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Folding Free Energies of 5'-UTRs Impact Post-Transcriptional Regulation on a Genomic Scale in Yeast.
- Source :
- PLoS Computational Biology; Dec2005, Vol. 1 Issue 7, pe72, 8p, 1 Diagram, 4 Charts, 4 Graphs
- Publication Year :
- 2005
-
Abstract
- Using high-throughput technologies, abundances and other features of genes and proteins have been measured on a genome-wide scale in Saccharomyces cerevisiae. In contrast, secondary structure in 5'-untranslated regions (UTRs) of mRNA has only been investigated for a limited number of genes. Here, the aim is to study genome-wide regulatory effects of mRNA 5'-UTR folding free energies. We performed computations of secondary structures in 5'-UTRs and their folding free energies for all verified genes in S. cerevisiae. We found significant correlations between folding free energies of 5'-UTRs and various transcript features measured in genome-wide studies of yeast. In particular, mRNAs with weakly folded 5'-UTRs have higher translation rates, higher abundances of the corresponding proteins, longer half-lives, and higher numbers of transcripts, and are upregulated after heat shock. Furthermore, 5'-UTRs have significantly higher folding free energies than other genomic regions and randomized sequences. We also found a positive correlation between transcript half-life and ribosome occupancy that is more pronounced for short-lived transcripts, which supports a picture of competition between translation and degradation. Among the genes with strongly folded 5'-UTRs, there is a huge overrepresentation of uncharacterized open reading frames. Based on our analysis, we conclude that (i) there is a widespread bias for 5'-UTRs to be weakly folded, (ii) folding free energies of 5'-UTRs are correlated with mRNA translation and turnover on a genomic scale, and (iii) transcripts with strongly folded 5'-UTRs are often rare and hard to find experimentally. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 1553734X
- Volume :
- 1
- Issue :
- 7
- Database :
- Complementary Index
- Journal :
- PLoS Computational Biology
- Publication Type :
- Academic Journal
- Accession number :
- 19276965
- Full Text :
- https://doi.org/10.1371/journal.pcbi.0010072