Genotyping of selected germline adaptive immune system loci using short-read sequencing data

Area of Science:

• Genomics and Bioinformatics
• Immunogenetics
• Personalized Medicine

Background:

• Personalized medicine requires understanding individual genetic variations, especially in the immune system.
• Classical sequencing methods struggle with highly repetitive and homologous immune genes like immunoglobulin (IG) and T cell receptor (TR).
• Accurate genotyping of these adaptive immune genes is crucial for advancing healthcare.

Purpose of the Study:

• To introduce ImmunoTyper2, a computational toolkit for genotyping variable IG lambda, kappa, and TR loci.
• To improve upon previous methods by utilizing short-read whole genome sequencing data.
• To enable robust genetic analysis of adaptive immune system genes for research and clinical applications.

Main Methods:

• Developed ImmunoTyper2 using an integer linear programming formulation for short-read whole genome sequencing data.
• Evaluated genotyping performance via Mendelian concordance analysis in 590 trios from the 1000 Genomes Project.
• Benchmarked against HPRC assembly-derived genotypes and assessed robustness through sequencing depth and parameter sensitivity tests.

Main Results:

• ImmunoTyper2 demonstrates high genotyping accuracy for IG and TR loci.
• Introduced allele call confidence metrics to quantify the reliability of genetic calls.
• Successfully applied ImmunoTyper2 to a COVID-19 patient cohort for disease association studies.

Conclusions:

• ImmunoTyper2 provides a reliable computational solution for genotyping complex adaptive immune system genes.
• The toolkit facilitates deeper insights into genetic variations influencing immune responses.
• ImmunoTyper2 is a valuable tool for personalized medicine, disease association studies, and advancing immunogenetic research.