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dc.contributor.authorLivny, Jonathan
dc.contributor.authorBrencic, Anja
dc.contributor.authorLory, Stephen
dc.contributor.authorWaldor, Matthew K.
dc.date.accessioned2019-10-05T16:05:33Z
dc.date.issued2006
dc.identifier.citationLivny, J. 2006. “Identification of 17 Pseudomonas Aeruginosa sRNAs and Prediction of sRNA-Encoding Genes in 10 Diverse Pathogens Using the Bioinformatic Tool sRNAPredict2.” Nucleic Acids Research 34 (12): 3484–93. https://doi.org/10.1093/nar/gkl453.
dc.identifier.issn0305-1048
dc.identifier.issn1362-4962
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:41483526*
dc.description.abstractsRNAs are small, non-coding RNA species that control numerous cellular processes. Although it iswidely accepted that sRNAs are encoded by most if not all bacteria, genome-wide annotations for sRNA-encoding genes have been conducted in only a few of the nearly 300 bacterial species sequenced to date. To facilitate the efficient annotation of bacterial genomes for sRNA-encoding genes, we developed a program, sRNAPredict2, that identifies putative sRNAs by searching for co-localization of genetic features commonly associated with sRNA-encoding genes. Using sRNAPredict2, we conducted genome-wide annotations for putative sRNA-encoding genes in the intergenic regions of 11 diverse pathogens. In total, 2759 previously unannotated candidate sRNA loci were predicted. There was considerable range in the number of sRNAs predicted in the different pathogens analyzed, raising the possibility that there are species-specific differences in the reliance on sRNA-mediated regulation. Of 34 previously unannotated sRNAs predicted in the opportunistic pathogen Pseudomonas aeruginosa, 31 were experimentally tested and 17 were found to encode sRNA transcripts. Our findings suggest that numerous genes have been missed in the current annotations of bacterial genomes and that, by using improved bioinformatic approaches and tools, much remains to be discovered in 'intergenic' sequences.
dc.language.isoen_US
dc.publisherOxford University Press
dash.licenseLAA
dc.titleIdentification of 17 Pseudomonas aeruginosa sRNAs and prediction of sRNA-encoding genes in 10 diverse pathogens using the bioinformatic tool sRNAPredict2
dc.typeJournal Article
dc.description.versionVersion of Record
dc.relation.journalNucleic Acids Research
dash.depositing.authorWaldor, Matthew K::d323ffce6ff0937ea2fb987a38019253::600
dc.date.available2019-10-05T16:05:33Z
dash.workflow.comments1Science Serial ID 74337
dc.identifier.doi10.1093/nar/gkl453
dash.source.volume34;12


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