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

NIAID COVID Consortium

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Human immunoglobulin heavy chain (IGH) locus on chromosome 14 includes more than 40 functional copies of the variable gene (IGHV), which are critical for the structure of antibodies that identify and neutralize pathogenic invaders as a part of the adaptive immune system. Because of its highly repetitive sequence composition, the IGH locus has been particularly difficult to assemble or genotype when using standard short-read sequencing technologies. Here, we introduce ImmunoTyper-SR, an algorithmic tool for the genotyping and CNV analysis of the germline IGHV genes on Illumina whole-genome sequencing (WGS) data using a combinatorial optimization formulation that resolves ambiguous read mappings. We have validated ImmunoTyper-SR on 12 individuals, whose IGHV allele composition had been independently validated, as well as concordance between WGS replicates from nine individuals. We then applied ImmunoTyper-SR on 585 COVID patients to investigate the associations between IGHV alleles and anti-type I IFN autoantibodies, which were previously associated with COVID-19 severity.

Original languageEnglish
Pages (from-to)808-816.e5
JournalCell Systems
Volume13
Issue number10
DOIs
StatePublished - 19 Oct 2022
Externally publishedYes

Keywords

  • ILP
  • WGS
  • algorithms
  • computational biology
  • genomics
  • genotyping
  • immunogenomics
  • immunoglobulin
  • next generation sequencing
  • optimization

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