An automated algorithm for extracting functional immunologic V-genes from genomes in jawed vertebrates.

Area of Science:

• Genomics
• Immunology
• Bioinformatics

Background:

• Variable (V) gene segments are essential for generating immunoglobulin (Ig) and T cell receptor (TCR) diversity.
• Current V-gene annotation is limited to a few species, hindering comparative genomic studies.

Purpose of the Study:

• To develop and validate a bioinformatics tool for rapid and accurate identification of functional V-genes from genome datasets.
• To enable comparative phylogenetic analysis of V-genes across species, including those with incomplete annotations.

Main Methods:

• Developed an algorithm recognizing V-gene signatures (recombination signal sequences, exon size, amino acid motifs).
• Implemented automated classification of V-genes into TCR or Ig loci.
• Validated the tool using human and mouse genomes against public repositories.

Main Results:

• The tool accurately identifies functional V-genes, accelerating annotation processes.
• Successfully identified V-genes in the rat genome, enabling new comparative analyses.
• Comparative analysis supports distinct evolutionary pressures on TCR and Ig V-gene repertoires.

Conclusions:

• The developed bioinformatics tool significantly enhances V-gene identification and annotation capabilities.
• Facilitates cross-species comparative genomics and evolutionary studies of immune system components.
• The open-source software provides a valuable resource for researchers in immunology and genomics.