Bioinformatics tool ngsmhc shows improved MHC genotyping accuracy in pigs using NGS data, highlighting the role of read length in allele determination.
Understanding the individual- and population-level polymorphisms of major histocompatibility complex (MHC) genes is crucial for identifying associations between MHC variations and immune phenotypes. To support this, we developed NGSMHC, a streamlined bioinformatics tool for efficient and accurate MHC genotyping using next-generation sequencing (NGS) data in non-human species. NGSMHC constructs phased haplotype contigs of selected MHC genes from BAM-format mapping data and determines the best matching MHC alleles and genotypes via nucleotide BLAST analysis against a user-provided reference set of MHC alleles. We evaluated NGSMHC using short-read whole-genome sequencing (WGS) data from 12 pigs, focusing on swine leukocyte antigen (SLA) genes. The typing results from NGSMHC were compared to those obtained using polymerase chain reaction sequence-based typing (PCR-SBT). In addition, we tested NGSMHC on a publicly available long-read WGS dataset with known SLA genotypes. The short-read WGS data showed an average read depth of 20.9× across the SLA region, enabling typing of SLA-2, SLA-3, SLA-DRB1, and SLA-DQB1 using NGSMHC. The concordance rates between NGSMHC and PCR-SBT were 88% for SLA-3, 92% for SLA-DRB1, and 100% for SLA-DQB1. However, SLA-2 typing showed lower concordance (58%), likely due to its high sequence similarity with other SLA class I genes and complex intra-locus polymorphisms. In contrast, NGSMHC accurately identified all tested SLA genotypes-including SLA-1, SLA-2, SLA-3, SLA-DRA, SLA-DRB1, SLA-DQA, and SLA-DQB1-when applied to the long-read WGS data. NGSMHC is a simple and effective tool for MHC genotyping using NGS data, particularly for non-human species. Its accuracy is significantly improved by long-read sequencing, underscoring the importance of read length in precise MHC allele determination.
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Kang et al. (2025) studied this question.
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