title: Mulan: multiple-sequence local alignment and visualization for studying function and evolution.
abstract: Multiple-sequence alignment analysis is a powerful approach for understanding phylogenetic relationships, annotating genes, and detecting functional regulatory elements. With a growing number of partly or fully sequenced vertebrate genomes, effective tools for performing multiple comparisons are required to accurately and efficiently assist biological discoveries. Here we introduce Mulan (http://mulan.dcode.org/), a novel method and a network server for comparing multiple draft and finished-quality sequences to identify functional elements conserved over evolutionary time. Mulan brings together several novel algorithms: the TBA multi-aligner program for rapid identification of local sequence conservation, and the multiTF program for detecting evolutionarily conserved transcription factor binding sites in multiple alignments. In addition, Mulan supports two-way communication with the GALA database; alignments of multiple species dynamically generated in GALA can be viewed in Mulan, and conserved transcription factor binding sites identified with Mulan/multiTF can be integrated and overlaid with extensive genome annotation data using GALA. Local multiple alignments computed by Mulan ensure reliable representation of short- and large-scale genomic rearrangements in distant organisms. Mulan allows for interactive modification of critical conservation parameters to differentially predict conserved regions in comparisons of both closely and distantly related species. We illustrate the uses and applications of the Mulan tool through multispecies comparisons of the GATA3 gene locus and the identification of elements that are conserved in a different way in avians than in other genomes, allowing speculation on the evolution of birds. Source code for the aligners and the aligner-evaluation software can be freely downloaded from http://www.bx.psu.edu/miller_lab/.
authors.affiliation: Energy, Environment, Biology and Institutional Computing, Lawrence Livermore National Laboratory, Livermore, California 94550, USA. ovcharenko1@llnl.gov
authors.forename: Ivan
authors.initials: I
authors.lastname: Ovcharenko
authors.forename: Gabriela G
authors.initials: GG
authors.lastname: Loots
authors.forename: Belinda M
authors.initials: BM
authors.lastname: Giardine
authors.forename: Minmei
authors.initials: M
authors.lastname: Hou
authors.forename: Jian
authors.initials: J
authors.lastname: Ma
authors.forename: Ross C
authors.initials: RC
authors.lastname: Hardison
authors.forename: Lisa
authors.initials: L
authors.lastname: Stubbs
authors.forename: Webb
authors.initials: W
authors.lastname: Miller
mesh_terms: D000818:Animals; D001001:Anura / Q000235:genetics; D001665:Binding Sites / Q000235:genetics; D002645:Chickens / Q000235:genetics; D019295:Computational Biology / Q000379:methods; D003196:Computer Graphics; D017124:Conserved Sequence / Q000235:genetics; D004268:DNA-Binding Proteins / Q000235:genetics; D019143:Evolution, Molecular; D005399:Fishes / Q000235:genetics; D050990:GATA3 Transcription Factor; D016678:Genome; D015894:Genome, Human; D006801:Humans; D051379:Mice; D010802:Phylogeny; D051381:Rats; D016415:Sequence Alignment / Q000379:methods*; D012689:Sequence Homology, Nucleic Acid; D012984:Software; D015534:Trans-Activators / Q000235:genetics
chemical_list: D004268:DNA-Binding Proteins; D050990:GATA3 Transcription Factor; C494749:GATA3 protein, human; C494748:Gata3 protein, mouse; D015534:Trans-Activators