Dataset Information

High-throughput, kingdom-wide prediction and annotation of bacterial non-coding RNAs.

ABSTRACT: Diverse bacterial genomes encode numerous small non-coding RNAs (sRNAs) that regulate myriad biological processes. While bioinformatic algorithms have proven effective in identifying sRNA-encoding loci, the lack of tools and infrastructure with which to execute these computationally demanding algorithms has limited their utilization. Genome-wide predictions of sRNA-encoding genes have been conducted in less than 3% of all sequenced bacterial strains, leading to critical gaps in current annotations. The relative paucity of genome-wide sRNA prediction represents a critical gap in current annotations of bacterial genomes and has limited examination of larger issues in sRNA biology, such as sRNA evolution.We have developed and deployed SIPHT, a high throughput computational tool that utilizes workflow management and distributed computing to effectively conduct kingdom-wide predictions and annotations of intergenic sRNA-encoding genes. Candidate sRNA-encoding loci are identified based on the presence of putative Rho-independent terminators downstream of conserved intergenic sequences, and each locus is annotated for several features, including conservation in other species, association with one of several transcription factor binding sites and homology to any of over 300 previously identified sRNAs and cis-regulatory RNA elements. Using SIPHT, we conducted searches for putative sRNA-encoding genes in all 932 bacterial replicons in the NCBI database. These searches yielded nearly 60% of previously confirmed sRNAs, hundreds of previously annotated cis-encoded regulatory RNA elements such as riboswitches, and over 45,000 novel candidate intergenic loci.Candidate loci were identified across all branches of the bacterial evolutionary tree, suggesting a central and ubiquitous role for RNA-mediated regulation among bacterial species. Annotation of candidate loci by SIPHT provides clues into the potential biological function of thousands of previously confirmed and candidate regulatory RNAs and affords new insights into the evolution of bacterial riboregulation.

SUBMITTER: Livny J

PROVIDER: S-EPMC2527527 | biostudies-literature | 2008 Sep

REPOSITORIES: biostudies-literature

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High-throughput, kingdom-wide prediction and annotation of bacterial non-coding RNAs.

Livny Jonathan J Teonadi Hidayat H Livny Miron M Waldor Matthew K MK

PloS one 20080912 9

<h4>Background</h4>Diverse bacterial genomes encode numerous small non-coding RNAs (sRNAs) that regulate myriad biological processes. While bioinformatic algorithms have proven effective in identifying sRNA-encoding loci, the lack of tools and infrastructure with which to execute these computationally demanding algorithms has limited their utilization. Genome-wide predictions of sRNA-encoding genes have been conducted in less than 3% of all sequenced bacterial strains, leading to critical gaps i ...[more]

PMID: 18787707

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Project description:BACKGROUND: Small non-coding RNAs (sRNAs) play key roles in plant development, growth and responses to biotic and abiotic stresses. At least four classes of sRNAs have been well characterized in plants, including repeat-associated siRNAs (rasiRNAs), microRNAs (miRNAs), trans-acting siRNAs (tasiRNAs) and natural antisense transcript-derived siRNAs. Chinese fir (Cunninghamia lanceolata) is one of the most important coniferous evergreen tree species in China. No sRNA from Chinese fir has been described to date. RESULTS: To obtain sRNAs in Chinese fir, we sequenced a sRNA library generated from seeds, seedlings, leaves, stems and calli, using Illumina high throughput sequencing technology. A comprehensive set of sRNAs were acquired, including conserved and novel miRNAs, rasiRNAs and tasiRNAs. With BLASTN and MIREAP we identified a total of 115 conserved miRNAs comprising 40 miRNA families and one novel miRNA with precursor sequence. The expressions of 16 conserved and one novel miRNAs and one tasiRNA were detected by RT-PCR. Utilizing real time RT-PCR, we revealed that four conserved and one novel miRNAs displayed developmental stage-specific expression patterns in Chinese fir. In addition, 209 unigenes were predicted to be targets of 30 Chinese fir miRNA families, of which five target genes were experimentally verified by 5' RACE, including a squamosa promoter-binding protein gene, a pentatricopeptide (PPR) repeat-containing protein gene, a BolA-like family protein gene, AGO1 and a gene of unknown function. We also demonstrated that the DCL3-dependent rasiRNA biogenesis pathway, which had been considered absent in conifers, existed in Chinese fir. Furthermore, the miR390-TAS3-ARF regulatory pathway was elucidated. CONCLUSIONS: We unveiled a complex population of sRNAs in Chinese fir through high throughput sequencing. This provides an insight into the composition and function of sRNAs in Chinese fir and sheds new light on land plant sRNA evolution.

Dataset Information

High-throughput, kingdom-wide prediction and annotation of bacterial non-coding RNAs.

Publications

High-throughput, kingdom-wide prediction and annotation of bacterial non-coding RNAs.

Similar Datasets

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