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An enhanced RNA alignment benchmark for sequence alignment programs.

Andreas Wilm1, Indra Mainz, Gerhard Steger

  • 1Institut für Physikalische Biologie, Heinrich-Heine-Universität Düsseldorf, Universitätsstr, 1, 40225 Düsseldorf, Germany. wilm@biophys.uni-duesseldorf.de

Algorithms for Molecular Biology : AMB
|October 26, 2006
PubMed
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This study enhances RNA sequence alignment benchmarks, finding that iterative programs outperform non-iterative ones, especially at lower sequence identities. Optimal parameters improve alignment quality for RNA sequences.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Traditional protein sequence alignment benchmarks are insufficient for RNA alignment due to distinct sequence and structural properties.
  • RNA alignment exhibits a wider 'twilight zone' of low alignment quality compared to proteins.
  • Previous RNA alignment benchmarks were limited in scope.

Purpose of the Study:

  • To enhance the existing RNA sequence alignment benchmark.
  • To evaluate the performance of various alignment programs and parameters on diverse RNA datasets.
  • To identify optimal parameters and program types for accurate RNA sequence alignment across varying sequence identities.

Main Methods:

  • Expanded RNA sequence sets from an increased number of RNA families.

Related Experiment Videos

  • Varied set sizes (2-15 sequences) to assess the impact of sequence count.
  • Scored alignment quality using nucleotide matches and structural conservation.
  • Utilized rank tests to evaluate program and parameter performance.

    • Main Results:

    • Most programs perform well on RNA sequences with average pairwise sequence identity (APSI) above 75%.
    • Gap-open and gap-extension parameters significantly influence alignment quality below 75% APSI.
    • Iterative alignment programs show superior performance with increasing sequence numbers and decreasing sequence identity.
    • Optimal parameter combinations were identified for several programs.

    Conclusions:

    • Iterative alignment programs are superior to non-iterative ones for RNA sequences, particularly at lower sequence identities.
    • High-quality RNA alignments are achievable down to 55% APSI with the best programs.
    • Sequence+structure alignment programs are recommended for RNA sequences with APSI below 55%.