Dataset Information

RNIE: genome-wide prediction of bacterial intrinsic terminators.

ABSTRACT: Bacterial Rho-independent terminators (RITs) are important genomic landmarks involved in gene regulation and terminating gene expression. In this investigation we present RNIE, a probabilistic approach for predicting RITs. The method is based upon covariance models which have been known for many years to be the most accurate computational tools for predicting homology in structural non-coding RNAs. We show that RNIE has superior performance in model species from a spectrum of bacterial phyla. Further analysis of species where a low number of RITs were predicted revealed a highly conserved structural sequence motif enriched near the genic termini of the pathogenic Actinobacteria, Mycobacterium tuberculosis. This motif, together with classical RITs, account for up to 90% of all the significantly structured regions from the termini of M. tuberculosis genic elements. The software, predictions and alignments described below are available from http://github.com/ppgardne/RNIE.

SUBMITTER: Gardner PP

PROVIDER: S-EPMC3152330 | biostudies-literature | 2011 Aug

REPOSITORIES: biostudies-literature

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RNIE: genome-wide prediction of bacterial intrinsic terminators.

Gardner Paul P PP Barquist Lars L Bateman Alex A Nawrocki Eric P EP Weinberg Zasha Z

Nucleic acids research 20110407 14

Bacterial Rho-independent terminators (RITs) are important genomic landmarks involved in gene regulation and terminating gene expression. In this investigation we present RNIE, a probabilistic approach for predicting RITs. The method is based upon covariance models which have been known for many years to be the most accurate computational tools for predicting homology in structural non-coding RNAs. We show that RNIE has superior performance in model species from a spectrum of bacterial phyla. Fu ...[more]

PMID: 21478170

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Project description:Intrinsic terminators, which encode GC-rich RNA hairpins followed immediately by a 7-to-9-nucleotide (nt) U-rich "U-tract," play principal roles of punctuating and regulating transcription in most bacteria. However, canonical intrinsic terminators with strong U-tracts are underrepresented in some bacterial lineages, notably mycobacteria, leading to proposals that their RNA polymerases stop at noncanonical intrinsic terminators encoding various RNA structures lacking U-tracts. We generated recombinant forms of mycobacterial RNA polymerase and its major elongation factors NusA and NusG to characterize mycobacterial intrinsic termination. Using in vitro transcription assays devoid of possible mycobacterial contaminants, we established that mycobacterial RNA polymerase terminates more efficiently than Escherichia coli RNA polymerase at canonical terminators with imperfect U-tracts but does not terminate at putative terminators lacking U-tracts even in the presence of mycobacterial NusA and NusG. However, mycobacterial NusG exhibits a novel termination-stimulating activity that may allow intrinsic terminators with suboptimal U-tracts to function efficiently. IMPORTANCE Bacteria rely on transcription termination to define and regulate units of gene expression. In most bacteria, precise termination and much regulation by attenuation are accomplished by intrinsic terminators that encode GC-rich hairpins and U-tracts necessary to disrupt stable transcription elongation complexes. Thus, the apparent dearth of canonical intrinsic terminators with recognizable U-tracts in mycobacteria is of significant interest both because noncanonical intrinsic terminators could reveal novel routes to destabilize transcription complexes and because accurate understanding of termination is crucial for strategies to combat mycobacterial diseases and for computational bioinformatics generally. Our finding that mycobacterial RNA polymerase requires U-tracts for intrinsic termination, which can be aided by NusG, will guide future study of mycobacterial transcription and aid improvement of predictive algorithms to annotate bacterial genome sequences.

Dataset Information

RNIE: genome-wide prediction of bacterial intrinsic terminators.

Publications

RNIE: genome-wide prediction of bacterial intrinsic terminators.

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