%0 Journal Article
%T ReAlignerV: Web-based genomic alignment tool with high specificity and robustness estimated by species-specific insertion sequences
%A Hisakazu Iwama
%A Yukio Hori
%A Kensuke Matsumoto
%A Koji Murao
%A Toshihiko Ishida
%J BMC Bioinformatics
%D 2008
%I BioMed Central
%R 10.1186/1471-2105-9-112
%X We constructed a web server 'ReAlignerV' for complex alignment of genomic sequences. ReAlignerV returns ladder-like schematic alignments that integrate predicted TFBSs and the location of TEs. It also provides pair-wise alignments in which the predicted TFBS sites and their names are shown alongside each sequence. Furthermore, we evaluated false positive aligned sites by focusing on the species-specific TEs (SSTEs), and found that ReAlignerV has a higher specificity and robustness to insertions for sequences having more than 20% TE content, compared to LAGAN, AVID, MAVID and BLASTZ.ReAlignerV can be applied successfully to TE-insertion-rich sequences without prior repeat masking, and this increases the chances of finding regulatory sequences hidden in TEs, which are important sources of the regulatory network evolution. ReAlignerV can be accessed through and downloaded from http://genet.med.kagawa-u.ac.jp/ webcite.Cross-species comparisons of genome sequences have provided an efficient means of identifying conserved functional elements. Alignment procedures of related species are the mainstay for comparative genomics [1]. Identification of CNSs followed by functional motif discovery has successfully revealed its power with regard to both yeast species [2,3] and mammals [4]. The combination of alignment-based CNS detection and TFBS prediction is also recognized as one of the promising approaches. Today, a wide variety of methods (for example, rVISTA [5], CONREAL [6], ConSite [7], etc.) are publicly available through the web. For the alignment, rVISTA utilizes BLASTZ [8], whereas CONREAL adopts a greedy strategy by allowing users to choose from LAGAN [9], MAVID [10] and/or BLASTZ.The aligners described above adopt heuristic index-based approaches to decrease processing time and memory usage. In order to obtain sufficiently long alignments, they utilize a chaining strategy based on the highly similar aligned sequences which are called anchors or seeds. In addition, rep
%U http://www.biomedcentral.com/1471-2105/9/112