@Article{Wright_Richter_Papenfort-Compa_genom_boost-PNAS2013,
  author =	 {Wright, Patrick R. and Richter, Andreas S. and Papenfort, 
                  Kai and Mann, Martin and Vogel, Jorg and Hess, Wolfgang R. 
                  and Backofen, Rolf and Georg, Jens},
  title =	 {Comparative genomics boosts target prediction for bacterial 
                  small {RNAs}},
  journal =	 PNAS,
  year =	 2013,
  volume =	 110,
  number =	 37,
  pages =	 {E3487-96},
  user =	 {wrightp},
  pmid =	 23980183,
  doi = 	 {10.1073/pnas.1303248110},
  issn = 	 {1091-6490},
  issn = 	 {0027-8424},
  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.}
}