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Title: Analyzing the transcriptome of Pseudomonas syringae using high-throughput sequencing methodologies

item Filiatrault, Melanie
item Bronstein, Philip
item Stodghill, Paul
item MOLL, SIMON - Cornell University
item Schneider, David
item Cartinhour, Samuel

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 6/6/2010
Publication Date: 8/31/2010
Citation: Filiatrault, M.J., Bronstein, P., Stodghill, P., Moll, S., Schneider, D.J., Cartinhour, S.W. 2010. Analyzing the transcriptome of Pseudomonas syringae using high-throughput sequencing methodologies. Meeting Abstract. p. 31.

Interpretive Summary:

Technical Abstract: New high-throughput sequencing technologies make it possible to query the transcriptome of an organism in a rapid manner. Previously, we reported the development of a method to analyze bacterial transcriptomes on a global scale (RNA-Seq). RNA-Seq provided high-throughput validation of gene predictions, and efficiently discovered regulatory non-coding RNAs (ncRNAs), transcriptional start sites (TSS), and antisense transcription. Here, we present several additional genome-wide approaches we have developed to evaluate the transcriptional landscape of the plant pathogen Pseudomonas syringae DC3000. One approach is to capture and globally identify TSS using Illumina’s high-throughput sequencing technology. We found a large percentage of TSS obtained by this method were consistent with results identified by 5’RACE, demonstrating this approach works accurately. Also, we found transcriptional activity within intergenic regions where no neighboring genes have been annotated, providing evidence for the expression of un-annotated genes and/or ncRNAs. Importantly, this method allows for rapid, large-scale discovery of specific areas in the genome where promoters reside, thus enabling targeted searches for regulatory motifs. Using another more focused high-throughput sequencing approach, we have identified hundreds of candidate ncRNAs. Additionally, our studies revealed numerous examples of antisense transcription, supporting previous findings. Together, the techniques provide an efficient way of evaluating the transcriptome of a bacterium on a genome-wide scale. Integration of these genome-wide data sets not only provides a comprehensive experimental validation of genome annotation but also facilitates discovery, allows for improvement of the existing annotation and generates a number of important questions regarding gene expression in P. syringae.