Zhang Z, et al. (2007) Genome-wide identification of spliced introns using a tiling microarray. Genome Res 17(4):503-9
Abstract: The prediction of gene models from genome sequence remains an unsolved problem. One hallmark of eukaryotic gene structure is the presence of introns, which are spliced out of pre-mRNAs prior to translation. The excised introns are released in the form of lariats, which must be debranched prior to their turnover. In the yeast Saccharomyces cerevisiae, the absence of the debranching enzyme causes these lariat RNAs to accumulate. This accumulation allows a comparison of tiling array signals of RNA from the debranching mutant to the wild-type parent strain, and thus the identification of lariats on a genome-wide scale. This approach identified 141 of 272 known introns, confirmed three previously predicted introns, predicted four novel introns (of which two were experimentally confirmed), and led to the reannotation of four others. In many instances, signals from the tiling array delineated the 5' splice site and branchpoint site, confirming predicted gene structures. Nearly all introns that went undetected are present in mRNAs expressed at low levels. Overall, 97% of the significant probes could be attributed either to spliced introns or to genes up-regulated by deletion of the debranching enzyme. Because the debranching enzyme is conserved among eukaryotes, this approach could be generally applicable for the annotation of eukaryotic genes and the detection of novel and alternative splice forms.
|Status: Published||Type: Journal Article||PubMed ID: 17351133|
Topics addressed in this paper
Number of different genes curated to this paper: 9
- To find other papers on a gene and topic, click on the colored ball in the appropriate box.
- displays other papers with information about that topic for that gene.
- displays other papers in SGD that are associated with that topic.
The topic is addressed in these papers but does not describe a specific gene or chromosomal feature.
- To go to the Locus page for a gene, click on the gene name.