Benchmarking the HLA typing performance of Polysolver and Optitype in 50 Danish parental trios

Abstract

Background: The adaptive immune response intrinsically depends on hypervariable human leukocyte antigen (HLA) genes. Concomitantly, correct HLA phenotyping is crucial for successful donor-patient matching in organ transplantation. The cost and technical limitations of current laboratory techniques, together with advances in next-generation sequencing (NGS) methodologies, have increased the need for precise computational typing methods.

Results: We tested two widespread HLA typing methods using high quality full genome sequencing data from 150 individuals in 50 family trios from the Genome Denmark project. First, we computed descendant accuracies assessing the agreement in the inheritance of alleles from parents to offspring. Second, we compared the locus-specific homozygosity rates as well as the allele frequencies; and we compared those to the observed values in related populations. We provide guidelines for testing the accuracy of HLA typing methods by comparing family information, which is independent of the availability of curated alleles.

Conclusions: Although current computational methods for HLA typing generally provide satisfactory results, our benchmark - using data with ultra-high sequencing depth - demonstrates the incompleteness of current reference databases, and highlights the importance of providing genomic databases addressing current sequencing standards, a problem yet to be resolved before benefiting fully from personalised medicine approaches HLA phenotyping is essential.

Keywords: Clinical genomics; HLA genotyping; NGS; Population genetics; Prediction.

Fig. 1

Concordance between the two methods at the level of individuals. The y-axis indicates the number of individuals, while the x-axis shows the number of alleles per individual identically typed for Optitype and Polysolver 4-D)

Fig. 2

Blastn results of Optitype sequences against Optitype database (l) and Polysolver sequences against Polysolver database (r). In the plots we can observe that the identity within Optitype is higher than within Polysolver. This stems from the nature of the database. Optitype relies on a database with exons 2 and 3 and reconstructed introns, which produces sequences with scarce variation. As expected, Polysolver, due to including genomic sequences, has more variance in the identity within sequences. The self-blasted results (i.e. Sequence A against itself) were removed from the analysis

Fig. 3

Distribution of alleles according to CWD for Polysolver (a) and Optitype (b). These results highlight that HLA- B harbours the rarest alleles