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Related Experiment Videos

A probabilistic classifier for olfactory receptor pseudogenes.

Idan Menashe1, Ronny Aloni, Doron Lancet

  • 1Department of Molecular Genetics and the Crown Human Genome Center, The Weizmann Institute of Science, Rehovot 76100, Israel. idan.menashe@weizmann.ac.il

BMC Bioinformatics
|August 31, 2006
PubMed
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The Classifier for Olfactory Receptor Pseudogenes (CORP) algorithm accurately identifies inactive olfactory receptor (OR) genes. CORP predicts approximately 70% of human OR genes are pseudogenes, a significantly higher proportion than previously estimated.

Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Olfactory receptors (ORs) form the largest mammalian gene superfamily, with a high proportion of pseudogenes in humans.
  • Distinguishing between functional and non-functional OR genes is crucial for understanding the human olfactory repertoire.
  • Inactive OR genes can be due to nonsense or missense mutations, necessitating advanced detection methods.

Purpose of the Study:

  • To develop and validate a computational tool for identifying inactive olfactory receptor genes with intact open reading frames.
  • To accurately assess the proportion of functional versus non-functional human OR genes.
  • To provide a method applicable to other gene families for annotating inactive members.

Main Methods:

  • Development of the Classifier for Olfactory Receptor Pseudogenes (CORP) algorithm.

Related Experiment Videos

  • Utilizing logistic regression analysis on conserved positions identified from mouse and dog OR repertoires.
  • Validation of CORP using mouse ORs, achieving a false positive rate below 0.05.

    • Main Results:

    • CORP accurately distinguishes functional from non-functional OR genes, even with single amino acid differences.
    • Application of CORP to 384 human OR genes predicted 135 as non-functional and 38 as polymorphic.
    • The algorithm identified a significantly higher proportion of pseudogenes in the mouse OR repertoire than previously reported.

    Conclusions:

    • Approximately 70% of human OR genes are predicted to be non-functional pseudogenes, revising previous estimates.
    • The CORP algorithm offers high precision in identifying inactive OR genes, including those with missense mutations.
    • The developed method can be broadly applied for annotating pseudogenes in other gene families.