|Thannhauser, Theodore - Ted|
Submitted to: Journal of Bacteriology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/15/2010
Publication Date: 5/1/2010
Citation: Filiatrault, M.J., Stodghill, P., Bronstein, P., Moll, S., Lindeberg, M., Grills, G., Schweitzer, P., Wang, W., Schroth, G., Luo, S., Khrebtukova, I., Thannhauser, T.W., Yang, Y., Butcher, B.G., Cartinhour, S.W., Schneider, D.J. 2010. Transcriptome analysis of Pseudomonas syringae identifies new genes, ncRNAs, and antisense activity. Journal of Bacteriology. 192(9):2359-2372. Interpretive Summary: In order to fully understand how bacteria respond to their surrounding environment, it is important to determine what occurs at the RNA (transcript) level. Determining what genes are expressed under a given condition, where transcripts start and stop, and where overlapping transcription occurs can provide substantial insight into the mechanisms used by bacteria to globally control the expression of genes. To evaluate this, we sequenced the RNA population of the bacteria using ultra-high-throughput sequencing technology. The resulting sequences were compared with the genomic sequence. As expected, we observed that there is a large percentage of transcripts whose expression is consistent with predictions from the genome annotation. Importantly, we were able to identify transcription in areas of the genome that was inconsistent with the genome annotation and identify transcriptional activity in un-annotated areas of the genome. Our method and approach provide a very useful and efficient way of constructing maps of transcriptional activity in bacteria and additionally it allows for the discovery of specific areas in the genome where the annotation may need to be investigated further.
Technical Abstract: To fully understand how bacteria respond to their environment, it is essential to assess genome-wide transcriptional activity. New high throughput sequencing technologies make it possible to query the transcriptome of an organism in an efficient unbiased manner. We applied a strand-specific method to sequence bacterial transcripts using Illumina’s high-throughput sequencing technology. The resulting sequences were used to construct genome-wide transcriptional profiles. Novel bioinformatics analyses were developed and used in combination with proteomics data for the qualitative classification of transcriptional activity in defined regions. As expected, most transcriptional activity was consistent with predictions from the genome annotation. Importantly, we identified and confirmed transcriptional activity in areas of the genome inconsistent with the annotation and in un-annotated regions. Further analyses revealed potential RpoN-dependent promoter sequences upstream of several ncRNAs suggesting a role for these ncRNAs in RpoN-dependent phenotypes. We were also able to validate a number of transcriptional start sites, many of which were consistent with predicted promoter motifs. Overall, our approach provides an efficient way to survey global transcriptional activity in bacteria and enables rapid discovery of specific areas in the genome that merit further investigation.