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Bioinformatics Advance Access published online on November 13, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti772
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Published by Oxford University Press 2005
Received July 1, 2005
Revised October 14, 2005
Accepted November 8, 2005

Article

Accurate anchoring alignment of divergent sequences

Weichun Huang 1, David M. Umbach 2, and Leping Li 2 *

1 Biostatistics Branch, The National Institute of Environmental Health Sciences, RTP, NC 27709 USA; Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27606 USA; Institute for Genome Sciences & Policy, Duke University Medical Center, Durham, NC 27708 USA
2 Biostatistics Branch, The National Institute of Environmental Health Sciences, RTP, NC 27709 USA

* To whom correspondence should be addressed.
Leping Li, E-mail: li3{at}niehs.nih.gov


  Abstract

Motivation: Obtaining high quality alignments of divergent homologous sequences for cross-species sequence comparison remains a challenge.

Results: We propose a novel pairwise sequence alignment algorithm, ACANA (ACcurate ANchoring Alignment), for aligning biological sequences at both local and global levels. Like many fast heuristic methods, ACANA uses an anchoring strategy. However, unlike others, ACANA uses a Smith-Waterman-like dynamic programming algorithm to recursively identify near optimal regions as anchors for a global alignment. Performance evaluations using a simulated benchmark dataset and real promoter sequences suggest that ACANA is accurate and consistent, especially for divergent sequences. Specifically, we use a simulated benchmark dataset to show that ACANA has the highest sensitivity to align constrained functional sites compared to BLASTZ, CHAOS and DIALIGN for local alignment and compared to AVID, ClustalW, DIALIGN, and LAGAN for global alignment. Applied to 6,007 pairs of human-mouse orthologous promoter sequences, ACANA identified the largest number of conserved regions (defined as over 70% identity over 100 bp) compared to AVID, ClustalW, DIALIGN and LAGAN. In addition, the average length of conserved region identified by ACANA was the longest. Thus, we suggest that ACANA is a useful tool for identifying functional elements in cross-species sequence analysis, such as predicting transcription factor binding sites in non-coding DNA.

Availability: ACANA software and test sequence data are publicly available at http://raga.statgen.ncsu.edu/ACANA.

Supplementary information: Supplementary materials are available at Bioinformatics online.


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