Evidence for common short natural trans sense-antisense pairing between transcripts from protein coding genes

Ping Wang, Shanye Yin, Zhenguo Zhang, Dedong Xin, Landian Hu, Xiangyin Kong, Laurence D. Hurst

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

Background: There is increasing realization that regulation of genes is done partly at the RNA level by sense-antisense binding. Studies typically concentrate on the role of non-coding RNAs in regulating coding RNA. But the majority of transcripts in a cell are likely to be coding. Is it possible that coding RNA might regulate other coding RNA by short perfect sense-antisense binding? Here we compare all well-described human protein coding mRNAs against all others to identify sites 15-25 bp long that could potentially perfectly match sense-antisense. Results: From 24,968 protein coding mRNA RefSeq sequences, none failed to find at least one match in the transcriptome. By randomizations generating artificial transcripts matched for G+C content and length, we found that there are more such trans short sense-antisense pairs than expected. Several further features are consistent with functionality of some of the putative matches. First, transcripts with more potential partners have lower expression levels, and the pair density of tissue specific genes is significantly higher than that of housekeeping genes. Further, the single nucleotide polymorphism density is lower in short pairing regions than it is in flanking regions. We found no evidence that the sense-antisense pairing regions are associated with small RNAs derived from the protein coding genes. Conclusions: Our results are consistent with the possibility of common short perfect sense-antisense pairing between transcripts of protein coding genes.

Original languageEnglish (US)
Article numberR169
JournalGenome biology
Volume9
Issue number12
DOIs
StatePublished - Dec 2 2008
Externally publishedYes

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Genetics
  • Cell Biology

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