RNAalifold: improved consensus structure prediction for RNA alignments

Bernhart, Stephan H.; Hofacker, Ivo L.; Will, Sebastian; Gruber, Andreas; Stadler, Peter F.

doi:10.1186/1471-2105-9-474

Cited by 530 publications

(562 citation statements)

References 44 publications

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“…Initially, using Turbofold program [52], we were able to compare the common domain architecture of individually folded Trypanosoma TR molecules to derive a consensus structure. This structure was then verified by RNAalifold [53], and a potential region to form a pseudoknot was identified by Pknots program [54]. Finally, covariations were checked manually within conserved domains.…”

Section: Secondary Structure Of Tbtrmentioning

confidence: 99%

A trans-spliced telomerase RNA dictates telomere synthesis in Trypanosoma brucei

et al. 2013

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Telomerase is a ribonucleoprotein enzyme typically required for sustained cell proliferation. Although both telomerase activity and the telomerase catalytic protein component, TbTERT, have been identified in the eukaryotic pathogen Trypanosoma brucei, the RNA molecule that dictates telomere synthesis remains unknown. Here, we identify the RNA component of Trypanosoma brucei telomerase, TbTR, and provide phylogenetic and in vivo evidence for TbTR's native folding and activity. We show that TbTR is processed through trans-splicing, and is a capped transcript that interacts and copurifies with TbTERT in vivo. Deletion of TbTR caused progressive shortening of telomeres at a rate of 3-5 bp/population doubling (PD), which can be rescued by ectopic expression of a wild-type allele of TbTR in an apparent dose-dependent manner. Remarkably, introduction of mutations in the TbTR template domain resulted in corresponding mutant telomere sequences, demonstrating that telomere synthesis in T. brucei is dependent on TbTR. We also propose a secondary structure model for TbTR based on phylogenetic analysis and chemical probing experiments, thus defining TbTR domains that may have important functional implications in telomere synthesis. Identification and characterization of TbTR not only provide important insights into T. brucei telomere functions, which have been shown to play important roles in T. brucei pathogenesis, but also offer T. brucei as an attractive model system for studying telomerase biology in pathogenic protozoa and for comparative analysis of telomerase function with higher eukaryotes.

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Section: Secondary Structure Of Tbtrmentioning

confidence: 99%

A trans-spliced telomerase RNA dictates telomere synthesis in Trypanosoma brucei

et al. 2013

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“…S3 and Tables S3 and S4). To determine the degree of secondary structural conservation between culture-derived ncRNA sequences and their counterparts in the metagenome and metatranscriptome, we used RNAfold to compare computationally predicted structures (71)(72)(73)(74). RNAfold predicted very similar core secondary structures between the culture and environmental sequences for most ncRNAs among the top matches (Fig.…”

Section: Significancementioning

confidence: 99%

Trichodesmium genome maintains abundant, widespread noncoding DNA in situ, despite oligotrophic lifestyle

Walworth

Pfreundt

Nelson

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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Understanding the evolution of the free-living, cyanobacterial, diazotroph Trichodesmium is of great importance because of its critical role in oceanic biogeochemistry and primary production. Unlike the other >150 available genomes of free-living cyanobacteria, only 63.8% of the Trichodesmium erythraeum (strain IMS101) genome is predicted to encode protein, which is 20-25% less than the average for other cyanobacteria and nonpathogenic, free-living bacteria. We use distinctive isolates and metagenomic data to show that low coding density observed in IMS101 is a common feature of the Trichodesmium genus, both in culture and in situ. Transcriptome analysis indicates that 86% of the noncoding space is expressed, although the function of these transcripts is unclear. The density of noncoding, possible regulatory elements predicted in Trichodesmium, when normalized per intergenic kilobase, was comparable and twofold higher than that found in the gene-dense genomes of the sympatric cyanobacterial genera Synechococcus and Prochlorococcus, respectively. Conserved Trichodesmium noncoding RNA secondary structures were predicted between most culture and metagenomic sequences, lending support to the structural conservation. Conservation of these intergenic regions in spatiotemporally separated Trichodesmium populations suggests possible genus-wide selection for their maintenance. These large intergenic spacers may have developed during intervals of strong genetic drift caused by periodic blooms of a subset of genotypes, which may have reduced effective population size. Our data suggest that transposition of selfish DNA, low effective population size, and high-fidelity replication allowed the unusual "inflation" of noncoding sequence observed in Trichodesmium despite its oligotrophic lifestyle. marine microbiology | oligotrophic | evolution genomics | nitrogen fixation T he low availability of N (and fixed carbon) in the midlatitude upper oceans provides an important niche for autotrophic organisms that can fix atmospheric nitrogen, which can exert control over global primary production (1-3). Nitrogen fixation is a prokaryotic process with a high-energy demand, and oceanic cyanobacteria are known to be significant sources of this "new" nitrogen (nitrogen that is fixed from the atmosphere or NO 3 advected from depth) (4, 5). Molecular field data have shown that a handful of cyanobacterial diazotrophs responsible for oligotrophic nitrogen fixation can reach relatively high cell numbers (6-12) and be of significant biogeochemical importance (13-16). These include photosynthetic free-living forms, such as the filamentous Trichodesmium and the unicellular Crocosphaera and Cyanothece, and photosynthetic and nonphotosynthetic symbiotic forms, such as heterocystous Richelia and Candidatus Atelocyanobacterium thalassa (3,5,17).Trichodesmium cells can grow either as trichomes (i.e., filaments) or aggregates and form three types of classically described colonies, including radial puffs, vertically aligned fusiform tufts, and bowties (...

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“…The performance of TurboFold is compared with three other methods that estimate base pairing probabilities 6 : 1) LocARNA [12] (Version 1.5.2a is used, with Vienna RNA Software Package version 1.8.4), 2) RNAalifold [13] (The version included in Vienna RNA Software Package version 1.8.4 is used with command line option '-p' for computation of base pairing probabilities with ClustalW 2.0.11 [14] for computation of input sequence alignment), and 3) Single sequence estimates of base pairing probabilities using a nearest neighbor thermodynamic model [10,15] (as implemented in RNAstructure version 4.5 [15,16]). …”

Section: Resultsmentioning

confidence: 99%

Iterative estimation of structures of multiple RNA homologs: Turbofold

Sharma

Harmanci

Mathews

2011

2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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TurboFold, an iterative algorithm for estimating the common secondary structures of multiple RNA homologs, is presented. The algorithm is motivated by and has structure and attributes analogous to the turbo decoding algorithm in communications. Instead of solving the joint problem of aligning and folding multiple RNA sequences, TurboFold uses an iterative process to fold a collection of RNA homologs. Beneficial information from inter-sequence comparisons is incorporated by using feedback from iteration to iteration in the form of pseudo-prior probabilities for base pairing which are incorporated in the computation of base pairing probabilities. As a result TurboFold retains several of the advantages of join alignment and folding while maintaining a per iteration computational complexity comparable to single sequence RNA folding. Experimental evaluation of the algorithm, performed over six ncRNA families, demonstrates that TurboFold achieves high accuracy, offering better performance than available alternatives for estimating RNA base pairing probabilities.Index Terms-RNA secondary structure, Turbo decoding, Iterative Estimation INTRODUCTION AND BACKGROUNDRNA has recently emerged as a key player in biology, serving a number of crucial noncoding roles, in addition to its traditionally known function as a transient mRNA copy of the genetic code for protein synthesis [1]. The secondary structure, i.e. the set of hydrogenbond-mediated pairings between bases located within the linear strand of an RNA molecule, plays a key role in defining the function for these noncoding RNAs (ncRNAs). The secondary structure is important in developing hypotheses about function, finding new instances of an RNA family in genomes , designing therapeutics , and is crucial in modeling and solving the 3D structure . Computational prediction of RNA secondary structure, commonly referred to as computational RNA folding, is therefore an important problem in computational biology [2, Chap. 10].Computational methods for predicting RNA secondary structure use, as inputs, the primary structure information for RNA, which, for the purposes of the ensuing discussion, consists of a sequence x ∈ A N where A = {A, U, G, C} and N denotes the length of the sequence. The length of the sequence corresponds to the number of nucleotides in the RNA chain and the elements of the sequence denote the identifying nitrogenous base associated with each of the nucleotides arranged in order from the 5 to the 3 end of the chain.

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RNAalifold: improved consensus structure prediction for RNA alignments

Cited by 530 publications

References 44 publications

A trans-spliced telomerase RNA dictates telomere synthesis in Trypanosoma brucei

A trans-spliced telomerase RNA dictates telomere synthesis in Trypanosoma brucei

Trichodesmium genome maintains abundant, widespread noncoding DNA in situ, despite oligotrophic lifestyle

Iterative estimation of structures of multiple RNA homologs: Turbofold

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