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      Rapid, accurate, computational discovery of Rho-independent transcription terminators illuminates their relationship to DNA uptake

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      1 , , 1 ,   1
      Genome Biology
      BioMed Central

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          Abstract

          Using a novel computational method, an extensive collection of predicted Rho-independent transcription terminators is derived from 343 prokaryotes, offering insight into their relationship to DNA uptake

          Abstract

          Background

          In many prokaryotes, transcription of DNA to RNA is terminated by a thymine-rich stretch of DNA following a hairpin loop. Detecting such Rho-independent transcription terminators can shed light on the organization of bacterial genomes and can improve genome annotation. Previous computational methods to predict Rho-independent terminators have been slow or limited in the organisms they consider.

          Results

          We describe TransTermHP, a new computational method to rapidly and accurately detect Rho-independent transcription terminators. We predict the locations of terminators in 343 prokaryotic genomes, representing the largest collection of predictions available. In Bacillus subtilis, we can detect 93% of known terminators with a false positive rate of just 6%, comparable to the best-known methods. Outside the Firmicutes division, we find that Rho-independent termination plays a large role in the Neisseria and Vibrio genera, the Pasteurellaceae (including the Haemophilus genus) and several other species. In Neisseria and Pasteurellaceae, terminator hairpins are frequently formed by closely spaced, complementary instances of exogenous DNA uptake signal sequences. We quantify the propensity for terminators to include these sequences. In the process, we provide the first discussion of potential uptake signals in Haemophilus ducreyi and Mannheimia succiniciproducens, and we discuss the preference for a particular configuration of uptake signal sequences within terminators.

          Conclusion

          Our new fast and accurate method for detecting transcription terminators has allowed us to identify and analyze terminators in many new genomes and to identify DNA uptake signal sequences in several species where they have not been previously reported. Our software and predictions are freely available.

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          Most cited references22

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          DNA uptake in bacteria.

          D Dubnau (1998)
          Natural competence is widespread among bacterial species. The mechanism of DNA uptake in both gram-positive and gram-negative bacteria is reviewed. The transformation pathways are discussed, with attention to the fate of donor DNA as it is processed by the competent cell. The proteins involved in mediating various steps in these pathways are described, and models for the transformation mechanisms are presented. Uptake of DNA across the inner membrane is probably similar in gram-positive and gram-negative bacteria, and at least some of the required proteins are orthologs. The initial transformation steps differ, as expected, from the presence of an outer membrane only in the gram-negative organisms. The similarity of certain essential competence proteins to those required for the assembly of type-4 pili and for type-2 protein secretion is discussed. Finally several hypotheses for the biological role of transformation are presented and evaluated.
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            Fast algorithm for predicting the secondary structure of single-stranded RNA.

            A computer method is presented for finding the most stable secondary structures in long single-stranded RNAs. It is 1-2 orders of magnitude faster than existing codes. The time required for its application increases as N3 for a chain N nucleotides long. As many as 1000 nucleotides can be searched in a single run. The approach is systematic and builds an optimal structure in a straightforward inductive procedure based on an exact mathematical algorithm. Two simple half-matrices are constructed and the best folded form is read directly from the second matrix by a simple back-tracking procedure. The program utilizes published values for base-pairing energies to compute one structure with the lowest free energy.
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              Prediction of rho-independent transcriptional terminators in Escherichia coli.

              A new algorithm called RNAMotif containing RNA structure and sequence constraints and a thermodynamic scoring system was used to search for intrinsic rho-independent terminators in the Escherichia coli K-12 genome. We identified all 135 reported terminators and 940 putative terminator sequences beginning no more than 60 nt away from the 3'-end of the annotated transcription units (TU). Putative and reported terminators with the scores above our chosen threshold were found for 37 of the 53 non-coding RNA TU and for almost 50% of the 2592 annotated protein-encoding TU, which correlates well with the number of TU expected to contain rho-independent terminators. We also identified 439 terminators that could function in a bi-directional fashion, servicing one gene on the positive strand and a different gene on the negative strand. Approximately 700 additional termination signals in non-coding regions (NCR) far away from the nearest annotated gene were predicted. This number correlates well with the excess number of predicted 'orphan' promoters in the NCR, and these promoters and terminators may be associated with as yet unidentified TU. The significant number of high scoring hits that occurred within the reading frame of annotated genes suggests that either an additional component of rho-independent terminators exists or that a suppressive mechanism to prevent unwanted termination remains to be discovered.
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                Author and article information

                Journal
                Genome Biol
                Genome Biology
                BioMed Central (London )
                1465-6906
                1465-6914
                2007
                21 February 2007
                : 8
                : 2
                : R22
                Affiliations
                [1 ]Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA
                Article
                gb-2007-8-2-r22
                10.1186/gb-2007-8-2-r22
                1852404
                17313685
                8f5d1c41-05f4-4edf-a44f-f461fddfd5c0
                Copyright © 2007 Kingsford et al.; licensee BioMed Central Ltd.

                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.

                History
                : 14 September 2006
                : 1 December 2006
                : 21 February 2007
                Categories
                Research

                Genetics
                Genetics

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