Identification of expressed and conserved human noncoding RNAs

Research output: Contribution to journalJournal articleResearchpeer-review

  • Morten Muhlig Nielsen
  • Disa Tehler
  • Søren Vang
  • Frantisek Sudzina
  • Jakob Hedegaard
  • Iver Nordentoft
  • Torben Falck Orntoft
  • Lund, Anders H.
  • Jakob Skou Pedersen

The past decade has shown mammalian genomes to be pervasively transcribed and identified thousands of noncoding (nc) transcripts. It is currently unclear to what extent these transcripts are of functional importance, as experimental functional evidence exists for only a small fraction. Here, we characterize the expression and evolutionary conservation properties of 12,115 known and novel nc transcripts, including structural RNAs, long nc RNAs (lncRNAs), antisense RNAs, EvoFold predictions, ultraconserved elements, and expressed nc regions. Expression levels are evaluated across 12 human tissues using a custom-designed microarray, supplemented with RNAseq. Conservation levels are evaluated at both the base level and at the syntenic level. We combine these measures with epigenetic mark annotations to identify subsets of novel nc transcripts that show characteristics similar to known functional ncRNAs. Few novel nc transcripts show both high expression and conservation levels. However, overall, we observe a positive correlation between expression and both conservation and epigenetic annotations, suggesting that a subset of the expressed transcripts are under purifying selection and likely functional. The identified subsets of expressed and conserved novel nc transcripts may form the basis for further functional characterization.

Original languageEnglish
JournalR N A
Volume20
Issue number2
Pages (from-to)236-51
Number of pages16
ISSN1355-8382
DOIs
Publication statusPublished - Feb 2014

    Research areas

  • Base Sequence, Chromatin, Conserved Sequence, Expressed Sequence Tags, Humans, Inverted Repeat Sequences, Molecular Sequence Annotation, Oligonucleotide Array Sequence Analysis, Open Reading Frames, Organ Specificity, RNA, Untranslated, Transcriptome, Journal Article, Research Support, Non-U.S. Gov't

ID: 174660543