Approaching Genetics Through the MHC Lens: Tools and Methods for HLA Research

Area of Science:

• Genetics and Immunology
• Infectious Disease Research
• Bioinformatics

Background:

• The SARS-CoV-2 pandemic spurred extensive research into host genetics, particularly human leukocyte antigen (HLA) associations with COVID-19.
• Previous HLA association studies varied in scale and success, with whole-genome association studies yielding more convincing results.
• Investigating HLA from large datasets is challenging due to the complexity of this genomic region.

Purpose of the Study:

• To provide a technical review of human leukocyte antigen (HLA) analysis.
• To offer basic HLA knowledge, available tools, and expert advice for geneticists.
• To enable investigation of HLA from large datasets, even without prior focus on the MHC region.

Main Methods:

• Review of existing literature and methodologies for HLA analysis.
• Description of recent algorithms for inferring HLA genotypes from Genome-Wide Association Study (GWAS) single nucleotide polymorphisms (SNPs).
• Explanation of methods for calling HLA genotypes from Next-Generation Sequencing (NGS) data.

Main Results:

• Recent algorithms allow for robust HLA genotype inference from GWAS SNPs and NGS data.
• These methods facilitate the analysis of HLA in large-scale genetic datasets.
• The review consolidates knowledge and tools, making HLA analysis more accessible.

Conclusions:

• This technical review empowers geneticists unfamiliar with HLA to conduct Major Histocompatibility Complex (MHC)-focused analyses.
• The described methods enable leveraging large datasets for HLA association studies, inspired by initiatives like the Covid-19|HLA & Immunogenetics Consortium.
• Enhanced understanding and analysis of HLA-MHC associations can significantly contribute to infectious disease research.