title: An advanced bioinformatics approach for analyzing RNA-seq data reveals sigma H-dependent regulation of competence genes in Listeria monocytogenes.
abstract: BACKGROUND
  Alternative σ factors are important transcriptional regulators in bacteria. While σ(B) has been shown to control a large regulon and play important roles in stress response and virulence in the pathogen Listeria monocytogenes, the function of σ(H) has not yet been well defined in Listeria, even though σ(H) controls a large regulon in the closely related non-pathogenic Bacillus subtilis.
  
  
  RESULTS
  Using RNA-seq characterization of a L. monocytogenes strain with deletions of all 4 genes encoding alternative σ factors (ΔBCHL), which was further modified to overexpress sigH (ΔBCHL::P rha -sigH), we identified 6 transcription units (TUs) that are transcribed from σ(H)-dependent promoters. Five of these TUs had not been previously identified. Identification of these promoters was facilitated by use of a bio-informatics approach that compared normalized RNA-seq coverage (NRC), between ΔBCHL::P rha -sigH and a ΔBCHL control, using sliding windows of 51 nt along the whole genome rather than comparing NRC calculated only for whole genes. Interestingly, we found that three operons that encode competence genes (comGABCDEFG, comEABC, coiA) are transcribed from σ(H)-dependent promoters. While these promoters were highly conserved in L. monocytogenes, none of them were found in all Listeria spp. and coiA and its σ(H)-dependent promoter were only found in L. monocytogenes.
  
  
  CONCLUSIONS
  Our data indicate that a number of L. monocytogenes competence genes are regulated by σ(H). This σ(H)-dependent regulation of competence related genes is conserved in the pathogen L. monocytogenes, but not in other non-pathogenic Listeria strains. Combined with prior data that indicated a role of σ(H) in virulence in a mouse model, this suggests a possible novel role of σ(H)-dependent competence genes in L. monocytogenes virulence. Development and implementation of a sliding window approach to identify differential transcription using RNA-seq data, not only allowed for identification of σ(H)-dependent promoters, but also provides a general approach for sensitive identification of differentially transcribed promoters and genes, particularly for genes that are transcribed from multiple promoter elements only some of which show differential transcription.
authors.affiliation: Department of Food Science, Cornell University, Ithaca, NY, 14853, USA. yl2383@cornell.edu.
authors.forename: Yichang
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Department of Food Science, Cornell University, Ithaca, NY, 14853, USA. rho2@cornell.edu.
authors.forename: Renato Hohl
authors.initials: RH
authors.lastname: Orsi
authors.affiliation: Department of Food Science, Cornell University, Ithaca, NY, 14853, USA. kjb4@cornell.edu.
authors.forename: Kathryn Jean
authors.initials: KJ
authors.lastname: Boor
authors.affiliation: Department of Food Science, Cornell University, Ithaca, NY, 14853, USA. mw16@cornell.edu.
authors.forename: Martin
authors.initials: M
authors.lastname: Wiedmann
authors.affiliation: Department of Food Science, Cornell University, Ithaca, NY, 14853, USA. vg93@cornell.edu.
authors.forename: Veronica
authors.initials: V
authors.lastname: Guariglia-Oropeza
mesh_terms: D001483:Base Sequence; D019295:Computational Biology / Q000379:methods*; D017124:Conserved Sequence; D015964:Gene Expression Regulation, Bacterial; D005798:Genes, Bacterial; D008089:Listeria monocytogenes / Q000235:genetics*; D059372:Nucleotide Motifs; D009876:Operon; D056510:Position-Specific Scoring Matrices; D011401:Promoter Regions, Genetic; D012329:RNA, Bacterial; D016415:Sequence Alignment; D017423:Sequence Analysis, RNA; D012808:Sigma Factor / Q000235:genetics* / Q000378:metabolism
chemical_list: D012329:RNA, Bacterial; D012808:Sigma Factor