A computational HLA allele-typing protocol to de-noise and leverage nanopore amplicon data

Area of Science:

• Genomics and Bioinformatics
• Immunogenetics
• Transplantation Science

Background:

• Accurate human leukocyte antigen (HLA) typing is crucial for successful organ transplantation.
• Rapid turnaround time for deceased donor HLA typing is essential to optimize organ utilization.
• Third-generation sequencing technologies like Oxford Nanopore (ONT) offer potential for faster, high-resolution HLA typing.

Purpose of the Study:

• To develop and validate a computational pipeline for high-resolution, third-field HLA allele typing using ONT sequencing data.
• To assess the concordance and accuracy of the developed pipeline compared to existing methods.

Main Methods:

• Utilized ONT sequencing data from human samples with known HLA allele types.
• Aligned sequencing reads to the IPD-IMGT/HLA database using the BWA aligner.
• Developed a computational pipeline to determine HLA alleles at the third-field resolution, selecting the top two reference allele hits.

Main Results:

• The pipeline achieved high concordance rates for most HLA genes, exceeding 96% for non-HLA-DRB genes at the third field in the first batch.
• Second batch results showed >88% concordance for non-HLA-DRB genes at the third field and >90% at the second field.
• The developed pipeline demonstrated superior performance compared to the HLA-LA tool and approached the accuracy of the commercial Athlon2 system.

Conclusions:

• The computational pipeline effectively enables accurate third-field HLA typing from ONT sequencing data.
• This approach has the potential to significantly improve the efficiency and outcomes of organ transplantation.
• The findings support the broader adoption of Nanopore sequencing for clinical HLA typing applications.