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Biocomputational prediction of non-coding RNAs in model cyanobacteria
BACKGROUND: In bacteria, non-coding RNAs (ncRNA) are crucial regulators of gene expression, controlling various stress responses, virulence, and motility. Previous work revealed a relatively high number of ncRNAs in some marine cyanobacteria. However, for efficient genetic and biochemical analysis i...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2009
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2662882/ https://www.ncbi.nlm.nih.gov/pubmed/19309518 http://dx.doi.org/10.1186/1471-2164-10-123 |
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author | Voß, Björn Georg, Jens Schön, Verena Ude, Susanne Hess, Wolfgang R |
author_facet | Voß, Björn Georg, Jens Schön, Verena Ude, Susanne Hess, Wolfgang R |
author_sort | Voß, Björn |
collection | PubMed |
description | BACKGROUND: In bacteria, non-coding RNAs (ncRNA) are crucial regulators of gene expression, controlling various stress responses, virulence, and motility. Previous work revealed a relatively high number of ncRNAs in some marine cyanobacteria. However, for efficient genetic and biochemical analysis it would be desirable to identify a set of ncRNA candidate genes in model cyanobacteria that are easy to manipulate and for which extended mutant, transcriptomic and proteomic data sets are available. RESULTS: Here we have used comparative genome analysis for the biocomputational prediction of ncRNA genes and other sequence/structure-conserved elements in intergenic regions of the three unicellular model cyanobacteria Synechocystis PCC6803, Synechococcus elongatus PCC6301 and Thermosynechococcus elongatus BP1 plus the toxic Microcystis aeruginosa NIES843. The unfiltered numbers of predicted elements in these strains is 383, 168, 168, and 809, respectively, combined into 443 sequence clusters, whereas the numbers of individual elements with high support are 94, 56, 64, and 406, respectively. Removing also transposon-associated repeats, finally 78, 53, 42 and 168 sequences, respectively, are left belonging to 109 different clusters in the data set. Experimental analysis of selected ncRNA candidates in Synechocystis PCC6803 validated new ncRNAs originating from the fabF-hoxH and apcC-prmA intergenic spacers and three highly expressed ncRNAs belonging to the Yfr2 family of ncRNAs. Yfr2a promoter-luxAB fusions confirmed a very strong activity of this promoter and indicated a stimulation of expression if the cultures were exposed to elevated light intensities. CONCLUSION: Comparison to entries in Rfam and experimental testing of selected ncRNA candidates in Synechocystis PCC6803 indicate a high reliability of the current prediction, despite some contamination by the high number of repetitive sequences in some of these species. In particular, we identified in the four species altogether 8 new ncRNA homologs belonging to the Yfr2 family of ncRNAs. Modelling of RNA secondary structures indicated two conserved single-stranded sequence motifs that might be involved in RNA-protein interactions or in the recognition of target RNAs. Since our analysis has been restricted to find ncRNA candidates with a reasonable high degree of conservation among these four cyanobacteria, there might be many more, requiring direct experimental approaches for their identification. |
format | Text |
id | pubmed-2662882 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-26628822009-03-31 Biocomputational prediction of non-coding RNAs in model cyanobacteria Voß, Björn Georg, Jens Schön, Verena Ude, Susanne Hess, Wolfgang R BMC Genomics Research Article BACKGROUND: In bacteria, non-coding RNAs (ncRNA) are crucial regulators of gene expression, controlling various stress responses, virulence, and motility. Previous work revealed a relatively high number of ncRNAs in some marine cyanobacteria. However, for efficient genetic and biochemical analysis it would be desirable to identify a set of ncRNA candidate genes in model cyanobacteria that are easy to manipulate and for which extended mutant, transcriptomic and proteomic data sets are available. RESULTS: Here we have used comparative genome analysis for the biocomputational prediction of ncRNA genes and other sequence/structure-conserved elements in intergenic regions of the three unicellular model cyanobacteria Synechocystis PCC6803, Synechococcus elongatus PCC6301 and Thermosynechococcus elongatus BP1 plus the toxic Microcystis aeruginosa NIES843. The unfiltered numbers of predicted elements in these strains is 383, 168, 168, and 809, respectively, combined into 443 sequence clusters, whereas the numbers of individual elements with high support are 94, 56, 64, and 406, respectively. Removing also transposon-associated repeats, finally 78, 53, 42 and 168 sequences, respectively, are left belonging to 109 different clusters in the data set. Experimental analysis of selected ncRNA candidates in Synechocystis PCC6803 validated new ncRNAs originating from the fabF-hoxH and apcC-prmA intergenic spacers and three highly expressed ncRNAs belonging to the Yfr2 family of ncRNAs. Yfr2a promoter-luxAB fusions confirmed a very strong activity of this promoter and indicated a stimulation of expression if the cultures were exposed to elevated light intensities. CONCLUSION: Comparison to entries in Rfam and experimental testing of selected ncRNA candidates in Synechocystis PCC6803 indicate a high reliability of the current prediction, despite some contamination by the high number of repetitive sequences in some of these species. In particular, we identified in the four species altogether 8 new ncRNA homologs belonging to the Yfr2 family of ncRNAs. Modelling of RNA secondary structures indicated two conserved single-stranded sequence motifs that might be involved in RNA-protein interactions or in the recognition of target RNAs. Since our analysis has been restricted to find ncRNA candidates with a reasonable high degree of conservation among these four cyanobacteria, there might be many more, requiring direct experimental approaches for their identification. BioMed Central 2009-03-23 /pmc/articles/PMC2662882/ /pubmed/19309518 http://dx.doi.org/10.1186/1471-2164-10-123 Text en Copyright © 2009 Voß et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Voß, Björn Georg, Jens Schön, Verena Ude, Susanne Hess, Wolfgang R Biocomputational prediction of non-coding RNAs in model cyanobacteria |
title | Biocomputational prediction of non-coding RNAs in model cyanobacteria |
title_full | Biocomputational prediction of non-coding RNAs in model cyanobacteria |
title_fullStr | Biocomputational prediction of non-coding RNAs in model cyanobacteria |
title_full_unstemmed | Biocomputational prediction of non-coding RNAs in model cyanobacteria |
title_short | Biocomputational prediction of non-coding RNAs in model cyanobacteria |
title_sort | biocomputational prediction of non-coding rnas in model cyanobacteria |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2662882/ https://www.ncbi.nlm.nih.gov/pubmed/19309518 http://dx.doi.org/10.1186/1471-2164-10-123 |
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