Abstract

Background: Even though only 1.5% of the human genome is translated into proteins, recent reports indicate that most of it is transcribed into non-coding RNAs (ncRNAs), which are becoming the subject of increased scientific interest. We hypothesized that examining how different classes of ncRNAs co-localized with annotated epigenomic elements could help understand the functions, regulatory mechanisms, and relationships among ncRNA families.

Results: We examined 15 different ncRNA classes for statistically significant genomic co-localizations with cell type-specific chromatin segmentation states, transcription factor binding sites (TFBSs), and histone modification marks using GenomeRunner (http://www.genomerunner.org). P-values were obtained using a Chi-square test and corrected for multiple testing using the Benjamini-Hochberg procedure. We clustered and visualized the ncRNA classes by the strength of their statistical enrichments and depletions.

Conclusions: Searching for statistically significant associations between ncRNA classes and epigenomic elements permits detection of potential functional and/or regulatory relationships among ncRNA classes, and suggests cell type-specific biological roles of ncRNAs.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Binding Sites
  • Chromatin / genetics
  • Chromatin / metabolism
  • Epigenomics*
  • Genome, Human
  • Histones / metabolism
  • Humans
  • RNA, Untranslated / chemistry
  • RNA, Untranslated / classification
  • RNA, Untranslated / genetics*
  • Transcription Factors / chemistry
  • Transcription Factors / metabolism

Substances

  • Chromatin
  • Histones
  • RNA, Untranslated
  • Transcription Factors