DIALIGN : multiple DNA and protein sequence alignment at BiBiServ

DIALIGN is a widely used software tool for multiple DNA and protein sequence alignment. The program combines local andglobal alignment featuresandcan therefore be applied to sequence data that cannot be correctly aligned by more traditional approaches. DIALIGN is available online through Bielefeld Bioinformatics Server (BiBiServ). The downloadable version of the program offers several new program features.Tocompare theoutputofdifferentalignment programs, we developed the program AltAVisT. Our software is available at http://bibiserv.TechFak. Uni-Bielefeld.DE/dialign/. Multiple sequence alignment is of fundamental importance in all aspects of DNA and protein sequence analysis. It is used as a first and critical step in protein structure prediction and classification, phylogenetic reconstruction, analysis of protein domains and identification of functional sites in genomic sequences, to mention just a few important applications. Development and improvement of multi-alignment methodology is therefore crucial for all branches of molecular biology and genomics, see (1) for an overview on existing multiplealignment approaches. A widely used software tool for DNA and protein multiple alignment is DIALIGN (2,3). This program differs in various aspects from more traditional multialignment algorithms. Those traditional approaches are generally classified as either global or local methods. This is not appropriate for distantly related sequences where multiple conserved domains may be separated by non-related parts of the sequences. In such situations neither purely global nor purely local methods can produce meaningful alignments. THE DIALIGN APPROACH In contrast to standard methods, DIALIGN combines both global and local alignment features. It assembles pair-wise and multiple alignments from local fragment alignments or fragments. More precisely, alignments are composed of equallength segment pairs exhibiting some statistically significant similarity. Note that these segment pairs are not directly visible to the user; they are used internally by the program to construct alignments from given input data sets. Gaps are not penalized, and the program does not try to align parts of the sequences that do not show significant similarity to other input sequences. Consequently, for sequence sets with local homology only, alignments are restricted to those homologies and the program ignores non-related parts of the sequences. In such a situation, DIALIGN returns a local alignment. For globally related sequences, however, the program finds segment pairs (fragments) covering the entire length of the sequences, so it returns a full global alignment. A mixture of global and local alignments is created for sequence families where islands of local similarity are separated by unrelated sequence. Here, the program aligns these similarities and leaves non-related sequence parts unaligned. As a result, DIALIGN is far more versatile than traditional alignment methods; it can be applied to a large range of sequence data that cannot be correctly aligned using standard approaches. During the last few years, several independent studies have been carried out to compare and evaluate the performance of multiple protein alignment software. Thompson et al. used the BAliBASE database of benchmark alignments (4) to evaluate the commonly used software tools. BAliBASEmainly contains globally related proteins. In this study, DIALIGN was found to be the best program on sequences with large insertions and deletions, while standard programs such as CLUSTAL W (5) were superior on globally related protein families (6). A more recent program comparison confirmed these findings (7). This study also included the newly developed program T-COFFEE (7), which was found to be superior on all five sequence categories in BAliBASE. Like DIALIGN, T-COFFEE combines global and local alignment features. The most comprehensive evaluation of protein multialignment programs so far has been carried out by Lassmann and Sonnhammer (8). These authors used not only globally related sequences but also artificial sequences where conserved motifs are separated by non-related random sequences, corresponding to the domain organization of proteins. They concluded that there are currently three methods *Tel: +49 551 39 14628; Fax: +49 551 39 14929; Email: bmorgen@gwdg.de The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated.