title: Alignments anchored on genomic landmarks can aid in the identification of regulatory elements.
abstract: BACKGROUND
  The transcription start site (TSS) has been located for an increasing number of genes across several organisms. Statistical tests have shown that some cis-acting regulatory elements have positional preferences with respect to the TSS, but few strategies have emerged for locating elements by their positional preferences. This paper elaborates such a strategy. First, we align promoter regions without gaps, anchoring the alignment on each promoter's TSS. Second, we apply a novel word-specific mask. Third, we apply a clustering test related to gapless BLAST statistics. The test examines whether any specific word is placed unusually consistently with respect to the TSS. Finally, our program A-GLAM, an extension of the GLAM program, uses significant word positions as new 'anchors' to realign the sequences. A Gibbs sampling algorithm then locates putative cis-acting regulatory elements. Usually, Gibbs sampling requires a preliminary masking step, to avoid convergence onto a dominant but uninteresting signal from a DNA repeat. However, since the positional anchors focus A-GLAM on the motif of interest, masking DNA repeats during Gibbs sampling becomes unnecessary.
  
  
  RESULTS
  In a set of human DNA sequences with experimentally characterized TSSs, the placement of 791 octonucleotide words was unusually consistent (multiple test corrected P < 0.05). Alignments anchored on these words sometimes located statistically significant motifs inaccessible to GLAM or AlignACE.
  
  
  BACKGROUND
  The A-GLAM program and a list of statistically significant words are available at ftp://ftp.ncbi.nih.gov/pub/spouge/papers/archive/AGLAM/.
authors.affiliation: Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health Building 38A, 8600 Rockville Pike, Bethesda, MD 20894-6075, USA.
authors.forename: Kannan
authors.initials: K
authors.lastname: Tharakaraman
authors.forename: Leonardo
authors.initials: L
authors.lastname: Mariño-Ramírez
authors.forename: Sergey
authors.initials: S
authors.lastname: Sheetlin
authors.forename: David
authors.initials: D
authors.lastname: Landsman
authors.forename: John L
authors.initials: JL
authors.lastname: Spouge
mesh_terms: D020816:Amino Acid Motifs; D001483:Base Sequence; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D004247:DNA / Q000737:chemistry; D030562:Databases, Protein; D023281:Genomics / Q000379:methods*; D006801:Humans; D015233:Models, Statistical; D008969:Molecular Sequence Data; D009711:Nucleotides / Q000737:chemistry; D011401:Promoter Regions, Genetic; D012045:Regulatory Sequences, Nucleic Acid; D016415:Sequence Alignment; D012984:Software; D024363:Transcription Initiation Site
chemical_list: D009711:Nucleotides; D004247:DNA