title: High-throughput, kingdom-wide prediction and annotation of bacterial non-coding RNAs.
abstract: BACKGROUND
  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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Channing Laboratories, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America. jlivny@rics.bwh.harvard.edu
authors.forename: Jonathan
authors.initials: J
authors.lastname: Livny
authors.forename: Hidayat
authors.initials: H
authors.lastname: Teonadi
authors.forename: Miron
authors.initials: M
authors.lastname: Livny
authors.forename: Matthew K
authors.initials: MK
authors.lastname: Waldor
mesh_terms: D000465:Algorithms; D001419:Bacteria / Q000235:genetics; D001665:Binding Sites; D002138:Calibration; D019295:Computational Biology / Q000379:methods; D019143:Evolution, Molecular; D005798:Genes, Bacterial; D016680:Genome, Bacterial; D023281:Genomics / Q000379:methods*; D016366:Open Reading Frames; D012329:RNA, Bacterial / Q000737:chemistry* / Q000235:genetics*; D022661:RNA, Untranslated / Q000235:genetics*; D015203:Reproducibility of Results; D012984:Software
chemical_list: D012329:RNA, Bacterial; D022661:RNA, Untranslated
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