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Analysis of Transcriptional Regulation of Bradyrhizobium japonicum Based on dRNA-seq Data J. Chuklina1,
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chuklina.jelena@gmail.com

N. Lyubimov , E. Evguenieva-Hackenberg4, M.S. Gelfand2,
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Moscow Institute of Physics and Technology, 9 Institutskiy per., Dolgoprudny, Russia
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Institute for Information Transmission Problems RAS, 19 Bolshoy Karetny per., Moscow, Russia, Moscow State University, GSP-1, Leninskie Gory, Moscow, Russia
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Justus-Liebig-University of Giessen, Heinrich-Buff-Ring 26-32, 35392 Giessen, Germany

The analysis of transcriptome can provide important insights on gene functions and regulatory network of the organism. In addition to the comparison of expression in varying environment, dRNA-seq allows one to map transcription start sites (TSSes) in bacteria, using terminal exonuclease (TEX) to degrade transcripts with processed 5'-ends (as described in [1]). Knowing TSSes also allows for detection of promoter motifs, one of the key elements in controlling differential expression. Here we present the transcriptome analysis of nitrogen fixing -protebacterium, soy symbiont Bradyrhizobium japonicum USDA 110 with RNA taken from soy root nodules and free-living state (see [2] for experimental details). To analyze the dRNA-seq data, we have developed a software package "Transcription Start Site Finder" (TSSF) that detects TSSes and promoters and is complemented with publicly available algorithms for the identification of terminators [3-5]. This allows for a combination of an automatic search and expert analysis using a convenient interface. To detect putative TSSes, we have computed a salience function (convolution with the Haar wavelet) that indicates where a sharp jump in read coverage occurs. To be scored as a TSS, a peaks should have the same coordinate in TEX-treated and non-treated library, be enriched in the former one, have expression above the noise level and satisfy several other empirical characteristics. These features were taken as input data for a machine-learning classification by SVM, which used a subset of manually reviewed TSSes as a training set. To date, 10071

putative TSSes were detected in 9Mb genome of B.japonicum, 6875 TSSes corresponded to putative non-coding RNAs, and only 2744 of 8371 protein-coding genes possessed at least one predicted TSS. To analyze transcriptional regulation, we developed a tool for de novo promoter prediction. It detects positionally overrepresented pairs of oligonucleotides, as sigma-factors
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predominantly used under experimental conditions tested, are known to recognize a motif comprised of two boxes. Having determined the most likely positions of the motif, we constructed positional-weight matrices (PWM) that were then used to score candidate promoters and select the associated sigma-factor. The dRNA-seq data analysis demonstrates an important role of small regulatory RNAs, both trans- and cis-encoded (such as 3'-anti-sense RNAs abundant in Bradyrhizobia-related species). It also is a powerful method to detect transcripts enriched in nodules thus possibly involved in symbiotic nitrogen fixation.

References
[1] Sharma C. M., Hoffmann S., Darfeuille F., Reignier J., Findeiss S., Sittka A., Chabas S., et al. (2010). The primary transcriptome of the major human pathogen Helicobacter pylori. Nature, 464(7286), 2505. [2] Madhugiri R., Pessi G., Voss B., Hahn J., Sharma C.M, Reinhardt R., Vogel J., Hess W.R., Fischer H.-M., Evguenieva-Hackenberg E. (2012) Small RNAs of the Bradyrhizobium/Rhodopseudomonas lineage and their analysis. RNA Biology 9 (1): 47-58. [3] Mitra A., Kesarwani, Anil K., Pal D., Nagaraja V. (2010) WebGeSTer DB--a transcription terminator database. Nucleic acids research.. 39 (Database issue), D12935. [4] Naville M., Ghuillot-Gaudeffroy A., Marchais A., Gautheret D. (2011) ARNold: A web tool for the prediction of Rho-independent transcription terminators. RNA Biology.. 8(1), 1113. [5] Gardner P.P., Barquist L., Bateman A., Nawrocki E. P., Weinberg Z. (2011) RNIE: genome-wide prediction of bacterial intrinsic terminators. Nucleic acids research. 39(14), 58455852.