title: Fast and sensitive multiple alignment of large genomic sequences.
abstract: BACKGROUND
  Genomic sequence alignment is a powerful method for genome analysis and annotation, as alignments are routinely used to identify functional sites such as genes or regulatory elements. With a growing number of partially or completely sequenced genomes, multiple alignment is playing an increasingly important role in these studies. In recent years, various tools for pair-wise and multiple genomic alignment have been proposed. Some of them are extremely fast, but often efficiency is achieved at the expense of sensitivity. One way of combining speed and sensitivity is to use an anchored-alignment approach. In a first step, a fast search program identifies a chain of strong local sequence similarities. In a second step, regions between these anchor points are aligned using a slower but more accurate method.
  
  
  RESULTS
  Herein, we present CHAOS, a novel algorithm for rapid identification of chains of local pair-wise sequence similarities. Local alignments calculated by CHAOS are used as anchor points to improve the running time of DIALIGN, a slow but sensitive multiple-alignment tool. We show that this way, the running time of DIALIGN can be reduced by more than 95% for BAC-sized and longer sequences, without affecting the quality of the resulting alignments. We apply our approach to a set of five genomic sequences around the stem-cell-leukemia (SCL) gene and demonstrate that exons and small regulatory elements can be identified by our multiple-alignment procedure.
  
  
  CONCLUSIONS
  We conclude that the novel CHAOS local alignment tool is an effective way to significantly speed up global alignment tools such as DIALIGN without reducing the alignment quality. We likewise demonstrate that the DIALIGN/CHAOS combination is able to accurately align short regulatory sequences in distant orthologues.
authors.affiliation: Department of Computer Science, Stanford University, Stanford, CA 94305, USA. brudno@cs.stanford.edu
authors.forename: Michael
authors.initials: M
authors.lastname: Brudno
authors.forename: Michael
authors.initials: M
authors.lastname: Chapman
authors.forename: Berthold
authors.initials: B
authors.lastname: Göttgens
authors.forename: Serafim
authors.initials: S
authors.lastname: Batzoglou
authors.forename: Burkhard
authors.initials: B
authors.lastname: Morgenstern
mesh_terms: D000465:Algorithms; D000818:Animals; D002645:Chickens / Q000235:genetics; D019295:Computational Biology / Q000706:statistics & numerical data; D004273:DNA, Neoplasm / Q000235:genetics; D052138:Genes, Neoplasm / Q000235:genetics; D016678:Genome; D006801:Humans; D007938:Leukemia / Q000235:genetics / Q000473:pathology; D051379:Mice; D051381:Rats; D012045:Regulatory Sequences, Nucleic Acid / Q000235:genetics; D012680:Sensitivity and Specificity; D016415:Sequence Alignment / Q000379:methods* / Q000706:statistics & numerical data; D012984:Software; D012986:Software Validation; D013234:Stem Cells / Q000473:pathology; D023721:Tetraodontiformes / Q000235:genetics; D015027:Zebrafish / Q000235:genetics
chemical_list: D004273:DNA, Neoplasm