Dataset Information

Human cells contain natural double-stranded RNAs with potential regulatory capacity

ABSTRACT: Although recent evidence suggests that overlapping sense/antisense transcription is a common feature in higher eukaryotes, the possibility that overlapping transcripts could interact to each other and bear a specific biological function has not been explored. Here we show that a plethora of sense/antisense transcript pairs are co-expressed from 8q24.21 within the same cell and acquire a stable double-stranded RNA conformation. Interestingly, these molecules display predominantly nuclear localization and establish specific interactions with nuclear components. A detailed characterization of a particular sense/antisense pair (ndsRNA-2a) revealed that this molecule displays differential localization throughout the cell cycle, interacts with RCC1 and RAN and through the latter with the mitotic RANGAP1-SUMO1/RANBP2 complex. Notably, an increased number of bi/multi-nucleated cells and chromatin bridges were observed upon ndsRNA-2a overexpression, whereas strand-specific ndsRNA-2a knockdown leads to mitotic catastrophe and cell death. This suggests a functional role of ndsRNA-2a in cell cycle progression that critically requires its double stranded nature. Finally, the identification of hundreds of sense/antisense transcripts pairs harboring ndsRNA profile signatures and their regulation by cellular cues suggests that ndsRNAs constitute a novel class of regulatory molecules that are likely to be involved in a plethora of biological processes.

ORGANISM(S): Homo sapiens

PROVIDER: GSE62930 | GEO | 2014/12/14

SECONDARY ACCESSION(S): PRJNA266237

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Background: Recent studies have demonstrated that antisense transcription is pervasive in budding yeasts and is conserved between Saccharomyces cerevisiae and S. paradoxus. While studies have examined antisense transcripts of S. cerevisiae for inverse transcription in stationary phase and stress conditions, there is a lack of comprehensive analysis of the conditional specific evolutionary characteristics of antisense transcription between yeasts. Here we attempt to decipher the evolutionary relationship of antisense transcription of S. cerevisiae and S. paradoxus cultured in mid log, early stationary phase, and heat shock conditions. Results: Massively parallel sequencing of sequence strand-specific cDNA library was performed from RNA isolated from S. cerevisiae and S. paradoxus cells at mid log, stationary phase and heat shock conditions. We performed this analysis using a stringent set of sense ORF transcripts and non-coding antisense transcripts that were expressed in all the three conditions, as well as in both species. We found the divergence of the condition specific anti-sense transcription levels is higher than that in condition specific sense transcription levels, suggesting that antisense transcription played a potential role in adapting to different conditions. Furthermore, 43% of sense-antisense pairs demonstrated inverse transcription in either stationary phase or heat shock conditions relative to the mid log conditions. In addition, a large part of sense-antisense pairs (67%), which demonstrated inverse transcription, were highly conserved between the two species. Our results were also concordant with known functional analyses from previous studies and with the evidence from mechanistic experiments of role of individual genes. Conclusions: This study provides a comprehensive picture of the role of antisense transcription mediating sense transcription in different conditions across yeast species. We can conclude from our findings that antisense regulation could act like an on-off switch on sense regulation in different conditions.

Dataset Information

Human cells contain natural double-stranded RNAs with potential regulatory capacity

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets