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A novel method for multiple alignment of sequences with repeated and shuffled elements.

Benjamin Raphael1, Degui Zhi, Haixu Tang

  • 1Department of Computer Science and Engineering, University of California, San Diego, La Jolla, California 92093-0114, USA. braphael@ucsd.edu

Genome Research
|November 3, 2004
PubMed
Summary
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A-Bruijn alignment (ABA) is a novel multiple sequence alignment method using directed graphs. This flexible approach accurately aligns complex protein and genomic sequences with shuffled, repeated, or rearranged structures.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Multiple sequence alignment is crucial for understanding biological sequence evolution.
  • Existing methods struggle with complex evolutionary relationships like shuffled or repeated domains.
  • Partial Order Alignment (POA) graphs offer improvements but have limitations.

Purpose of the Study:

  • Introduce A-Bruijn alignment (ABA), a new method for multiple sequence alignment.
  • Address limitations of traditional and POA methods in handling complex sequence structures.
  • Demonstrate ABA's utility in aligning challenging protein and genomic datasets.

Main Methods:

  • Representing alignments as directed graphs, potentially with cycles.
  • Utilizing graph-based flexibility to model diverse evolutionary relationships.

Related Experiment Videos

  • Applying ABA to protein sequences with shuffled/repeated domains and genomic sequences with duplications/inversions.

    • Main Results:

    • ABA accommodates proteins with variable domain content, order, and copy number.
    • ABA effectively aligns genomic sequences exhibiting duplications and inversions.
    • The graph representation offers greater flexibility than alignment matrices or POA graphs.

    Conclusions:

    • ABA provides a more flexible and powerful approach to multiple sequence alignment.
    • This method is particularly advantageous for analyzing complex protein and genomic architectures.
    • ABA expands the capabilities for reconstructing evolutionary histories from sequence data.