Background
Rapid turnaround time for a high-resolution deceased donor human leukocyte antigen (HLA) typing is critical to improve organ transplantation outcomes. Third generation DNA sequencing platforms such as Oxford Nanopore (ONT) offer the opportunity to deliver rapid results at single nucleotide level resolution, in particular sequencing data that could be denoised computationally. Here we present a computational pipeline for the high-resolution (up to third field) HLA allele typing following ONT sequencing.
Results
From a R10.4 Q20 + chemistry batch of 31 samples of known HLA allele types, up to 10,000 ONT reads were aligned using BWA aligner, to reference allele sequences from the IMGT/HLA database. For each gene, the top two hits to reference alleles at the third field were selected. Using our pipeline, we obtained the following percent concordance at the 1st, 2nd and 3rd field: A (98.4%, 98.4%, 98.4%), B (100%, 96.8%, 96.8%), C (100%, 98.4%, 98.4%), DPA1 (100%, 96.8%, 96.8), DPB1 (100%, 100%, 98.4%), DQA1 (100%, 98.4%, 98.4%), DQB1 (100%, 98.4%, 98.4%), DRB1 (83.9%, 64.5%, 64.5%), DRB3 (96%, 88%, 88%), DRB4 (100%, 100%, 100%) and DRB5 (100%, 100%, 100%). By running our pipeline on an R10.3 flow cell batch of 63 samples, the following percent concordances were obtained: : A (100%, 96.8%, 88.1%), B (100%, 90.5.4%, 88.1%), C (100%, 99.2%, 99.2%), DPA1 (100%, 100%, 99.2), DPB1 (98.4%, 97.6%, 92.9%), DQA1 (100%, 100%, 98.4%), DQB1 (100%, 97.6%, 96%), DRB1 (88.9%, 68.3%, 68.3%), DRB3 (97.3%, 94.6%, 94.6%), DRB4 (100%, 100%, 97%) and DRB5 (73.3%, 66.7%, 66.7%). In addition, our pipelines demonstrated significantly improved concordance compared to publicly available pipeline HLA-LA (> 9% difference) and concordances close to Athlon2 (< 5% difference) in commercial development.
Conclusion
Our algorithm had a > 98% concordance for non-DRB genes at 3rd field on the R10.4 Q20 + chemistry batch and > 88% concordance for non-DRB genes at 3rd field and > 90% at 2nd field on the R10.3 batch tested. In addition, it out-performs HLA-LA and approaches the performance of the Athlon2. This lays groundwork for better utilizing Nanopore sequencing data for HLA typing especially in improving organ transplant outcomes.
