ImmunoTyper-SR: A computational approach for genotyping immunoglobulin heavy chain variable genes using short-read...

Area of Science:

• Genetics
• Immunology
• Bioinformatics

Background:

• The human immunoglobulin heavy chain (IGH) locus contains over 40 variable genes (IGHV) crucial for antibody structure and adaptive immunity.
• The repetitive nature of the IGH locus challenges standard short-read sequencing for accurate genotyping and assembly.

Purpose of the Study:

• To develop and validate ImmunoTyper-SR, an algorithmic tool for germline IGHV gene genotyping and copy number variation (CNV) analysis.
• To apply ImmunoTyper-SR to whole-genome sequencing (WGS) data for improved IGH locus analysis.
• To investigate associations between IGHV alleles and anti-type I IFN autoantibodies in COVID-19 patients.

Main Methods:

• Development of ImmunoTyper-SR, utilizing a combinatorial optimization formulation to resolve ambiguous read mappings.
• Validation of ImmunoTyper-SR on 12 individuals with independently validated IGHV allele composition.
• Concordance assessment using WGS replicates from nine individuals.
• Application of ImmunoTyper-SR to WGS data from 585 COVID-19 patients.

Main Results:

• ImmunoTyper-SR successfully performed genotyping and CNV analysis of germline IGHV genes using Illumina WGS data.
• Validation demonstrated high accuracy and concordance of the ImmunoTyper-SR tool.
• The study identified potential associations between specific IGHV alleles and anti-type I IFN autoantibodies in COVID-19 patients.

Conclusions:

• ImmunoTyper-SR provides a robust solution for analyzing the complex IGHV locus from WGS data.
• The tool enhances our ability to study antibody gene repertoire and its role in immune responses.
• Further research using ImmunoTyper-SR may elucidate the link between IGHV alleles, autoantibodies, and COVID-19 severity.