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Related Experiment Videos

Detecting frame shifts by amino acid sequence comparison

J M Claverie1

  • 1National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health Bethesda, MD 20894.

Journal of Molecular Biology
|December 20, 1993
PubMed
Summary

New scoring matrices detect protein sequence frame shifts caused by insertions, deletions, or inversions. These tools reveal potential sequencing errors and suggest frame shift mutations may drive protein evolution.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Molecular Evolution

Background:

  • Standard amino acid substitution matrices assume point mutations and gradual amino acid property changes.
  • Nucleotide insertions, deletions, and inversions cause frame shifts, rendering protein sequences unrecognizable.
  • Existing methods struggle to detect evolutionary relationships affected by frame shift mutations.

Purpose of the Study:

  • To develop novel scoring matrices for detecting specific frame shift events (deletion, insertion, inversion) in protein sequences.
  • To identify amino acid sequences potentially derived from alternative reading frames of the same nucleotide sequence.
  • To investigate the role of frame shift mutations in protein evolution and sequence discovery.

Main Methods:

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  • Derivation of five new scoring matrices, each designed to detect a specific type of frame shift across three reading frames.
  • Application of these matrices with a local alignment program (BLASTP) to compare all sequences in the Swissprot database.
  • Inference of frame shifts based solely on protein sequence comparisons.

    • Main Results:

    • Hundreds of highly significant frame shift matches were discovered across the Swissprot database.
    • A substantial number of these matches are likely attributable to sequencing errors.
    • Some findings suggest frame shift mutations may contribute to the creation of novel amino acid sequences from existing coding regions.

    Conclusions:

    • The developed scoring matrices are effective in detecting frame shifts directly from protein sequences.
    • Frame shift events, while often indicative of errors, may also play a role in evolutionary innovation.
    • This work provides a new computational approach for exploring protein sequence relationships and evolutionary mechanisms.