title: Phylogenomic identification of regulatory sequences in bacteria: an analysis of statistical power and an application to Borrelia burgdorferi sensu lato.
abstract: Phylogenomic footprinting is an approach for ab initio identification of genome-wide regulatory elements in bacterial species based on sequence conservation. The statistical power of the phylogenomic approach depends on the degree of sequence conservation, the length of regulatory elements, and the level of phylogenetic divergence among genomes. Building on an earlier model, we propose a binomial model that uses synonymous tree lengths as neutral expectations for determining the statistical significance of conserved intergenic spacer (IGS) sequences. Simulations show that the binomial model is robust to variations in the value of evolutionary parameters, including base frequencies and the transition-to-transversion ratio. We used the model to search for regulatory sequences in the Lyme disease species group (Borrelia burgdorferi sensu lato) using 23 genomes. The model indicates that the currently available set of Borrelia genomes would not yield regulatory sequences shorter than five bases, suggesting that genome sequences of additional B. burgdorferi sensu lato species are needed. Nevertheless, we show that previously known regulatory elements are indeed strongly conserved in sequence or structure across these Borrelia species. Further, we predict with sufficient confidence two new RpoS binding sites, 39 promoters, 19 transcription terminators, 28 noncoding RNAs, and four sets of coregulated genes. These putative cis- and trans-regulatory elements suggest novel, Borrelia-specific mechanisms regulating the transition between the tick and host environments, a key adaptation and virulence mechanism of B. burgdorferi. Alignments of IGS sequences are available on BorreliaBase.org, an online database of orthologous open reading frame (ORF) and IGS sequences in Borrelia.
  
  
  OBJECTIVE
  While bacterial genomes contain mostly protein-coding genes, they also house DNA sequences regulating the expression of these genes. Gene regulatory sequences tend to be conserved during evolution. By sequencing and comparing related genomes, one can therefore identify regulatory sequences in bacteria based on sequence conservation. Here, we describe a statistical framework by which one may determine how many genomes need to be sequenced and at what level of evolutionary relatedness in order to achieve a high level of statistical significance. We applied the framework to Borrelia burgdorferi, the Lyme disease agent, and identified a large number of candidate regulatory sequences, many of which are known to be involved in regulating the phase transition between the tick vector and mammalian hosts.
authors: Che L
authors: CL
authors: Martin
authors: Department of Biology, The Graduate Center, City University of New York, New York, USA.
authors: Che I
authors: CI
authors: Martin
authors: Department of Biology, The Graduate Center, City University of New York, New York, USA.
authors: Tika Y
authors: TY
authors: Sukarna
authors: Department of Biological Sciences and Center for Translational and Basic Research, Hunter College, City University of New York, New York, USA.
authors: Saymon
authors: S
authors: Akther
authors: Department of Biological Sciences and Center for Translational and Basic Research, Hunter College, City University of New York, New York, USA.
authors: Girish
authors: G
authors: Ramrattan
authors: Department of Biological Sciences and Center for Translational and Basic Research, Hunter College, City University of New York, New York, USA.
authors: Pedro
authors: P
authors: Pagan
authors: Department of Biological Sciences and Center for Translational and Basic Research, Hunter College, City University of New York, New York, USA.
authors: Lia
authors: L
authors: Di
authors: Institute for Genome Sciences, University of Maryland BioPark, Baltimore, Maryland, USA.
authors: Emmanuel F
authors: EF
authors: Mongodin
authors: Institute for Genome Sciences, University of Maryland BioPark, Baltimore, Maryland, USA.
authors: Claire M
authors: CM
authors: Fraser
authors: Department of Medicine, New Jersey Medical School, Rutgers, the State University of New Jersey, Newark, New Jersey, USA.
authors: Steven E
authors: SE
authors: Schutzer
authors: Department of Medicine, Health Science Center, Stony Brook University, Stony Brook, New York, USA.
authors: Benjamin J
authors: BJ
authors: Luft
authors: Department of Pathology, Division of Molecular Cell Biology and Immunology, University of Utah School of Medicine, Salt Lake City, Utah, USA.
authors: Sherwood R
authors: SR
authors: Casjens
authors: weigang@genectr.hunter.cuny.edu.
authors: Wei-Gang
authors: http://orcid.org/0000-0003-4585-1872
authors: WG
authors: Qiu
mesh_terms: D056808:Biostatistics / Q000379:methods; D015748:Borrelia burgdorferi Group / Q000235:genetics*; D019295:Computational Biology / Q000379:methods*; D017124:Conserved Sequence; D021901:DNA, Intergenic; D012045:Regulatory Sequences, Nucleic Acid
chemical_list: D021901:DNA, Intergenic