RNAspace.org: An integrated environment for the prediction, annotation, and analysis of ncRNA

Cros, Marie‐Josée; Monte, Antoine de; Mariette, Jérôme; Bardou, Philippe; Grenier‐Boley, Benjamin; Gautheret, Daniel; Touzet, Hélène; Gaspin, Christine

doi:10.1261/rna.2844911

Cited by 29 publications

(28 citation statements)

References 63 publications

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“…The algorithms RNAz, INFERNAL, and BLASTn were all used through the platform RNAspace (Cros et al 2011), and SIPHT was used through its own platform (Livny 2012). RNAz is a method of comparative genomics that searches for conserved genome fragments which present sRNA motifs, while evaluating the thermodynamic stability of their secondary structure (Gruber et al 2010).…”

Section: Discussionmentioning

confidence: 99%

“…Four algorithms with distinct approaches were used to increase prediction accuracy: RNAz (Gruber et al 2010), INFERNAL (Nawrocki and Eddy 2013), SIPHT (Livny 2012), and BLASTn on Rfam (Nawrocki et al 2015). The predictions with BLASTn, RNAz, and INFERNAL were performed through the RNAspace platform (Cros et al 2011), available at www.rnaspace. org/.…”

Section: In Silico Identification Of Srnasmentioning

confidence: 99%

“…For that reason, computational tools have become relevant, with ever-growing approaches for the discovery and characterization of regulatory RNAs (Cros et al 2011;Livny 2012;Tesorero et al 2013;Corredor and Murillo 2014).…”

Section: Introductionmentioning

confidence: 99%

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A computational strategy for the search of regulatory small RNAs in Actinobacillus pleuropneumoniae

Rossi

Bossé

et al. 2016

RNA

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Bacterial regulatory small RNAs (sRNAs) play important roles in gene regulation and are frequently connected to the expression of virulence factors in diverse bacteria. Only a few sRNAs have been described for Pasteurellaceae pathogens and no in-depth analysis of sRNAs has been described for Actinobacillus pleuropneumoniae, the causative agent of porcine pleuropneumonia, responsible for considerable losses in the swine industry. To search for sRNAs in A. pleuropneumoniae, we developed a strategy for the computational analysis of the bacterial genome by using four algorithms with different approaches, followed by experimental validation. The coding strand and expression of 17 out of 23 RNA candidates were confirmed by Northern blotting, RT-PCR, and RNA sequencing. Among them, two are likely riboswitches, three are housekeeping regulatory RNAs, two are the widely studied GcvB and 6S sRNAs, and 10 are putative novel trans-acting sRNAs, never before described for any bacteria. The latter group has several potential mRNA targets, many of which are involved with virulence, stress resistance, or metabolism, and connect the sRNAs in a complex gene regulatory network. The sRNAs identified are well conserved among the Pasteurellaceae that are evolutionarily closer to A. pleuropneumoniae and/or share the same host. Our results show that the combination of newly developed computational programs can be successfully utilized for the discovery of novel sRNAs and indicate an intricate system of gene regulation through sRNAs in A. pleuropneumoniae and in other Pasteurellaceae, thus providing clues for novel aspects of virulence that will be explored in further studies.

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Section: Discussionmentioning

confidence: 99%

Section: In Silico Identification Of Srnasmentioning

confidence: 99%

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A computational strategy for the search of regulatory small RNAs in Actinobacillus pleuropneumoniae

Rossi

Bossé

et al. 2016

RNA

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“…RNASpace server (http://rnaspace.org/ [28]) and Rfam (http:// rfam.xfam.org/ [29]) database and search tool (similar by architecture to Pfam, see below) are more convenient for more comprehensive search and annotation of non-coding RNAs. The fast way of tRNA sequence prediction is to use the tRNAscan-SE web-based tool [30,31].…”

Section: Non-coding Rna Predictionsmentioning

confidence: 99%

Genomic Analysis of Pure Cultures and Communities

Toshchakov

Kublanov

Messina

et al. 2015

Springer Protocols Handbooks

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Oil-degrading bacteria and their communities have been in focus of the research for the past few decades for a number of reasons. First, this allows filling the voids in our knowledge on the major mechanisms facilitating the oil biodegradation, to identify the key organisms playing significant roles in these processes and, furthermore, to learn how to effectively manage their performance in situ to enhance the rates of biodegradation. Historically, of a particular interest for genomics studies were the so-called marine hydrocarbonoclastic bacteria, the petroleum biodegradation specialists with very restricted substrate profiles. Apart from their utility in environmental cleanup, oil-degrading bacteria possess an array of enzymes and pathways of a great potential for further biotechnological applications: biopolymers production, oxidationreduction reactions, chiral synthesis, biosurfactant production, etc. In this chapter we describe current methods for genome and metagenome sequencing and annotation. Importantly, these are not limited to a particular group of microorganisms and are thus almost universally applicable. We focused exclusively on the methods and tools that everyone could use on a non-commercial basis. Due to the availability of numerous alternative methods and approaches, we have arbitrarily chosen reliable protocols that can be used by a common biologist without a great deal of computational biology background.

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“…Recently, two bacterial sRNA databases were developed: (i) sRNAdb, which focused exclusively on Gram-positive bacteria (Pischimarov et al 2012) but provides only 39 sRNA sequences for S. aureus; (ii) BSRD is a generalist bacterial sRNA database with >700 species included (Li et al 2013). Finally, RNAspace.org is a platform devoted to the prediction, annotation, and analysis of noncoding RNA but does not provide data set (Cros et al 2011). In S. aureus and more generally in the Staphylococcal genus, a unified sRNA nomenclature is lacking, while many redundancies, as single sequence described under several IDs, and potential misannotated sRNAs (e.g., repeated sequences, mRNA leader or trailer sequences) would require an in-depth manual cleaning.…”

Section: Introductionmentioning

confidence: 99%

SRD: a Staphylococcus regulatory RNA database

Sassi

Augagneur

Mauro

et al. 2015

RNA

108

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An overflow of regulatory RNAs (sRNAs) was identified in a wide range of bacteria. We designed and implemented a new resource for the hundreds of sRNAs identified in Staphylococci, with primary focus on the human pathogen Staphylococcus aureus. The "Staphylococcal Regulatory RNA Database" (SRD, http://srd.genouest.org/) compiled all published data in a single interface including genetic locations, sequences and other features. SRD proposes novel and simplified identifiers for Staphylococcal regulatory RNAs (srn) based on the sRNA's genetic location in S. aureus strain N315 which served as a reference. From a set of 894 sequences and after an in-depth cleaning, SRD provides a list of 575 srn exempt of redundant sequences. For each sRNA, their experimental support(s) is provided, allowing the user to individually assess their validity and significance. RNAseq analysis performed on strains N315, NCTC8325, and Newman allowed us to provide further details, upgrade the initial annotation, and identified 159 RNA-seq independent transcribed sRNAs. The lists of 575 and 159 sRNAs sequences were used to predict the number and location of srns in 18 S. aureus strains and 10 other Staphylococci. A comparison of the srn contents within 32 Staphylococcal genomes revealed a poor conservation between species. In addition, sRNA structure predictions obtained with MFold are accessible. A BLAST server and the intaRNA program, which is dedicated to target prediction, were implemented. SRD is the first sRNA database centered on a genus; it is a user-friendly and scalable device with the possibility to submit new sequences that should spread in the literature.

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RNAspace.org: An integrated environment for the prediction, annotation, and analysis of ncRNA

Cited by 29 publications

References 63 publications

A computational strategy for the search of regulatory small RNAs in Actinobacillus pleuropneumoniae

A computational strategy for the search of regulatory small RNAs in Actinobacillus pleuropneumoniae

Genomic Analysis of Pure Cultures and Communities

SRD: a Staphylococcus regulatory RNA database

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