title: An empirical strategy to detect bacterial transcript structure from directional RNA-seq transcriptome data.
abstract: BACKGROUND
  As sequencing costs are being lowered continuously, RNA-seq has gradually been adopted as the first choice for comparative transcriptome studies with bacteria. Unlike microarrays, RNA-seq can directly detect cDNA derived from mRNA transcripts at a single nucleotide resolution. Not only does this allow researchers to determine the absolute expression level of genes, but it also conveys information about transcript structure. Few automatic software tools have yet been established to investigate large-scale RNA-seq data for bacterial transcript structure analysis.
  
  
  RESULTS
  In this study, 54 directional RNA-seq libraries from Salmonella serovar Typhimurium (S. Typhimurium) 14028s were examined for potential relationships between read mapping patterns and transcript structure. We developed an empirical method, combined with statistical tests, to automatically detect key transcript features, including transcriptional start sites (TSSs), transcriptional termination sites (TTSs) and operon organization. Using our method, we obtained 2,764 TSSs and 1,467 TTSs for 1331 and 844 different genes, respectively. Identification of TSSs facilitated further discrimination of 215 putative sigma 38 regulons and 863 potential sigma 70 regulons. Combining the TSSs and TTSs with intergenic distance and co-expression information, we comprehensively annotated the operon organization in S. Typhimurium 14028s.
  
  
  CONCLUSIONS
  Our results show that directional RNA-seq can be used to detect transcriptional borders at an acceptable resolution of ±10-20 nucleotides. Technical limitations of the RNA-seq procedure may prevent single nucleotide resolution. The automatic transcript border detection methods, statistical models and operon organization pipeline that we have described could be widely applied to RNA-seq studies in other bacteria. Furthermore, the TSSs, TTSs, operons, promoters and unstranslated regions that we have defined for S. Typhimurium 14028s may constitute valuable resources that can be used for comparative analyses with other Salmonella serotypes.
authors.affiliation: Vaccine and Infectious Disease Organization-International Vaccine Centre, University of Saskatchewan, Saskatoon, SK, Canada. yejun.wang@gmail.com.
authors.forename: Yejun
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Vaccine and Infectious Disease Organization-International Vaccine Centre, University of Saskatchewan, Saskatoon, SK, Canada. keith.mackenzie@usask.ca.|Department of Microbiology and Immunology, University of Saskatchewan, Saskatoon, SK, Canada. keith.mackenzie@usask.ca.
authors.forename: Keith D
authors.initials: KD
authors.lastname: MacKenzie
authors.affiliation: Vaccine and Infectious Disease Organization-International Vaccine Centre, University of Saskatchewan, Saskatoon, SK, Canada. aaron.white@usask.ca.|Department of Microbiology and Immunology, University of Saskatchewan, Saskatoon, SK, Canada. aaron.white@usask.ca.
authors.forename: Aaron P
authors.initials: AP
authors.lastname: White
mesh_terms: D001426:Bacterial Proteins / Q000737:chemistry / Q000378:metabolism; D001483:Base Sequence; D012321:DNA-Directed RNA Polymerases / Q000737:chemistry / Q000378:metabolism; D015723:Gene Library; D009876:Operon; D011401:Promoter Regions, Genetic; D012333:RNA, Messenger / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D012486:Salmonella typhimurium / Q000235:genetics*; D012808:Sigma Factor / Q000737:chemistry / Q000378:metabolism; D013728:Terminator Regions, Genetic; D024363:Transcription Initiation Site; D014158:Transcription, Genetic; D059467:Transcriptome
chemical_list: D001426:Bacterial Proteins; D012333:RNA, Messenger; D012808:Sigma Factor; C081775:RNA polymerase sigma 70; D012321:DNA-Directed RNA Polymerases