Fast and sensitive multiple alignment of large genomic sequences.

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. CONCLUSION: 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.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

VARiD: A variation detection framework for color-space and letter-space platforms

Motivation: High-throughput sequencing (HTS) technologies are transforming the study of genomic variation. The various HTS technologies have different sequencing biases and error rates, and while most HTS technologies sequence the residues of the genome directly, generating base calls for each position, the Applied Biosystem's SOLiD platform generates dibase-coded (color space) sequences. While combining data from the various platforms should increase the accuracy of variation detection, to date there are only a few tools that can identify variants from color space data, and none that can analyze color space and regular (letter space) data together

A haplome alignment and reference sequence of the highly polymorphic Ciona savignyi genome

The high degree of polymorphism in the genome of the sea squirt Ciona savignyi complicated the assembly of sequence contigs, but a new alignment method results in a much improved sequence

Multiple whole genome alignments and novel biomedical applications at the VISTA portal

The VISTA portal for comparative genomics is designed to give biomedical scientists a unified set of tools to lead them from the raw DNA sequences through the alignment and annotation to the visualization of the results. The VISTA portal also hosts the alignments of a number of genomes computed by our group, allowing users to study the regions of their interest without having to manually download the individual sequences. Here we describe various algorithmic and functional improvements implemented in the VISTA portal over the last 2 years. The VISTA Portal is accessible at http://genome.lbl.gov/vista

Extensive parallelism in protein evolution

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens