TRIg: a robust alignment pipeline for non-regular T-cell receptor and immunoglobulin sequences

Area of Science:

• Immunology
• Bioinformatics
• Genomics

Background:

• Adaptive immunity relies on T cells and B cells recognizing antigens via diverse T cell receptors and immunoglobulins.
• Receptor gene recombination generates this diversity, and its frequency offers insights into immunity and disease.
• Current computational tools fail with non-regular recombination patterns often found in RACE sequencing data.

Purpose of the Study:

• To develop a computational program capable of analyzing non-regular T cell receptor and immunoglobulin gene sequences.
• To address the limitations of existing tools that assume regular recombination patterns.

Main Methods:

• TRIg aligns sequences to the entire receptor gene, not just coding regions, to accommodate non-regular recombination.
• A heuristic strategy and gene annotation are employed to resolve ambiguous alignments caused by repetitive regions.
• The program was validated on both internal and public RACE datasets.

Main Results:

• TRIg successfully identified non-regularly recombined sequences in RACE data, outperforming existing methods.
• The tool also demonstrated efficacy in analyzing regularly recombined sequences.
• TRIg provides accurate estimation of recombination events from RACE data.

Conclusions:

• TRIg is suitable for analyzing RACE data, accurately capturing non-regular recombination events in T cell receptor and immunoglobulin genes.
• This accurate analysis benefits immune studies and aids in investigating aberrant recombination in immune diseases.
• TRIg is freely available for use and further development.