Orthanq: transparent and uncertainty-aware haplotype quantification with application in HLA-typing.

BACKGROUND: Identification of human leukocyte antigen (HLA) types from DNA-sequenced human samples is important in organ transplantation and cancer immunotherapy and remains a challenging task considering sequence homology and extreme polymorphism of HLA genes. RESULTS: We present Orthanq, a novel statistical model and corresponding application for transparent and uncertainty-aware quantification of haplotypes. We utilize our approach to perform HLA typing while, for the first time, reporting uncertainty of predictions and transparently observing mutations beyond reported HLA types. Using 99 gold standard samples from 1000 Genomes, Illumina Platinum Genomes and Genome In a Bottle projects, we show that Orthanq can provide overall superior accuracy and shorter runtimes than state-of-the-art HLA typers. CONCLUSIONS: Orthanq is the first approach that allows to directly utilize existing pangenome alignments and type all HLA loci. Moreover, it can be generalized for usages beyond HLA typing, e.g. for virus lineage quantification. Orthanq is available under https://orthanq.github.io .

A novel HLA-DPA1 allele, HLA-DPA1*02:134, identified by next-generation sequencing.

HLA-DPA1*02:134, a novel HLA class II allele detected by next-generation sequencing.

Identification of the novel HLA-DQA1*05:03:03 allele by next-generation sequencing.

HLA-DQA1*05:03:03, a novel HLA class II allele detected by next-generation sequencing.

The novel HLA-C*04:01:01:182 allele identified in a candidate bone marrow donor by next-generation sequencing.

HLA-C*04:01:01:182 differs from the HLA-C*04:01:01:06 allele by one nucleotide substitution in the 5'UTR.

Identification of the novel HLA-A*30:221 allele by next-generation sequencing.

The novel HLA-A*30:221 allele differs from HLA-A*30:01:01:01 by one nucleotide substitution in Exon 7.

Characterisation of the novel HLA-B*46:96 allele by next-generation sequencing.

HLA-B*46:96 differs from HLA-B*46:01:01:01 by a single nucleotide substitution at position 479 C>T.

Identification of eight new HLA class I alleles by next-generation sequencing.

Eight novel HLA class I alleles detected by next-generation sequencing.

Identification of the new allele HLA-C*04:01:01:186 in a Greek individual using next generation sequencing.

The newly discovered HLA-C*04:01:01:186 allele differs from HLA-C*04:01:01:01 by a single nucleotide substitution in intron 3.

Sensitive HLA antibody testing and the risk of antibody-mediated rejection and graft failure.

Solid phase detection and identification of HLA antibodies in kidney transplantation currently relies on single antigen bead (Luminex®) assays, which is more sensitive than the previously used enzyme-linked immunosorbent assays (ELISA). To evaluate the impact of more sensitive HLA testing on antibody-mediated rejection (AMR) occurrence and allograft survival, we analysed 1818 renal allograft recipients transplanted between March 2004 and May 2021. In 2008, solid phase testing switched from ELISA to Luminex. We included 393 (21.6%) transplantations before and 1425 (78.4%) transplantations after transition from ELISA- to Luminex-based testing. For this study, bio-banked ELISA era samples were tested retrospectively with Luminex. Significantly less pretransplant DSA were found in patients transplanted with pre-existing HLA antibodies in the Luminex (109/387) versus the ELISA period (43/90) (28% vs. 48%, p < 0.01). Throughout histological follow-up, 169 of 1818 (9.3%) patients developed AMR. After implementing Luminex-based testing, the rate of AMR significantly decreased (p = 0.003). However, incidence of graft failure did not significantly differ between both eras. In conclusion, less patients with pretransplant DSA were transplanted since the implementation of Luminex HLA testing. Transition from ELISA- to Luminex-based HLA testing was associated with a significant decrease in AMR occurrence post-transplantation. Since the decline of AMR did not translate into improved graft survival, Luminex-based testing has the added value of preventing low-risk AMR cases. Therefore, Luminex' high sensitivity must be balanced against waiting time for a suitable organ.

Characterisation of the novel HLA-DRB1*03:215 allele using short- and long-read sequencing technologies.

The novel HLA-DRB1*03:215 allele, first described in a potential bone marrow donor from Brazil.

Characterisation of the novel HLA-B*07:02:01:110 allele by next-generation sequencing.

HLA-B*07:02:01:110 differs from the HLA-B*07:02:01:01 allele by two nucleotide substitutions in the 3'UTR.

Characterisation of the novel HLA-B*18:243 allele using short- and long-read sequencing technologies.

The novel HLA-B*18:243 allele, first described in a potential bone marrow donor from Brazil.

Characterisation of novel MICB alleles by next generation sequencing: MICB*055 and MICB*005:15.

Two novel MICB alleles with coding polymorphisms in exon 3 were detected by next generation sequencing.

The impact of MICB mismatches in unrelated haematopoietic stem cell transplantation.

MICA polymorphisms have been associated with increased incidence of acute GvHD and adverse outcome in allogeneic haematopoietic stem cell transplantation (HSCT). MICB is another expressed member of MHC class I-related chain genes and its impact on HSCT outcome is yet to be fully defined. We typed a large cohort of patients and donors for MICB polymorphisms and investigated the impact of MICB matching on outcome after unrelated HSCT. 69.2% of the patients were 10/10 human leukocyte antigen (HLA) matched and 30.8% were 9/10 HLA matched. MICB typing was performed using a short amplicon-based NGS typing assay on the Illumina MiSeq platform. Differences in proteins were considered as mismatches. MICA polymorphisms were identified as possible confounder and were therefore included as parameter in the multivariate analyses. Due to the strong linkage disequilibrium with the classical HLA-genes, sub-stratification for HLA matching status was necessary, and no effect of MICB mismatches was seen in the 10/10 HLA matched group when compared to the MICB matched cases. However, in the 9/10 HLA matched group, MICB mismatched cases showed significantly worse disease free survival (DFS), GvHD and relapse free survival (GRFS) compared to the MICB matched cases (DFS: HR 1.24, p = 0.011; GRFS: HR 1.26, p = 0.002). MICA mismatches had no impact on any outcome parameter. According to our findings, effects previously attributed to MICA differences may have been confounded by MICB polymorphisms. We show that MICB differences contribute a small but relevant effect in 9/10 HLA-matched transplantations, which in turn highlights the possible usefulness of MICB typing in donor selection among similarly suitable 9/10 matched donors, especially when HLA-B mismatches have to be accepted.

AmpliSAS and AmpliHLA: Web Server and Local Tools for MHC Typing of Non-model Species and Human Using NGS Data.

AmpliSAS and AmpliHLA are tools for automatic genotyping of MHC genes from high-throughput sequencing data. AmpliSAS is designed specifically to analyze amplicon sequencing data from non-model species and it is able to perform de novo genotyping without any previous knowledge of the reference alleles. AmpliHLA is a human specific version; it performs HLA typing by comparing sequenced variants against human reference alleles from the IMGT/HLA database. Both tools are available in AmpliSAT web-server as well as scripts for local/server installation. Here we describe the installation and deployment of AmpliSAS and AmpliHLA Perl scripts and dependencies on a local or a server computer. We will show how to run them in the command line using as examples four genotyping protocols: the first two use amplicon sequencing data to genotype the MHC genes of a passerine bird and human respectively; the third and fourth present the HLA typing of a human cell line starting from RNA and exome sequencing data respectively.

NanoHLA: A Method for Human Leukocyte Antigen Class I Genes Typing Without Error Correction Based on Nanopore Sequencing Data.

Human leukocyte antigen (HLA) typing is of great importance in clinical applications such as organ transplantation, blood transfusion, disease diagnosis and treatment, and forensic analysis. In recent years, nanopore sequencing technology has emerged as a rapid and cost-effective option for HLA typing. However, due to the principles and data characteristics of nanopore sequencing, there was a scarcity of robust and generalizable bioinformatics tools for its downstream analysis, posing a significant challenge in deciphering the thousands of HLA alleles present in the human population. To address this challenge, we developed NanoHLA as a tool for high-resolution typing of HLA class I genes without error correction based on nanopore sequencing. The method integrated the concepts of HLA type coverage analysis and the data conversion techniques employed in Nano2NGS, which was characterized by applying nanopore sequencing data to NGS-liked data analysis pipelines. In validation with public nanopore sequencing datasets, NanoHLA showed an overall concordance rate of 84.34% for HLA-A, HLA-B, and HLA-C, and demonstrated superior performance in comparison to existing tools such as HLA-LA. NanoHLA provides tools and solutions for use in HLA typing related fields, and look forward to further expanding the application of nanopore sequencing technology in both research and clinical settings. The code is available at https://github.com/langjidong/NanoHLA .

Full-Length Characterization of Novel HLA-DRB1 Alleles for Reference Database Submission.

The prerequisite for successful HLA genotyping is the integrity of the large allele reference database IPD-IMGT/HLA. Consequently, it is in the laboratories' best interest that the data quality of submitted novel sequences is high. However, due to its long and variable length, the gene HLA-DRB1 presents the biggest challenge and as of today only 16% of the HLA-DRB1 alleles in the database are characterized in full length. To improve this situation, we developed a protocol for long-range PCR amplification of targeted HLA-DRB1 alleles. By subsequently combining both long-read and short-read sequencing technologies, our protocol ensures phased and error-corrected sequences of reference grade quality. This dual redundant reference sequencing (DR2S) approach is of particular importance for correctly resolving the challenging repeat regions of DRB1 intron 1. Until today, we used this protocol to characterize and submit 384 full-length HLA-DRB1 sequences to IPD-IMGT/HLA.

Characterisation of the novel HLA-DQA1*04:14N allele by next-generation sequencing.

HLA-DQA1*04:14N differs from HLA-DQA1*04:01:01:03 by a single nucleotide deletion in codon 113 in exon 3.

Characterisation of the novel HLA-A*32:01:01:41 allele by next-generation sequencing.

HLA-A*32:01:01:41 differs from the HLA-A*32:01:01:01 allele by one nucleotide substitution in the intron 3.

HLA-DPB1 and DPA1 ~ DPB1 linkage mismatch affects the survival of recipients receiving HLA-14/14 matched unrelated donor HSCT.

To analyse the effect of HLA-DPA1 and HLA-DPB1 allelic mismatches on the outcomes of unrelated donor haematopoietic stem cell transplantation (URD-HSCT), we collected 258 recipients with haematological disease who underwent HLA-10/10 matched URD-HSCT. HLA-A, -B, -C, -DRB1, -DQB1, -DRB3/4/5, -DQA1, -DPA1 and -DPB1 typing was performed for the donors and recipients using next-generation sequencing (NGS) technology. After excluding 8 cases with DQA1 or DRB3/4/5 mismatches, we included 250 cases with HLA-14/14 matching for further analysis. Our results showed that the proportion of matched DPA1 and DPB1 alleles was only 10.4% (26/250). The remaining 89.6% of donors and recipients demonstrated DPA1 or DPB1 mismatch. In the DPA1 matched and DPB1 mismatched group, accounting for 18.8% (47/250) of the cohort, DPB1*02:01/DPB1*03:01 allelic mismatches were associated with decreased 2-year OS and increased NRM. DPB1*02:02/DPB1*05:01 and DPB1*02:01/DPB1*05:01 mismatches showed no impact on outcomes. Moreover, the specific allelic mismatches observed were consistent with the DPB1 T-cell epitope (TCE) classification as permissive and non-permissive. We innovatively established an analysis method for DPA1 ~ DPB1 linkage mismatch for cases with both DPA1 and DPB1 mismatched, accounting for 70% (175/250) of the total. DPA1*02:02 ~ DPB1*05:01/DPA1*02:01 ~ DPB1*17:01 linkage mismatches were associated with lower 2-year OS, especially among AML/MDS recipients. DPA1*02:02 ~ DPB1*05:01/DPA1*01:03 ~ DPB1*02:01 linkage mismatches showed no impact on outcomes. In conclusion, applying the DPA1 ~ DPB1 linkage mismatch analysis approach can identify different types of mismatches affecting transplant outcomes and provide valuable insight for selecting optimal donors for AML/MDS and ALL recipients.