Development of a high-resolution NGS-based HLA-typing and analysis pipeline

Area of Science:

• Genetics
• Immunology
• Bioinformatics

Background:

• The human leukocyte antigen (HLA) complex is highly polymorphic and critical for immune responses.
• Accurate HLA typing is essential for transplantation medicine, autoimmune disease research, and infectious disease susceptibility studies.
• Current HLA typing methods, while effective, are often proprietary, limiting accessibility and broad application.

Purpose of the Study:

• To introduce the first highly automated, open-kit, and open-source method for next-generation sequencing (NGS)-based HLA typing.
• To provide a reliable and accessible tool for high-resolution HLA allele identification.
• To validate the performance of the new method against established typing techniques.

Main Methods:

• Employed in-solution targeted capturing of classical class I (HLA-A, HLA-B, HLA-C) and class II HLA genes (HLA-DRB1, HLA-DQA1, HLA-DQB1, HLA-DPA1, HLA-DPB1).
• Developed a calling algorithm for confident allele identification to three-field resolution.
• Validated the method on 357 commercial DNA samples with known HLA alleles determined by classical typing.

Main Results:

• Achieved an average accurate allele call rate of 0.99 in a fully automated process.
• Demonstrated high confidence in HLA allele identification, including the detection of errors in reference data.
• The method proved flexible, with potential for adding further target enrichment regions.

Conclusions:

• The developed open-source HLA typing method offers a highly accurate and automated solution for NGS-based HLA allele calling.
• This approach enhances accessibility to advanced HLA typing technology, benefiting research and clinical applications.
• The method's reliability and flexibility support its widespread adoption in the fields of immunology and transplantation.