HLA typing using next generation sequencing: An overview

Genotyping of canine MHC gene DLA-88 by next-generation sequencing reveals high frequencies of new allele discovery and gene duplication

Dogs have served as one of the most reliable preclinical models for a variety of diseases and treatments, including stem/progenitor cell transplantation. At the genetic epicenter of dog transplantation models, polymorphic major histocompatibility complex (MHC) genes are most impactful on transplantation success. Among the canine class I and class II genes, DLA-88 has been best studied in transplantation matching and outcomes, with 129 DLA-88 alleles identified. In this study we developed and tested a next generation (NGS) sequencing protocol for rapid identification of DLA-88 genotypes in dogs and compared the workflow and data generated with an established DLA-88 Sanger sequencing protocol that has been in common prior use for clinical studies. By testing the NGS protocol on a random population of 382 dogs, it was possible to demonstrate superior efficacy based on laboratory execution and overall cost. In addition, NGS proved far more effective at discovering new alleles and detecting multiple alleles associated with gene duplication. A total of 51 new DLA-88 alleles are reported here. This rate of new allele discovery indicates that a large pool of yet un-discovered DLA-88 alleles exists in the domestic dog population. In addition, more than 46% of dogs carried three or more copies of DLA-88, further emphasizing the need for more sensitive and cost-effective DLA typing methodology for the dog clinical model.

Graphical user interface for the haplotype frequency estimation software Hapl-o-Mat

Population-specific human leukocyte antigen (HLA) haplotype frequencies are an essential basis of advanced algorithms for donor selection in unrelated hematopoietic stem cell transplantation. In 2016, we introduced Hapl-o-Mat, a versatile tool for haplotype frequency estimation based on an expectation-maximization algorithm (https://github.com/DKMS/hapl-o-Mat). Hapl-o-Mat is specifically tailored to the analysis of HLA genes and able to cope with the heterogeneous genotyping data usually found in donor registries. To make Hapl-o-Mat accessible to a wider range of users, we designed a graphical user interface module that considerably facilitates the interaction with the application (https://github.com/DKMS/hapl-o-Mat_GUI). We further provide a precompiled version of Hapl-o-Mat that can be used on Windows personal computers without dependency on additional software libraries (https://github.com/DKMS/hapl-o-Mat_WinBin). We are confident that these new, user-oriented features will encourage more researchers to apply Hapl-o-Mat to their data, thereby increasing knowledge and public availability of population-specific HLA haplotype frequencies.

High-resolution HLA allele and haplotype frequencies in several unrelated populations determined by next generation sequencing: 17th International HLA and Immunogenetics Workshop joint report

The primary goal of the unrelated population HLA diversity (UPHD) component of the 17th International HLA and Immunogenetics Workshop was to characterize HLA alleles at maximum allelic-resolution in worldwide populations and re-evaluate patterns of HLA diversity across populations. The UPHD project included HLA genotype and sequence data, generated by various next-generation sequencing methods, from 4,240 individuals collated from 12 different countries. Population data included well-defined large datasets from the USA and smaller samples from Europe, Australia, and Western Asia. Allele and haplotype frequencies varied across populations from distant geographical regions. HLA genetic diversity estimated at 2- and 4-field allelic resolution revealed that diversity at the majority of loci, particularly for European-descent populations, was lower at the 2-field resolution. Several common alleles with identical protein sequences differing only by intronic substitutions were found in distinct haplotypes, revealing a more detailed characterization of linkage between variants within the HLA region. The examination of coding and non-coding nucleotide variation revealed many examples in which almost complete biunivocal relations between common alleles at different loci were observed resulting in higher linkage disequilibrium. Our reference data of HLA profiles characterized at maximum resolution from many populations is useful for anthropological studies, unrelated donor searches, transplantation, and disease association studies.

Concurrent typing of over 4000 samples by long-range PCR amplicon-based NGS and rSSO revealed the need to verify NGS typing for HLA allelic dropouts

Hematopoietic stem cell transplantation (HSCT) from HLA-matched donors significantly decreases the risks of graft-rejection and graft-versus-host disease. Long-range PCR- amplicon-based next-generation sequencing (NGS) is increasingly used as a standalone method in clinical laboratories to determine HLA compatibility for HSCT and solid-organ transplantation. We hypothesized that an allelic dropout is a frequent event in the long-range PCR amplicon-based NGS HLA typing method. To test the hypothesis, we typed 4,006 samples concurrently using a commercially available long-range PCR amplicon-based NGS-typing and short exon-specific amplicon-based reverse sequence-specific oligonucleotide (rSSO) methods. The concordance between the NGS and rSSO typing results was 100% at HLA-A, -B, -C, -DRB1, -DRB3, -DRB5, -DQA1, DPA1 loci. However, 4.5% of the samples (179/4006) showed allelic-dropouts at one of the other three loci: HLA-DRB4 (3.9%), HLA-DPB1 (0.4%), and HLA-DQB1*(0.15%). The allelic-dropouts are not associated with specific haplotypes, and some dropouts can be reagent lot-specific. Although DRB1-DRB3/4/5-DQB1 linkages help to diagnose these allelic-dropouts in some cases, the rSSO typing was crucial to identify the dropouts in DQB1 and DPB1 loci. These results uncover the critical limitations of using long-range PCR amplicon-based NGS as a standalone method in clinical histocompatibility laboratories and advocate the need for strategies to diagnose and resolve allelic-dropouts.

Capturing Differential Allele-Level Expression and Genotypes of All Classical HLA Loci and Haplotypes by a New Capture RNA-Seq Method

The highly polymorphic human major histocompatibility complex (MHC) also known as the human leukocyte antigen (HLA) encodes class I and II genes that are the cornerstone of the adaptive immune system. Their unique diversity (>25,000 alleles) might affect the outcome of any transplant, infection, and susceptibility to autoimmune diseases. The recent rapid development of new next-generation sequencing (NGS) methods provides the opportunity to study the influence/correlation of this high level of HLA diversity on allele expression levels in health and disease. Here, we describe the NGS capture RNA-Seq method that we developed for genotyping all 12 classical HLA loci (HLA-A, HLA-B, HLA-C, HLA-DPA1, HLA-DPB1, HLA-DQA1, HLA-DQB1, HLA-DRA, HLA-DRB1, HLA-DRB3, HLA-DRB4, and HLA-DRB5) and assessing their allelic imbalance by quantifying their allele RNA levels. This is a target enrichment method where total RNA is converted to a sequencing-ready complementary DNA (cDNA) library and hybridized to a complex pool of RNA-specific HLA biotinylated oligonucleotide capture probes, prior to NGS. This method was applied to 161 peripheral blood mononuclear cells and 48 umbilical cord blood cells of healthy donors. The differential allelic expression of 10 HLA loci (except for HLA-DRA and HLA-DPA1) showed strong significant differences (P < 2.1 × 10-15). The results were corroborated by independent methods. This newly developed NGS method could be applied to a wide range of biological and medical questions including graft rejections and HLA-related diseases.

A long road/read to rapid high-resolution HLA typing: The nanopore perspective

Next-generation sequencing (NGS) has been widely adopted for clinical HLA typing and advanced immunogenetics researches. Current methodologies still face challenges in resolving cis-trans ambiguity involving distant variant positions, and the turnaround time is affected by testing volume and batching. Nanopore sequencing may become a promising addition to the existing options for HLA typing. The technology delivered by the MinION sequencer of Oxford Nanopore Technologies (ONT) can record the ionic current changes during the translocation of DNA/RNA strands through transmembrane pores and translate the signals to sequence reads. It features simple and flexible library preparations, long sequencing reads, portable and affordable sequencing devices, and rapid, real-time sequencing. However, the error rate of the sequencing reads is high and remains a hurdle for its broad application. This review article will provide a brief overview of this technology and then focus on the opportunities and challenges of using nanopore sequencing for high-resolution HLA typing and immunogenetics research.

Performance of a multiplexed amplicon-based next-generation sequencing assay for HLA typing

BACKGROUND

Next-generation sequencing (NGS) has enabled efficient high-resolution typing of human leukocyte antigen (HLA) genes with minimal ambiguity. Most commercially available assays amplify individual or subgroup of HLA genes by long-range PCR followed by library preparation and sequencing. The AllType assay simplifies the workflow by amplifying 11 transplant-relevant HLA genes in one PCR reaction. Here, we report the performance of this unique workflow evaluated using 218 genetically diverse samples.

METHODS

Five whole genes (HLA-A/B/C/DQA1/DPA1) and six near-whole genes (HLA-DRB1/DRB345/DQB1/DPB1; excluding exon 1 and part of intron 1) were amplified in a multiplexed, long-range PCR. Manual library preparation was performed per manufacturer's protocol, followed by template preparation and chip loading on the Ion Chef, and sequencing on the Ion S5 sequencer. Pre-specified rules for quality control and repeat testing were followed; technologists were blinded to the reference results. The concordance between AllType and reference results was determined at 2-field resolution. We also describe the ranges of input DNA and library concentrations, read number per sample and per locus, and key health metrics in relation to typing results.

RESULTS

The concordance rates were 98.6%, 99.8% and 99.9% at the sample (n = 218), genotype (n = 1688), and allele (n = 3376) levels, respectively. Three genotypes were discordant, all of which shared the same G group typing results with the reference. Most ambiguous genotypes (116 out of 144, 80.6%) were due to the lack of exon 1 and intron 1 coverage for HLA-DRB1/DRB345/DQB1/DPB1 genes. A broad range of input DNA concentrations and library concentrations were tolerated. Per sample read numbers were adequate for accurate genotyping. Per locus read numbers showed some inter-lot variations, and a trend toward improved inter-locus balance was observed with later lots of reagents.

CONCLUSION

The AllType assay on the Ion Chef/Ion S5 platform offers a robust and efficient workflow for clinical HLA typing at the 2-field resolution. The multiplex PCR strategy simplifies the laboratory procedure without compromising the typing accuracy.

Next-generation sequencing of HLA: validation and identification of new polymorphisms in a Brazilian population

BACKGROUND

Next-generation sequencing (NGS) is the most modern sequencing technique that has revolutionized HLA typing, providing high-resolution results with low ambiguity rates. This study aimed to show the experiences and challenges of an HLA laboratory in the validation process of the NGS methodology for HLA typing and show the use of this method for the study of HLA genetic diversity.

METHODS

We used 115 samples that comprised a comprehensive testing panel for validation of the NGS methodology using the AllType kit (One Lambda, Canoga Park, California) on the Ion Torrent S5 NGS platform. All quality metrics were analyzed. During validation, two new HLA sequences were identified and named by the HLA Nomenclature Committee.

RESULTS

A total of 1380 alleles from the HLA-A, -B, -C, -DRB1, -DQB1, and -DPB1 loci were examined by NGS. This validation panel provided a wide range of HLA sequence variations, including non-CWD HLA alleles, new variants, and homozygous alleles. The concordance rate with Sanger sequencing-based typing was 100.0% for HLA-A, -B, -C, -DRB1, -DQB1, and 99.93% for HLA-DPB1. The newly identified HLA alleles were HLA-B*14:69N and HLA-DQB1*02:145.

CONCLUSION

We have successfully validated NGS HLA typing despite numerous challenges, contributing to the identification of novel alleles that impact on HLA matching and antibody evaluation in organ and tissue transplantation.

A new set of reagents and related software used for NGS based classical and non-classical HLA typing showing evidence for a greater HLA haplotype diversity

To evaluate the HLA typing performance of a new Long-Range PCR NGS set of reagents and its dedicated software, a panel of 41 reference homozygous cell lines from the International Histocompatibility Working Group (IHWG) and a panel of 376 volunteer bone marrow donors were analyzed for classical and non-classical HLA class I and class II genes. All results, except HLA-DPB1, were obtained without any ambiguities at the 3rd field level. Based on the high resolution performance of the reagents, a number of new alleles have been described not only for classical but also for non-classical HLA class I genes, leading to a more accurate haplotype definition. Linkage disequilibrium between HLA-A and HLA-G genes has been defined at 4th field level of resolution. Moreover, for the first time, HLA-DQA2 and DQB2 polymorphisms and their linkage disequilibrium with DQB1 were described.

Comparison of sequence-specific oligonucleotide probe vs next generation sequencing for HLA-A, B, C, DRB1, DRB3/B4/B5, DQA1, DQB1, DPA1, and DPB1 typing: Toward single-pass high-resolution HLA typing in support of solid organ and hematopoietic cell transplant programs

Many clinical laboratories supporting solid organ transplant programs use multiple HLA genotyping technologies, depending on individual laboratory needs. Sequence‐specific primers and quantitative polymerase chain reaction (qPCR) serve the rapid turnaround necessary for deceased donor workup, while sequence‐specific oligonucleotide probe (SSOP) technology is widely employed for higher volumes. When clinical need mandates high‐resolution data, Sanger sequencing‐based typing (SBT) has been the “gold standard.” However, all those methods commonly yield ambiguous typing results that utilize valuable laboratory resources when resolution is required. In solid organ transplantation, high‐resolution typing may provide critical information for highly sensitized patients with donor‐specific anti‐HLA antibodies (DSA), particularly when DSA involve HLA alleles not discriminated by SSOP typing. Arguments against routine use of SBT include assay complexity, long turnaround times (TAT), and increased costs. Here, we compare a next generation sequencing (NGS) technology with SSOP for accuracy, effort, turnaround time, and level of resolution for genotyping of 11 HLA loci among 289 specimens from five clinical laboratories. Results were concordant except for SSOP misassignments in eight specimens and 21 novel sequences uniquely identified by NGS. With few exceptions, SSOP generated ambiguous results while NGS provided unambiguous three‐field allele assignments. For complete HLA genotyping of up to 24 samples by either SSOP or NGS, bench work was completed on day 1 and typing results were available on day 2. This study provides compelling evidence that, although not viable for STAT typing of deceased donors, a single‐pass NGS HLA typing method has direct application for solid organ transplantation.

Quality control project of NGS HLA genotyping for the 17th International HLA and Immunogenetics Workshop

The 17th International HLA and Immunogenetics Workshop (IHIW) organizers conducted a Pilot Study (PS) in which 13 laboratories (15 groups) participated to assess the performance of the various sequencing library preparation protocols, NGS platforms and software in use prior to the workshop. The organizers sent 50 cell lines to each of the 15 groups, scored the 15 independently generated sets of NGS HLA genotyping data, and generated "consensus" HLA genotypes for each of the 50 cell lines. Proficiency Testing (PT) was subsequently organized using four sets of 24 cell lines, selected from 48 of 50 PS cell lines, to validate the quality of NGS HLA typing data from the 34 participating IHIW laboratories. Completion of the PT program with a minimum score of 95% concordance at the HLA-A, HLA-B, HLA-C, HLA-DRB1 and HLA-DQB1 loci satisfied the requirements to submit NGS HLA typing data for the 17th IHIW projects. Together, these PS and PT efforts constituted the 17th IHIW Quality Control project. Overall PT concordance rates for HLA-A, HLA-B, HLA-C, HLA-DPA1, HLA-DPB1, HLA-DQA1, HLA-DQB1, HLA-DRB1, HLA-DRB3, HLA-DRB4 and HLA-DRB5 were 98.1%, 97.0% and 98.1%, 99.0%, 98.6%, 98.8%, 97.6%, 96.0%, 99.1%, 90.0% and 91.7%, respectively. Across all loci, the majority of the discordance was due to allele dropout. The high cost of NGS HLA genotyping per experiment likely prevented the retyping of initially failed HLA loci. Despite the high HLA genotype concordance rates of the software, there remains room for improvement in the assembly of more accurate consensus DNA sequences by NGS HLA genotyping software.

Deciphering the fine nucleotide diversity of full HLA class I and class II genes in a well-documented population from sub-Saharan Africa

With the aim to understand how next‐generation sequencing (NGS) improves both our assessment of genetic variation within populations and our knowledge on HLA molecular evolution, we sequenced and analysed 8 HLA loci in a well‐documented population from sub‐Saharan Africa (Mandenka). The results of full‐gene NGS‐MiSeq sequencing compared with those obtained by traditional typing techniques or limited sequencing strategies showed that segregating sites located outside exon 2 are crucial to describe not only class I but also class II population diversity. A comprehensive analysis of exons 2, 3, 4 and 5 nucleotide diversity at the 8 HLA loci revealed remarkable differences among these gene regions, notably a greater variation concentrated in the antigen recognition sites of class I exons 3 and some class II exons 2, likely associated with their peptide‐presentation function, a lower diversity of HLA‐C exon 3, possibly related to its role as a KIR ligand, and a peculiar molecular diversity of HLA‐A exon 2, revealing demographic signals. Based on full‐length HLA sequences, we also propose that the most frequent DRB1 allele in the studied population, DRB1*13:04, emerged from an allelic conversion involving 3 potential alleles as donors and DRB1*11:02:01 as recipient. Finally, our analysis revealed a high occurrence of the DRB1*13:04‐DQA1*05:05:01‐DQB1*03:19 haplotype, possibly resulting from a selective sweep due to protection to Onchorcerca volvulus, a prevalent pathogen in West Africa. This study unveils highly relevant information on the molecular evolution of HLA genes in relation to their immune function, calling for similar analyses in other populations living in contrasting environments.

Determination of HLA-A, -B, -C, -DRB1 and -DQB1 allele and haplotype frequencies in heart failure patients

Aims

Cell therapy can be used to repair functionally impaired organs and tissues in humans. Although autologous cells have an immunological advantage, it is difficult to obtain high cell numbers for therapy. Well‐characterized banks of cells with human leukocyte antigens (HLA) that are representative of a given population are thus needed. The present study investigates the HLA allele and haplotype frequencies in a cohort of heart failure (HF) patients.

Methods and results

We carried out the HLA typing and the allele and haplotype frequency analysis in 247 ambulatory HF patients. We determined HLA class I (A, B, and C) and class II (DRB1 and DQB1) using next‐generation sequencing technology. The allele frequencies were obtained using Python for Population Genomics (PyPop) software, and HLA haplotypes were estimated using HaploStats. A total of 30 HLA‐A, 56 HLA‐B, 23 HLA‐C, 36 HLA‐DRB1, and 15 HLA‐DQB1 distinct alleles were identified within the studied cohort. The genotype frequencies of all five HLA loci were in Hardy–Weinberg equilibrium. We detected differences in HLA allele frequencies among patients when the etiological cause of HF was considered. There were a total of 494 five‐loci haplotypes, five of which were present six or more times. Moreover, the most common estimated HLA haplotype was HLA‐A*01:01, HLA‐B*08:01, HLA‐C*07:01, HLA‐DRB1*03:01, and HLA‐DQB1*02:01 (6.07% haplotype frequency per patient). Remarkably, the 11 most frequent haplotypes would cover 31.17% of the patients of the cohort in need of allogeneic cell therapy.

Conclusions

Our findings could be useful for improving allogeneic cell administration outcomes without concomitant immunosuppression.

Simple, rapid and inexpensive typing of common HLA class I alleles for immunological studies

Current HLA-typing methods are typically designed to provide exquisitely-detailed identification of multiple HLA-alleles to satisfy the requirements for organ and bone marrow transplantation or genetic studies. Many human immunological studies, on the other hand, focus around only a small number of HLA alleles that are abundant or of relevance to specific diseases. Consequently, for such studies, many HLA typing approaches are not cost-effective and are potentially complicated, slow and not easily performed in-house. Work-flow would be streamlined by a simple, inexpensive and rapid typing method able to be performed in-house. We outline a straightforward approach that provides appropriate data for much immunological research. In a predominantly Caucasian population, flow cytometry using anti-HLA-A2, -B8 and -B7 antibodies consistently and accurately screened for samples carrying the highly-abundant HLA class I alleles HLA-A*02:01, -B*08:01 and -B*07:02 that form the focus of immunological studies. Next, we describe a straightforward and simple strategy for design and use of allele-specific PCR primers to identify, at high-resolution, alleles of interest. When combined with a simple gDNA extraction technique this provides reliable, simple and inexpensive in-house HLA typing demonstrated here for highly-abundant HLA class I alleles.

HLA-B*45:22: a novel allele that differs from HLA-B*45:01:01 at several locations

Discovery of a novel HLA-B*45:22 allele in a Middle Eastern heart and lung transplant candidate.

Identifying a newly discovered HLA-C allele, HLA-C*02:138

A new allele, now named HLA-C*02:138, was discovered during testing of a registry donor for possible stem cell transplantation.

Identifying a newly discovered HLA-C allele: HLA-C*07:607

Phased sequencing identified the HLA-C*07:607 allele in an African-American patient and sibling donor.

Using Exome and Amplicon-Based Sequencing Data for High-Resolution HLA Typing with ATHLATES

ATHLATES (accurate typing of human leukocyte antigen through exome sequencing) was originally developed to analyze whole-exome sequencing (exome-seq) data from the Illumina platform and to predict the HLA genotype at 2-field or higher resolution. HLA locus-specific reads are first collected by stringent read mapping to the IMGT/HLA database. ATHLATES then performs read assembly, candidate allele identification, and genotype inference. Here, we describe the protocol of using ATHLATES for the above purpose and expand the application to analyze targeted sequencing data using amplicons of full HLA genes.

Accuracy of Programs for the Determination of Human Leukocyte Antigen Alleles from Next-Generation Sequencing Data

The human leukocyte antigen (HLA) genes code for proteins that play a central role in the function of the immune system by presenting peptide antigens to T cells. As HLA genes show extremely high genetic polymorphism, HLA typing at the allele level is demanding and is based on DNA sequencing. Determination of HLA alleles is warranted as HLA alleles are major genetic risk factors in autoimmune diseases and are matched in transplantation. Here, we compared the accuracy of several published HLA-typing algorithms that are based on next-generation sequencing (NGS) data. As genome sequencing is becoming increasingly common in research, we wanted to test how well HLA alleles can be deduced from genome data produced in studies with objectives other than HLA typing and in platforms not especially designed for HLA typing. The accuracies were assessed using datasets consisting of NGS data produced using an in-house sequencing platform, including the full 4 Mbp HLA segment, from 94 stem cell transplantation patients and exome sequences from 63 samples of the 1000 Genomes collection. In the patient dataset, none of the software gave perfect results for all the samples and genes when programs were used with the default settings. However, we found that ensemble prediction of the results or modifications of the settings could be used to improve accuracy. For the exome-only data, most of the algorithms did not perform very well. The results indicate that the use of these algorithms for accurate HLA allele determination is not straightforward when based on NGS data not especially targeted to the HLA typing and their accurate use requires HLA expertise.

Different DRB1*03:01-DQB1*02:01 haplotypes confer different risk for celiac disease

Celiac disease is associated with the HLA-DR3-DQA1*05:01-DQB1*02:01 and DR4-DQA1*03:01-DQB1*03:02 haplotypes. In addition, there are currently over 40 non-HLA loci associated with celiac disease. This study extends previous analyses on different HLA haplotypes in celiac disease using next generation targeted sequencing. Included were 143 patients with celiac disease and 135 non-celiac disease controls investigated at median 9.8 years (1.4-18.3 years). PCR-based amplification of HLA and sequencing with Illumina MiSeq technology were used for extended sequencing of the HLA class II haplotypes HLA-DRB1, DRB3, DRB4, DRB5, DQA1 and DQB1, respectively. Odds ratios were computed marginally for every allele and haplotype as the ratio of allelic frequency in patients and controls as ratio of exposure rates (RR), when comparing a null reference with equal exposure rates in cases and controls. Among the extended HLA haplotypes, the strongest risk haplotype for celiac disease was shown for DRB3*01:01:02 in linkage with DQA1*05:01-DQB1*02:01 (RR = 6.34; P-value < .0001). In a subpopulation analysis, DRB3*01:01:02-DQA1*05:01-DQB1*02:01 remained the most significant in patients with Scandinavian ethnicity (RR = 4.63; P < .0001) whereas DRB1*07:01:01-DRB4*01:03:01-DQA1*02:01-DQB1*02:02:01 presented the highest risk of celiac disease among non-Scandinavians (RR = 7.94; P = .011). The data also revealed 2 distinct celiac disease risk DR3-DQA1*05:01-DQB*02:01 haplotypes distinguished by either the DRB3*01:01:02 or DRB3*02:02:01 alleles, indicating that different DRB1*03:01-DQB1*02:01 haplotypes confer different risk for celiac disease. The associated risk of celiac disease for DR3-DRB3*01:01:02-DQA1*05:01-DQB1*02:01 is predominant among patients of Scandinavian ethnicity.

Detection of 549 new HLA alleles in potential stem cell donors from the United States, Poland and Germany

We characterized 549 new human leukocyte antigen (HLA) class I and class II alleles found in newly registered stem cell donors as a result of high‐throughput HLA typing. New alleles include 101 HLA‐A, 132 HLA‐B, 105 HLA‐C, 2 HLA‐DRB1, 89 HLA‐DQB1 and 120 HLA‐DPB1 alleles. Mainly, new alleles comprised single nucleotide variations when compared with homologous sequences. We identified nonsynonymous nucleotide mutations in 70.7% of all new alleles, synonymous variations in 26.4% and nonsense substitutions in 2.9% (null alleles). Some new alleles (55, 10.0%) were found multiple times, HLA‐DPB1 alleles being the most frequent among these. Furthermore, as several new alleles were identified in individuals from ethnic minority groups, the relevance of recruiting donors belonging to such groups and the importance of ethnicity data collection in donor centers and registries is highlighted.

HLA imputation in an admixed population: An assessment of the 1000 Genomes data as a training set

Methods to impute HLA alleles based on dense single nucleotide polymorphism (SNP) data provide a valuable resource to association studies and evolutionary investigation of the MHC region. The availability of appropriate training sets is critical to the accuracy of HLA imputation, and the inclusion of samples with various ancestries is an important pre-requisite in studies of admixed populations. We assess the accuracy of HLA imputation using 1000 Genomes Project data as a training set, applying it to a highly admixed Brazilian population, the Quilombos from the state of São Paulo. To assess accuracy, we compared imputed and experimentally determined genotypes for 146 samples at 4 HLA classical loci. We found imputation accuracies of 82.9%, 81.8%, 94.8% and 86.6% for HLA-A, -B, -C and -DRB1 respectively (two-field resolution). Accuracies were improved when we included a subset of Quilombo individuals in the training set. We conclude that the 1000 Genomes data is a valuable resource for construction of training sets due to the diversity of ancestries and the potential for a large overlap of SNPs with the target population. We also show that tailoring training sets to features of the target population substantially enhances imputation accuracy.

HLA Haplotype Validator for quality assessments of HLA typing

HLA alleles are observed in specific haplotypes, due to Linkage Disequilibrium (LD) between particular alleles. Haplotype frequencies for alleles in strong LD have been established for specific ethnic groups and racial categories. Application of high-resolution HLA typing using Next Generation Sequencing (NGS) is becoming a common practice in research and clinical laboratory settings. HLA typing errors using NGS occasionally occur due to allelic sequence imbalance or misalignment. Manual inspection of HLA genotypes is labor intensive and requires an in-depth knowledge of HLA alleles and haplotypes. We developed the "HLA Haplotype Validator (HLAHapV)" software, which inspects an HLA genotype for both the presence of common and well-documented alleles and observed haplotypes. The software also reports warnings when rare alleles, or alleles that do not belong to recognized haplotypes, are found. The software validates observable haplotypes in genotype data, providing increased confidence regarding the accuracy of the HLA typing, and thus reducing the effort involved in correcting potential HLA typing errors. The HLAHapV software is a powerful tool for quality control of HLA genotypes prior to the application of downstream analyses. We demonstrate the use of the HLAHapV software for identifying unusual haplotypes, which can lead to finding potential HLA typing errors.

Minimum information for reporting next generation sequence genotyping (MIRING): Guidelines for reporting HLA and KIR genotyping via next generation sequencing

The development of next-generation sequencing (NGS) technologies for HLA and KIR genotyping is rapidly advancing knowledge of genetic variation of these highly polymorphic loci. NGS genotyping is poised to replace older methods for clinical use, but standard methods for reporting and exchanging these new, high quality genotype data are needed. The Immunogenomic NGS Consortium, a broad collaboration of histocompatibility and immunogenetics clinicians, researchers, instrument manufacturers and software developers, has developed the Minimum Information for Reporting Immunogenomic NGS Genotyping (MIRING) reporting guidelines. MIRING is a checklist that specifies the content of NGS genotyping results as well as a set of messaging guidelines for reporting the results. A MIRING message includes five categories of structured information - message annotation, reference context, full genotype, consensus sequence and novel polymorphism - and references to three categories of accessory information - NGS platform documentation, read processing documentation and primary data. These eight categories of information ensure the long-term portability and broad application of this NGS data for all current histocompatibility and immunogenetics use cases. In addition, MIRING can be extended to allow the reporting of genotype data generated using pre-NGS technologies. Because genotyping results reported using MIRING are easily updated in accordance with reference and nomenclature databases, MIRING represents a bold departure from previous methods of reporting HLA and KIR genotyping results, which have provided static and less-portable data. More information about MIRING can be found online at miring.immunogenomics.org.