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Comparative genomics boosts target prediction for bacterial small RNAs.

ABSTRACT: Small RNAs (sRNAs) constitute a large and heterogeneous class of bacterial gene expression regulators. Much like eukaryotic microRNAs, these sRNAs typically target multiple mRNAs through short seed pairing, thereby acting as global posttranscriptional regulators. In some bacteria, evidence for hundreds to possibly more than 1,000 different sRNAs has been obtained by transcriptome sequencing. However, the experimental identification of possible targets and, therefore, their confirmation as functional regulators of gene expression has remained laborious. Here, we present a strategy that integrates phylogenetic information to predict sRNA targets at the genomic scale and reconstructs regulatory networks upon functional enrichment and network analysis (CopraRNA, for Comparative Prediction Algorithm for sRNA Targets). Furthermore, CopraRNA precisely predicts the sRNA domains for target recognition and interaction. When applied to several model sRNAs, CopraRNA revealed additional targets and functions for the sRNAs CyaR, FnrS, RybB, RyhB, SgrS, and Spot42. Moreover, the mRNAs gdhA, lrp, marA, nagZ, ptsI, sdhA, and yobF-cspC were suggested as regulatory hubs targeted by up to seven different sRNAs. The verification of many previously undetected targets by CopraRNA, even for extensively investigated sRNAs, demonstrates its advantages and shows that CopraRNA-based analyses can compete with experimental target prediction approaches. A Web interface allows high-confidence target prediction and efficient classification of bacterial sRNAs.

SUBMITTER: Wright PR

PROVIDER: S-EPMC3773804 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature

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Comparative genomics boosts target prediction for bacterial small RNAs.

Wright Patrick R PR Richter Andreas S AS Papenfort Kai K Mann Martin M Vogel Jörg J Hess Wolfgang R WR Backofen Rolf R Georg Jens J

Proceedings of the National Academy of Sciences of the United States of America 20130826 37

Small RNAs (sRNAs) constitute a large and heterogeneous class of bacterial gene expression regulators. Much like eukaryotic microRNAs, these sRNAs typically target multiple mRNAs through short seed pairing, thereby acting as global posttranscriptional regulators. In some bacteria, evidence for hundreds to possibly more than 1,000 different sRNAs has been obtained by transcriptome sequencing. However, the experimental identification of possible targets and, therefore, their confirmation as functi ...[more]

PMID: 23980183

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Project description:Small RNAs (sRNAs) posttranscriptionally regulate mRNA targets, typically under conditions of environmental stress. Although hundreds of sRNAs have been discovered in diverse bacterial genomes, most sRNAs remain uncharacterized, even in model organisms. Identification of mRNA targets directly regulated by sRNAs is rate-limiting for sRNA functional characterization. To address this, we developed a computational pipeline that we named SPOT for sRNA target prediction organizing tool. SPOT incorporates existing computational tools to search for sRNA binding sites, allows filtering based on experimental data, and organizes the results into a standardized report. SPOT sensitivity (number of correctly predicted targets/number of total known targets) was equal to or exceeded any individual method when used on 12 characterized sRNAs. Using SPOT, we generated a set of target predictions for the sRNA RydC, which was previously shown to positively regulate cfa mRNA, encoding cyclopropane fatty acid synthase. SPOT identified cfa along with additional putative mRNA targets, which we then tested experimentally. Our results demonstrated that in addition to cfa mRNA, RydC also regulates trpE and pheA mRNAs, which encode aromatic amino acid biosynthesis enzymes. Our results suggest that SPOT can facilitate elucidation of sRNA target regulons to expand our understanding of the many regulatory roles played by bacterial sRNAs.IMPORTANCE Small RNAs (sRNAs) regulate gene expression in diverse bacteria by interacting with mRNAs to change their structure, stability, or translation. Hundreds of sRNAs have been identified in bacteria, but characterization of their regulatory functions is limited by difficulty with sensitive and accurate identification of mRNA targets. Thus, new robust methods of bacterial sRNA target identification are in demand. Here, we describe our small RNA target prediction organizing tool (SPOT), which streamlines the process of sRNA target prediction by providing a single pipeline that combines available computational prediction tools with customizable results filtering based on experimental data. SPOT allows the user to rapidly produce a prioritized list of predicted sRNA-target mRNA interactions that serves as a basis for further experimental characterization. This tool will facilitate elucidation of sRNA regulons in bacteria, allowing new discoveries regarding the roles of sRNAs in bacterial stress responses and metabolic regulation.

Project description:BackgroundSmall nucleolar (sno)RNAs are required for posttranscriptional processing and modification of ribosomal, spliceosomal and messenger RNAs. Their presence in both eukaryotes and archaea indicates that snoRNAs are evolutionarily ancient. The location of some snoRNAs within the introns of ribosomal protein genes has been suggested to belie an RNA world origin, with the exons of the earliest protein-coding genes having evolved around snoRNAs after the advent of templated protein synthesis. Alternatively, this intronic location may reflect more recent selection for coexpression of snoRNAs and ribosomal components, ensuring rRNA modification by snoRNAs during ribosome synthesis. To gain insight into the evolutionary origins of this genetic organization, we examined the antiquity of snoRNA families and the stability of their genomic location across 44 eukaryote genomes.ResultsWe report that dozens of snoRNA families are traceable to the Last Eukaryotic Common Ancestor (LECA), but find only weak similarities between the oldest eukaryotic snoRNAs and archaeal snoRNA-like genes. Moreover, many of these LECA snoRNAs are located within the introns of host genes independently traceable to the LECA. Comparative genomic analyses reveal the intronic location of LECA snoRNAs is not ancestral however, suggesting the pattern we observe is the result of ongoing intragenomic mobility. Analysis of human transcriptome data indicates that the primary requirement for hosting intronic snoRNAs is a broad expression profile. Consistent with ongoing mobility across broadly-expressed genes, we report a case of recent migration of a non-LECA snoRNA from the intron of a ubiquitously expressed non-LECA host gene into the introns of two LECA genes during the evolution of primates.ConclusionsOur analyses show that snoRNAs were a well-established family of RNAs at the time when eukaryotes began to diversify. While many are intronic, this association is not evolutionarily stable across the eukaryote tree; ongoing intragenomic mobility has erased signal of their ancestral gene organization, and neither introns-first nor evolved co-expression adequately explain our results. We therefore present a third model - constrained drift - whereby individual snoRNAs are intragenomically mobile and may occupy any genomic location from which expression satisfies phenotype.

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Comparative genomics boosts target prediction for bacterial small RNAs.

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Comparative genomics boosts target prediction for bacterial small RNAs.

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