Development and validation of a pipeline for the systematic search for new HLA alleles in WGS data

Human leukocyte antigen (HLA) is a highly polymorphic locus in the human genome that also has high clinical significance. New alleles of HLA genes are constantly being discovered but mostly by HLA typing laboratories using field-specific protocols, such as enrichment of the HLA region in high-throughput sequencing data. Nevertheless, a vast amount of whole-genome sequencing (WGS) data has been accumulated over the past years. The main goal of our work was to develop and validate a pipeline specifically tailored toward the identification and characterization of new HLA alleles from 30x WGS sequencing.

In this article, we present a pipeline, HLAchecker, which is specifically designed to identify potentially new HLA alleles based on discrepancies between predicted HLA types, generated using any other dedicated tool, and the underlying raw 30x WGS data. HLAchecker reports results in a structured way that simplifies further validation of potentially new HLA alleles and streamlines the submission of alleles to appropriate databases. We validated this tool on 4,195 30x WGS samples and 6 HLA genes (A, B, C, DQA1, DQB1, and DRB1) typed by HLA-HD and discovered 17 potentially new HLA alleles with substitutions in exonic regions. We further validated five of these alleles using Sanger sequencing and submitted them to the IPD-IMGT/HLA database.

HLAchecker is suitable for the identification of new HLA alleles in large WGS cohorts accumulated by the scientific community in recent years. HLAchecker is freely available at https://gitlab.com/EugeneA/hlachecker.