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BLAST and FASTA similarity searching for multiple sequence alignment.

William R Pearson1

  • 1Department of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, Charlottesville, VA, USA.

Methods in Molecular Biology (Clifton, N.J.)
|October 31, 2013
PubMed
Summary
This summary is machine-generated.

Sequence similarity searches using BLAST and FASTA programs help identify homologous proteins and DNA. Protein sequence comparisons are more sensitive for inferring homology and evolutionary relationships, even over billions of years.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Evolutionary Biology

Background:

  • Homology detection is crucial for understanding evolutionary relationships between biological sequences.
  • Similarity searching programs like BLAST and FASTA are widely used tools in molecular biology.
  • Inferring homology requires careful consideration of sequence similarity beyond chance expectations.

Purpose of the Study:

  • To outline the principles and effective strategies for using similarity searching programs.
  • To compare the sensitivity and utility of protein versus DNA sequence comparisons.
  • To guide users in optimizing search parameters for different evolutionary scales.

Main Methods:

  • Utilizing sequence similarity searching programs such as BLAST and FASTA.
  • Comparing protein sequences against protein databases for enhanced sensitivity.
  • Employing expectation values over percent identity for homology inference.
  • Adjusting scoring strategies and database selection for specific search objectives.

Main Results:

  • Protein sequence comparisons are significantly more sensitive than DNA:DNA searches for detecting homology.
  • Expectation values provide reliable statistical estimates for inferring homology.
  • Searches can reliably identify homologous sequences diverged over 1-2 billion years ago.
  • Customizable local installations and targeted database searches improve sensitivity.

Conclusions:

  • Protein sequence analysis with BLAST and FASTA is the most sensitive method for inferring homology.
  • Expectation values are superior to percent identity for robust homology detection.
  • These tools facilitate deep evolutionary analyses, looking back billions of years.
  • Optimizing search parameters and databases enhances the discovery of evolutionary relationships.