Phase-defined complete sequencing of the HLA genes by next-generation sequencing

Frequencies of HLA-B alleles in Indonesian Malay Ethnic

Background

The HLA-B alleles have been used as a marker to predict drug-induced adverse reactions and as a major contributor to hypersensitivity reactions. We examined the feasibility of HLA-B alleles as pharmacogenomic markers of drug-induced hypersensitivity in an Indonesian Malay Ethnic.

Methods

Fifty-eight Indonesian individuals of Malay ethnicity were enrolled in this study. HLA-B alleles were determined using reverse sequence-specific oligonucleotide probe coupled with xMAP technology.

Results

HLA-B*15:02 (15.52%), HLA-B*35:05 (9.48%), and HLA-B*07:05 (7.76%) were frequent alleles in the Indonesian Malay ethnic populations. We discovered at least eight pharmacogenomics markers of drug-induced hypersensitivity: HLA-B*15:02, HLA-B*15:21, HLA-B*13:01, HLA-B*35:05, HLA-B*38:02, HLA-B*51:01, HLA-B*57:01, and HLA-B*58:01. HLA-B*15:02 was in the same serotype group with HLA-B*15:21, which is a B-75 serotype associated with genetic predisposition for carbamazepine-induced Stevens-Johnson syndrome and toxic epidermal necrolysis. The Indonesian population, represented by Malay, Javanese, and Sundanese ethnicities, was similar to South East Asian, Han Chinese, and Taiwanese populations based on HLA-B*15:02 frequency as the most common allele found in Malay ethnics.

Conclusion

We provided valuable information on the frequency of drug hypersensitivity-associated HLA-B alleles in Indonesian Malay ethnic population, which can improve treatment safety.

Association of HLA-A*11:01, -A*24:02, and -B*18:01 with Prostate Cancer Risk: A Case-Control Study

The major histocompatibility complex (MHC) loci, the most polymorphic regions within the human genome, encode protein complexes responsible for antigen presentation and CD4+ and CD8+ cell activation. In prostate cancer (PCa), the second most diagnosed cancer in the male population, MHC loci undergo significant changes in their expression patterns, which affect the ability of the immune system to attack and eliminate malignant cells. The purpose of this study was to explore the genetic diversity of human leukocyte antigen (HLA)-A and HLA-B in patients with PCa and healthy controls (HCs) by performing HLA genotyping using NGS technology. The analysis highlighted statistically significant differences (p < 0.05) in the prevalence of three alleles (A*11:01, A*24:02, and B*18:01). Among the HCs analyzed, 14.89% had A*11:01, 20.21% had A*24:02, and 30.61% had B*18:01; while 5.21% of patients with PCa presented A*11:01, 9.38% presented A*24:02, 18.08% presented B*18:01. Odds ratio (OR) calculations underlined a negative association between the three alleles and the risk of PCa (OR < 1). The results presented in this study suggest a protective role of A*11:01, A*24:02, and B*18:01 in PCa.

Tutorial: a statistical genetics guide to identifying HLA alleles driving complex disease

The human leukocyte antigen (HLA) locus is associated with more complex diseases than any other locus in the human genome. In many diseases, HLA explains more heritability than all other known loci combined. In silico HLA imputation methods enable rapid and accurate estimation of HLA alleles in the millions of individuals that are already genotyped on microarrays. HLA imputation has been used to define causal variation in autoimmune diseases, such as type I diabetes, and in human immunodeficiency virus infection control. However, there are few guidelines on performing HLA imputation, association testing, and fine mapping. Here, we present a comprehensive tutorial to impute HLA alleles from genotype data. We provide detailed guidance on performing standard quality control measures for input genotyping data and describe options to impute HLA alleles and amino acids either locally or using the web-based Michigan Imputation Server, which hosts a multi-ancestry HLA imputation reference panel. We also offer best practice recommendations to conduct association tests to define the alleles, amino acids, and haplotypes that affect human traits. Along with the pipeline, we provide a step-by-step online guide with scripts and available software ( https://github.com/immunogenomics/HLA_analyses_tutorial ). This tutorial will be broadly applicable to large-scale genotyping data and will contribute to defining the role of HLA in human diseases across global populations.

Whole blood transcriptome profiling identifies gene expression subnetworks and a key gene characteristic of the rare type of osteomyelitis

Chronic non-bacterial osteomyelitis (CNO) is a rare and severe inflammatory bone disorder that can occur in the jaw. It is often associated with systemic conditions including autoimmune deficiency. Medical management of patients and establishment of a correct diagnosis are difficult as the etiology of the disease remains unknown. Therefore, little is known about the disease characteristics at the gene expression level. Here, we explored aspects of CNO based on whole blood RNA sequencing (>6 Gb per sample) of 11 patients and 9 healthy controls in Japan and on a recently developed method that is applicable to small datasets, can estimate a directed gene network, and extract a subnetwork of genes underlying patient characteristics. We identified nine subnetworks, comprising 26 differentially regulated edges and 36 genes, with the gene encoding glycophorin C (GYPC) presenting the highest discrimination ability. The expression of the gene was mostly lower in patients with CNO than in the healthy controls, suggesting an abnormal status of red cells in patients with CNO. This study enhances our understanding of CNO at the transcriptome level and further provides a framework for whole blood RNA sequencing and analysis of data obtained for a better diagnosis of the disease.

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We explored new aspects of chronic non-bacterial osteomyelitis (CNO) via whole-blood RNA-seq and gene network analysis.

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Nine subnetworks of genes were identified.

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A GYPC-encoding gene had the highest discrimination ability in these subnetworks.

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The expression level of the gene suggested an abnormal status of red cells in the patients.

Atopy as Immune Dysregulation: Offender Genes and Targets

Allergic diseases are a heterogeneous group of disorders resulting from exaggerated type 2 inflammation. Although typically viewed as polygenic multifactorial disorders caused by the interaction of several genes with the environment, we have come to appreciate that allergic diseases can also be caused by monogenic variants affecting the immune system and the skin epithelial barrier. Through a myriad of genetic association studies and high-throughput sequencing tools, many monogenic and polygenic culprits of allergic diseases have been described. Identifying the genetic causes of atopy has shaped our understanding of how these conditions occur and how they may be treated and even prevented. Precision diagnostic tools and therapies that address the specific molecular pathways implicated in allergic inflammation provide exciting opportunities to improve our care for patients across the field of allergy and immunology. Here, we highlight offender genes implicated in polygenic and monogenic allergic diseases and list targeted therapeutic approaches that address these disrupted pathways.

A Single-Center Experience on HLA Typing with 11 Loci Next Generation Sequencing in Korean Patients with Hematologic Disease

The human leukocyte antigen (HLA) system comprises the most polymorphic genes of the human genome and is famous for its potential pathological roles. To accurately type HLA genes and find HLA-matched donors, which are critical for effective hematopoietic transplantation, HLA typing using next-generation sequencing (NGS) was implemented. We aimed to share the experience of HLA typing using NGS in patients with hematologic malignancies and evaluate its association with hematologic diseases. Data from 211 Korean, non-familial patients diagnosed with a hematologic disease were reviewed, and NGS was performed for 11 HLA loci. Three-field HLA typing with G code was successfully achieved for all loci and the known linkage between HLA-DRB3/4/5 and HLA-DRB1 was fully matched. Therefore, NGS-based HLA typing enables a detailed, high-resolution analysis of the HLA system that can help with the selection of suitable donors. Notably, HLA-DRB1*08:02:01G was significantly associated with myelodysplastic syndrome. Although this result confirms the tendency of some alleles to be associated with hematological disorders, this may not be the case in hematologic malignancies. Nonetheless, NGS-based HLA typing data for HLA-DP, HLA-DQ, and HLA-DRB3/4/5 are still warranted for a better understanding of the corresponding locus.

A novel swab storage gel is superior to dry swab DNA collection, and enables long-range high resolution NGS HLA typing from buccal cell samples

HLA sequence-based DNA typing (SBT) by long-range PCR amplification (LR PCR) and next-generation sequencing (NGS) is a high-throughput DNA sequencing method (LR-NGS-SBT) for the efficient and sensitive detection of novel and null HLA alleles to the field-4 level of allelic resolution without phase ambiguity. However, the accuracy and reliability of the HLA typing results using buccal cells (BCs) and saliva as genetic source materials for the LR-NGS-SBT method are dependent largely on the quality of the extracted genomic DNA (gDNA) because a large degree of gDNA fragmentation can result in insufficient PCR amplification with the incorrect assignment of HLA alleles due to allele dropouts. In this study, we developed a new cost-efficient swab storage gel (SSG) for wet swab collection of BCs (BC-SSG) and evaluated its usefulness by performing different DNA analytical parameters including LR-NGS-SBT to compare the quality and quantity of gDNA extracted from BCs (in SSG or air dried), blood and saliva of 30 subjects. The BC-SSG samples after 5 days of storage revealed qualitative and quantitative DNA values equivalent to that of blood and/or saliva and better than swabs that were only air-dried (BC-nSSG). Moreover, all the gDNA extracted from blood, saliva and BC-SSG samples were HLA-typed successfully to an equivalent total of 408 alleles for each sample type. Therefore, the application of BC-SSG collection media for LR-NGS-SBT has benefits over BC dried samples (dry swabs) such as reducing retesting and the number of untestable BC samples due to insufficient DNA amplification. This article is protected by copyright. All rights reserved.

HLA associations, somatic loss of HLA expression, and clinical outcomes in immune aplastic anemia

Immune aplastic anemia (AA) features somatic loss of HLA class I allele expression on bone marrow cells, consistent with a mechanism of escape from T-cell-mediated destruction of hematopoietic stem and progenitor cells. The clinical significance of HLA abnormalities has not been well characterized. We examined the somatic loss of HLA class I alleles and correlated HLA loss and mutation-associated HLA genotypes with clinical presentation and outcomes after immunosuppressive therapy in 544 AA patients. HLA class I allele loss was detected in 92 (22%) of the 412 patients tested, in whom there were 393 somatic HLA gene mutations and 40 instances of loss of heterozygosity. Most frequently affected was HLA-B*14:02, followed by HLA-A*02:01, HLA-B*40:02, HLA-B*08:01, and HLA-B*07:02. HLA-B*14:02, HLA-B*40:02, and HLA-B*07:02 were also overrepresented in AA. High-risk clonal evolution was correlated with HLA loss, HLA-B*14:02 genotype, and older age, which yielded a valid prediction model. In 2 patients, we traced monosomy 7 clonal evolution from preexisting clones harboring somatic mutations in HLA-A*02:01 and HLA-B*40:02. Loss of HLA-B*40:02 correlated with higher blood counts. HLA-B*07:02 and HLA-B*40:01 genotypes and their loss correlated with late-onset of AA. Our results suggest the presence of specific immune mechanisms of molecular pathogenesis with clinical implications. HLA genotyping and screening for HLA loss may be of value in the management of immune AA. This study was registered at clinicaltrials.gov as NCT00001964, NCT00061360, NCT00195624, NCT00260689, NCT00944749, NCT01193283, and NCT01623167.

HLA genotyping in Japanese patients with multiple myeloma receiving bortezomib: An exploratory biomarker study of JCOG1105 (JCOG1105A1)

Bortezomib (Btz) shows robust efficacy in patients with multiple myeloma (MM); however, some patients experience suboptimal responses and show specific toxicities. Therefore, we attempted to identify specific HLA alleles associated with Btz-related toxicities and response to treatment. Eighty-two transplant-ineligible patients with newly diagnosed MM enrolled in a phase II study (JCOG1105) comparing two less intensive melphalan, prednisolone, plus Btz (MPB) regimens were subjected to HLA typing. The frequency of each allele was compared between the groups, categorized based on toxicity grades and responses to MPB therapy. Among 82 patients, the numbers of patients with severe peripheral neuropathy (PN; grade 2 or higher), skin disorders (SD; grade 2 or higher), and pneumonitis were 16 (19.5%), 15 (18.3%), and 6 (7.3%), respectively. Complete response was achieved in 10 (12.2%) patients. Although no significant HLA allele was identified by multiple comparisons, several candidates were identified. HLA-B*40:06 was more prevalent in patients with severe PN than in those with less severe PN (odds ratio [OR] = 6.76). HLA-B*40:06 and HLA-DRB1*12:01 were more prevalent in patients with SD than in those with less severe SD (OR = 7.47 and OR = 5.55, respectively). HLA-DRB1*08:02 clustered in the group of patients with pneumonitis (OR = 11.34). Complete response was achieved in patients carrying HLA-DQB1*03:02, HLA-DQB1*05:01, and HLA-DRB1*01:01 class II alleles. HLA genotyping could help predict Btz-induced toxicity and treatment efficacy in patients with MM, although this needs further validation.

Allelic and haplotypic HLA diversity in indigenous Malaysian populations explored using Next Generation Sequencing

The heterogenous population of Malaysia includes more than 50 indigenous groups, and characterizing their HLA diversity would not only provide insights to their ancestry, but also on the effects of natural selection on their genome. We utilized hybridization-based sequence capture and short-read sequencing on the HLA region of 172 individuals representing seven indigenous groups in Malaysia (Jehai, Kintaq, Temiar, Mah Meri, Seletar, Temuan, Bidayuh). Allele and haplotype frequencies of HLA-A, -B, -C, -DRB1, -DQA1, -DQB1, -DPA1, and -DPB1 revealed several ancestry-informative markers. Using SNP-based heterozygosity and pairwise Fst, we observed signals of natural selection, particularly in HLA-A, -C and -DPB1 genes. Consequently, we showed the impact of natural selection on phylogenetic inference using HLA and non-HLA SNPs. We demonstrate the utility of Next Generation Sequencing for generating unambiguous, high-throughput, high-resolution HLA data that adds to our knowledge of HLA diversity and natural selection in indigenous minority groups.

Identification of 8-Digit HLA-A, -B, -C, and -DRB1 Allele and Haplotype Frequencies in Koreans Using the One Lambda AllType Next-Generation Sequencing Kit

Background

Recent studies have successfully implemented next-generation sequencing (NGS) in HLA typing. We performed HLA NGS in a Korean population to estimate HLA-A, -B, -C, and -DRB1 allele and haplotype frequencies up to an 8-digit resolution, which might be useful for an extended application of HLA results.

Methods

A total of 128 samples collected from healthy unrelated Korean adults, previously subjected to Sanger sequencing for 6-digit HLA analysis, were used. NGS was performed for HLA-A, -B, -C, and -DRB1 using the AllType NGS kit (One Lambda, West Hills, CA, USA), Ion Torrent S5 platform (Thermo Fisher Scientific, Waltham, MA, USA), and Type Steam Visual NGS analysis software (One Lambda).

Results

Eight HLA alleles showed frequencies of ≥10% in the Korean population, namely, A*24:02:01:01 (19.5%), A*33:03:01 (15.6%), A*02:01:01:01 (14.5%), A*11:01:01:01 (13.3%), B*15:01:01:01 (10.2%), C*01:02:01 (19.9%), C*03:04:01:02 (11.3%), and DRB1*09:01:02 (10.2%). Nine previous 6-digit HLA alleles were further identified as two or more 8-digit HLA alleles. Of these, eight alleles (A*24:02:01, B*35:01:01, B*40:01:02, B*55:02:01, B*58:01:01, C*03:02:02, C*07:02:01, and DRB1*07:01:01) were identified as two 8-digit HLA alleles, and one allele (B*51:01:01) was identified as three 8-digit HLA alleles. The most frequent four-loci haplotype was HLA-A*33:03:01-B*44:03:01:01-C*14:03-DRB1*13:02:01.

Conclusions

We identified 8-digit HLA-A, -B, -C, and -DRB1 allele and haplotype frequencies in a healthy Korean population using NGS. These new data can be used as a representative Korean data for further disease-related HLA type analysis.

Analysis of HLA gene polymorphisms in East Africans reveals evidence of gene flow in two Semitic populations from Sudan

Sudan, a northeastern African country, is characterized by high levels of cultural, linguistic, and genetic diversity, which is believed to be affected by continuous migration from neighboring countries. Consistent with such demographic effect, genome-wide SNP data revealed a shared ancestral component among Sudanese Afro-Asiatic speaking groups and non-African populations, mainly from West Asia. Although this component is shared among all Afro-Asiatic speaking groups, the extent of this sharing in Semitic groups, such as Sudanese Arab, is still unknown. Using genotypes of six polymorphic human leukocyte antigen (HLA) genes (i.e., HLA-A, -C, -B, -DRB1, -DQB1, and -DPB1), we examined the genetic structure of eight East African ethnic groups with origins in Sudan, South Sudan, and Ethiopia. We identified informative HLA alleles using principal component analysis, which revealed that the two Semitic groups (Gaalien and Shokrya) constituted a distinct cluster from the other Afro-Asiatic speaking groups in this study. The HLA alleles that distinguished Semitic Arabs co-exist in the same extended HLA haplotype, and those alleles are in strong linkage disequilibrium. Interestingly, we find the four-locus haplotype "C*12:02-B*52:01-DRB1*15:02-DQB1*06:01" exclusively in non-African populations and it is widely spread across Asia. The identification of this haplotype suggests a gene flow from Asia, and likely these haplotypes were brought to Africa through back migration from the Near East. These findings will be of interest to biomedical and anthropological studies that examine the demographic history of northeast Africa.

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.

Challenges in the application of NGS in the clinical laboratory

Next-generation sequencing (NGS), also known as massively parallel sequencing, has revolutionized genomic research. The current advances in NGS technology make it possible to provide high resolution, high throughput HLA typing in clinical laboratories. The focus of this review is on the recent development and implementation of NGS in clinical laboratories. Here, we examine the critical role of NGS technologies in clinical immunology for HLA genotyping. Two major NGS platforms (Illumina and Ion Torrent) are characterized including NGS library preparation, data analysis, and validation. Challenges of NGS implementation in the clinical laboratory are also discussed, including sequencing error rate, bioinformatics, result interpretation, analytic sensitivity, as well as large data storage. This review aims to promote the broader applications of NGS technology in clinical laboratories and advocate for the novel applications of NGS to drive future research.

Standard reference sequences for submission of HLA genotyping for the 18th International HLA and Immunogenetics Workshop

The International human leukocyte antigen (HLA) and Immunogenetics Workshops (IHIWs) have fostered international collaborations of researchers and experts in the fields of HLA, histocompatibility and immunology. These IHIW collaborations have comprised many projects focused on achieving a variety of specific goals. The international and collaborative nature of these projects necessitates the collection and analysis of complex data generated in multiple laboratories, often using multiple methods of acquisition. Collection and storage of these data in a consistent way adds value to IHIW projects, which can be extended to future work. DNA‐based genotyping data, especially HLA genotyping data, can be transmitted in the form of a Histoimmunogenetics Markup Language (HML) document. HML facilitates clear communication of a genotype and supporting metadata, such as, sequencing platform, laboratory assays, consensus sequence, and interpretation. Sequence information can be reported relative to known reference sequences, which add meaning and context to genotypes. Selecting the correct reference sequence for a given allele sequence is nuanced, and guidelines have emerged through collaborative community efforts such as Data Standards Hackathons. Here, we describe the guidelines established for the selection of reference sequences to be used in transmission of HLA (and MICA/MICB) genotyping data for the 18th IHIW.

Genome wide association study of HTLV-1-associated myelopathy/tropical spastic paraparesis in the Japanese population

Human T cell leukemia virus type 1 (HTLV-1) proviral load is associated with the risk of developing HTLV-1–associated myelopathy/tropical spastic paraparesis (HAM/TSP) and several small-scale candidate gene approaches have also identified associations of particular HLA alleles with HAM/TSP risk. However, no large-scale genome-wide association (GWA) studies have been performed to date. By a large-scale GWA study and comprehensive genotyping of classical HLA genes, we found that HLA-DRB1 alleles carrying leucine at the antigen presentation groove domain (DRB1-GB-7-Leu) increased the susceptibility to HAM/TSP. Individuals who were homozygous for DRB1-GB-7-Leu had a ninefold increased odds of developing HAM/TSP. This effect of DRB1-GB-7-Leu was independent of proviral load. These findings identify DRB1-GB-7-Leu as a genetic risk marker of HAM/TSP development.

HTLV-1–associated myelopathy (HAM/TSP) is a chronic and progressive inflammatory disease of the central nervous system. The aim of our study was to identify genetic determinants related to the onset of HAM/TSP in the Japanese population. We conducted a genome-wide association study comprising 753 HAM/TSP patients and 899 asymptomatic HTLV-1 carriers. We also performed comprehensive genotyping of HLA-A, -B, -C, -DPB1, -DQB1, and -DRB1 genes using next-generation sequencing technology for 651 HAM/TSP patients and 804 carriers. A strong association was observed in HLA class I (P = 1.54 × 10⁻⁹) and class II (P = 1.21 × 10⁻⁸) loci with HAM/TSP. Association analysis using HLA genotyping results showed that HLA-C*07:02 (P = 2.61 × 10⁻⁵), HLA-B*07:02 (P = 4.97 × 10⁻¹⁰), HLA-DRB1*01:01 (P = 1.15 × 10⁻⁹) and HLA-DQB1*05:01 (P = 2.30 × 10⁻⁹) were associated with disease risk, while HLA-B*40:06 (P = 3.03 × 10⁻⁵), HLA-DRB1*15:01 (P = 1.06 × 10⁻⁵) and HLA-DQB1*06:02 (P = 1.78 × 10⁻⁶) worked protectively. Logistic regression analysis identified amino acid position 7 in the G-BETA domain of HLA-DRB1 as strongly associated with HAM/TSP (P = 9.52 × 10⁻¹⁰); individuals homozygous for leucine had an associated increased risk of HAM/TSP (odds ratio, 9.57), and proline was protective (odds ratio, 0.65). Both associations were independent of the known risk associated with proviral load. DRB1-GB-7-Leu was not significantly associated with proviral load. We have identified DRB1-GB-7-Leu as a genetic risk factor for HAM/TSP development independent of proviral load. This suggests that the amino acid residue may serve as a specific marker to identify the risk of HAM/TSP even without knowledge of proviral load. In light of its allele frequency worldwide, this biomarker will likely prove useful in HTLV-1 endemic areas across the globe.

HLA-B*39:01:01 is a novel risk factor for antithyroid drug-induced agranulocytosis in Japanese population

Antithyroid drug (ATD) is a mainstay of Graves' disease (GD). About 0.1-0.5% of patients with GD treated with ATD exhibit ATD-induced agranulocytosis, which is characterized by severe reduction of circulating neutrophils. Immune-mediated responses have been proposed as a possible mechanism for the pathogenesis of ATD-induced agranulocytosis. Although it has been reported that the HLA class II allele (HLA-DRB1*08:03) was associated with ATD-induced agranulocytosis in multiple populations, the entire HLA region have not been explored in Japanese. Therefore, we performed HLA sequencing for 10 class I and 11 class II genes in 87 patients with ATD-induced agranulocytosis and 384 patients with GD who did not show ATD-induced agranulocytosis. By conducting case-control association studies at the HLA allele and haplotype levels, we replicated the association between HLA-DRB1*08:03:02 and ATD-induced agranulocytosis (P = 5.2 × 10^-7, odds ratio = 2.80), and identified HLA-B*39:01:01 as an independent risk factor (P = 1.4 × 10^-3, odds ratio = 3.35). To verify reproducibility of the novel association of HLA-B*39:01:01, we reanalyzed allele frequency data for HLA-B*39:01:01 from previous case-control association studies. The association of HLA-B*39:01:01 was significantly replicated in Chinese (P = 9.0 × 10^-3), Taiwanese (P = 1.1 × 10^-3), and European populations (P = 5.2 × 10^-4). A meta-analysis combining results from the previous and current studies reinforced evidence of the association between HLA-B*39:01:01 and ATD-induced agranulocytosis (P_meta = 1.2 × 10^-9, pooled OR = 3.66, 95% CI; 2.41-5.57). The results of this study will provide a better understanding of the pathogenesis of ATD-induced agranulocytosis in the context of HLA-mediated hypersensitivity reactions.

High-Throughput Sequencing to Investigate Associations Between HLA Genes and Metamizole-Induced Agranulocytosis

Background and Objective: Agranulocytosis is a rare and potentially life-threatening complication of metamizole (dipyrone) intake that is characterized by a loss of circulating neutrophil granulocytes. While the mechanism underlying this adverse drug reaction is not well understood, involvement of the immune system has been suggested. In addition, associations between genetic variants in the Human Leukocyte Antigen (HLA) region and agranulocytosis induced by other drugs have been reported. The aim of the present study was to assess whether genetic variants in classical HLA genes are associated with the susceptibility to metamizole-induced agranulocytosis (MIA) in a European population by targeted resequencing of eight HLA genes.

Design: A case-control cohort of Swiss patients with a history of neutropenia or agranulocytosis associated with metamizole exposure (n = 53), metamizole-tolerant (n = 39) and unexposed controls (n = 161) was recruited for this study. A high-throughput resequencing (HTS) and high-resolution typing method was used to sequence and analyze eight HLA loci in a discovery subset of this cohort (n = 31 cases, n = 38 controls). Identified candidate alleles were investigated in the full Swiss cohort as well as in two independent cohorts from Germany and Spain using HLA imputation from genome-wide SNP array data. In addition, variant calling based on HTS data was performed in the discovery subset for the class I genes HLA-A, -B, and -C using the HLA-specific mapper hla-mapper.

Results: Eight candidate alleles (p < 0.05) were identified in the discovery subset, of which HLA-C^∗04:01 was associated with MIA in the full Swiss cohort (p < 0.01) restricted to agranulocytosis (ANC < 0.5 × 10⁹/L) cases. However, no candidate allele showed a consistent association in the Swiss, German and Spanish cohorts. Analysis of individual sequence variants in class I genes produced consistent results with HLA typing but did not reveal additional small nucleotide variants associated with MIA.

Conclusion: Our results do not support an HLA-restricted T cell-mediated immune mechanism for MIA. However, we established an efficient high-resolution (three-field) eight-locus HTS HLA resequencing method to interrogate the HLA region and demonstrated the feasibility of its application to pharmacogenetic studies.

Naming HLA diversity: A review of HLA nomenclature

The development of a standardized HLA nomenclature has been critical in our understanding of the HLA system and in facilitating the clinical applications of HLA. The Nomenclature Committee for Factors of the HLA System, established in 1968, has overseen the development and usage of nomenclature based on serologic specificities, cellular responses, and DNA sequences. Their decisions have been guided by community consensus reached through 17 international workshops beginning in 1964 and continuing today. Two websites provide a curated database of the sequences of over 26,000 HLA alleles and a reference site for the current nomenclature. This review covers the major steps in the development of the HLA nomenclature as well as the efforts of other groups to extend its usefulness for research and clinical applications.

High-Resolution HLA Typing of HLA-A, -B, -C, -DRB1, and -DQB1 in Kinh Vietnamese by Using Next-Generation Sequencing

Human leukocyte antigen (HLA) genotyping displays the particular characteristics of HLA alleles and haplotype frequencies in each population. Although it is considered the current gold standard for HLA typing, high-resolution sequence-based HLA typing is currently unavailable in Kinh Vietnamese populations. In this study, high-resolution sequence-based HLA typing (3-field) was performed using an amplicon-based next-generation sequencing platform to identify the HLA-A, -B, -C, -DRB1, and -DQB1 alleles of 101 unrelated healthy Kinh Vietnamese individuals from southern Vietnam. A total of 28 HLA-A, 41 HLA-B, 21 HLA-C, 26 HLA-DRB1, and 25 HLA-DQB1 alleles were identified. The most frequently occurring HLA alleles were A^∗11:01:01, B^∗15:02:01, C^∗07:02:01, DRB1^∗12:02:01, and DQB1^∗03:01:01. Haplotype calculation showed that A^∗29:01:01∼B^∗07:05:01, DRB1^∗12:02:01∼DQB1^∗3:01:01, A^∗29:01:01∼C^∗15:05:02∼B^∗07:05:01, A^∗33:03:01∼B^∗58:01:01∼DRB1^∗03:01:01, and A^∗29:01:01∼C^∗15:05:02∼B^∗07:05:01∼DRB1^∗10:01:01∼DQB1^∗05:01:01 were the most common haplotypes in the southern Kinh Vietnamese population. Allele distribution and haplotype analyses demonstrated that the Vietnamese population shares HLA features with South-East Asians but retains unique characteristics. Data from this study will be potentially applicable in medicine and anthropology.

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.

Next generation sequencing of 11 HLA loci characterises a diverse UK cord blood bank

The introduction of next generation sequencing (NGS) for stem cell donor registry typing has contributed to faster identification of compatible stem cell donors. However, the successful search for a matched unrelated donor for some patient groups is still affected by their ethnicity. In this study, DNA samples from 714 National Health Service (NHS) Cord Blood Bank donors were typed for HLA-A, -B, -C, -DRB1, -DRB345, -DQA1, -DQB1, -DPA1 and -DPB1 by NGS. Analysis of the ethnic diversity showed a high level of diversity, with the cohort comprising of 62.3% European and 37.7% of either multi-ethnic or non-European donors, of which 12.3% were multi-ethnic. The HLA diversity was further confirmed using PyPop analysis, 405 distinct alleles were observed in the overall NHS-CBB cohort, of which 37 alleles are non-CWD, including A*31:14N, B*35:68:02, C*14:23 and DQA1*05:10. Furthermore, HLA-DQA1 and HLA-DPA1 analysis showed 12% and 10%, respectively, of the alleles currently submitted to IMGT, confirming further diversity of the NHS-CBB cohort. The application of 11 HLA loci resolution by NGS revealed a high level of diversity in the NHS-CBB cohort. The incorporation of this data coupled with ethnicity data could lead to improved donor selection, contributing to better clinical outcomes for patients.

A new HLA-C allele with an alternative splice site in exon 3: HLA-C*03:23N

We identified a probable new null HLA-C allele, C*03:23N, which originated from C*03:04:01:02, but does not react with Cw3 antibodies. This allele was identified by sequence analysis, which indicated that a single G-to-A substitution at position 406 in exon 3 created a null allele under a new mechanism: the mutation changes the position of the intron 2-exon 3 splice site to be further into exon 3, leading to a frameshift and a premature stop codon. Sequence analysis of cDNA confirmed the existence of the causative alternative acceptor splice site and the resultant deletion of 64 nucleotides in exon 3. Analysis of 220 blood or bone marrow donors in Japan with C*03:23N demonstrated that Japanese HLA-C*03:23N is on the haplotype A*26:01∼C*03:23N∼B*40:02∼DRB1*09:01.

A Targeted Genetic Association Study of the Rare Type of Osteomyelitis

Chronic nonbacterial osteomyelitis is a rare bone disorder that can be found in the jaw. It is often associated with systemic conditions, including autoimmune deficiencies. However, little is known about how the genetic and immunologic background of patients influences the disease. Here, we focus on human leukocyte antigen (HLA), killer cell immunoglobulin-like receptors (KIRs), and their specific combinations that have been difficult to analyze owing to their high diversity. We employed a recently developed technology of simultaneous typing of HLA alleles and KIR haplotype and investigated alleles of the 35 HLA loci and KIR haplotypes composed of centromeric and telomeric motifs in 18 cases and 18 controls for discovery and 472 independent controls for validation. We identified an amino acid substitution of threonine at position 94 of HLA-C in combination with the telomeric KIR genotype of haplotype tA01/tB01 that had significantly higher frequency (>20%) in the case population than in both control populations. Multiple logistic regression analysis based on a dominant model with adjustments for age and sex revealed and validated its statistical significance and high predictive accuracy (C-statistic ≥0.85). Structure-based analysis revealed that the combination of the amino acid change in HLA-C and the telomeric genotype tA01/tB01 could be associated with lower stability of HLA-C. This is the first case-control study of a rare disease that employed the latest sequencing technology enabling simultaneous typing and investigated amino acid polymorphisms at HLA loci in combination with KIR haplotype.

High-Definition Genomic Analysis of HLA Genes Via Comprehensive HLA Allele Genotyping

HLA is essential for various medical applications, such as genomic studies of multifactorial diseases, including immune system and inflammation-related disorders. Therefore, an accurate HLA typing method that is applicable for any allele registered in HLA allele databases is required to deduce scientific evidence related to disorders. Here, we describe a method for determining HLA alleles from next-generation sequencing (NGS) results by using currently available HLA sequence data in public HLA databases and show its application in association analysis.

Rapid High-Resolution Typing of Class I HLA Genes by Nanopore Sequencing

Nanopore sequencing, enabled initially by the MinION device from Oxford Nanopore Technologies (ONT), is the only technology that offers portable, single-molecule sequencing and ultralong reads. The technology is ideal for the typing of human leukocyte antigen (HLA) genes for transplantation and cancer immunotherapy. However, such applications have been hindered by the high error rate of nanopore sequencing reads. We developed the workflow and bioinformatic pipeline, Athlon (accurate typing of human leukocyte antigen by Oxford Nanopore), to perform high-resolution typing of Class I HLA genes by nanopore sequencing. The method features a novel algorithm for candidate allele selection, followed by error correction through consensus building. Here, we describe the protocol of using Athlon packaged in a VirtualBox image for the above application.

Next-generation sequencing identifies contribution of both class I and II HLA genes on susceptibility of multiple sclerosis in Japanese

Background

The spectrum of classical and non-classical HLA genes related to the risk of multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) in the Japanese population has not been studied in detail. We conducted a case-control analysis of classical and non-classical HLA genes.

Methods

We used next-generation sequencing (NGS)-based HLA genotyping methods for mapping risk for 45 MS patients, 31 NMOSD patients, and 429 healthy controls. We evaluated the association of the HLA variants with the risk of MS and NMOSD using logistic regression analysis and Fisher’s exact test.

Results

We confirmed that HLA-DRB1*15:01 showed the strongest association with MS (P = 2.1 × 10⁻⁵; odds ratio [OR] = 3.44, 95% confidence interval [95% CI] = 1.95–6.07). Stepwise conditional analysis identified HLA-DRB1*04:05, HLA-B*39:01, and HLA-B*15:01 as being associated with independent MS susceptibility (P_Conditional < 8.3 × 10⁻⁴). With respect to amino acid polymorphisms in HLA genes, we found that phenylalanine at HLA-DQβ1 position 9 had the strongest effect on MS susceptibility (P = 3.7 × 10⁻⁸, OR = 3.48, 95% CI = 2.23–5.43). MS risk at HLA-DQβ1 Phe9 was independent of HLA-DRB1*15:01 (P_Conditional = 1.5 × 10⁻⁵, OR = 2.91, 95% CI = 1.79–4.72), while HLA-DRB1*15:01 was just significant when conditioned on HLA-DQβ1 Phe9 (P_Conditional = 0.037). Regarding a case-control analysis for NMOSD, HLA-DQA1*05:03 had a significant association with NMOSD (P = 1.5 × 10⁻⁴, OR = 6.96, 95% CI = 2.55–19.0).

Conclusions

We identified HLA variants associated with the risk of MS and NMOSD. Our study contributes to the understanding of the genetic architecture of MS and NMOSD in the Japanese population.

Electronic supplementary material

The online version of this article (10.1186/s12974-019-1551-z) contains supplementary material, which is available to authorized users.

Rare variant phasing using paired tumor:normal sequence data

Background

In standard high throughput sequencing analysis, genetic variants are not assigned to a homologous chromosome of origin. This process, called haplotype phasing, can reveal information important for understanding the relationship between genetic variants and biological phenotypes. For example, in genes that carry multiple heterozygous missense variants, phasing resolves whether one or both gene copies are altered. Here, we present a novel approach to phasing variants that takes advantage of unique properties of paired tumor:normal sequencing data from cancer studies.

Results

VAF phasing uses changes in variant allele frequency (VAF) between tumor and normal samples in regions of somatic chromosomal gain or loss to phase germline variants. We apply VAF phasing to 6180 samples from the Cancer Genome Atlas (TCGA) and demonstrate that our method is highly concordant with other standard phasing methods, and can phase an average of 33% more variants than other read-backed phasing methods. Using variant annotation tools designed to score gene haplotypes, we find a suggestive association between carrying multiple missense variants in a single copy of a cancer predisposition gene and earlier age of cancer diagnosis.

Conclusions

VAF phasing exploits unique properties of tumor genomes to increase the number of germline variants that can be phased over standard read-backed methods in paired tumor:normal samples. Our phase-informed association testing results call attention to the need to develop more tools for assessing the joint effect of multiple genetic variants.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2753-1) contains supplementary material, which is available to authorized users.

Evaluation of computational programs to predict HLA genotypes from genomic sequencing data

Motivation

Despite being essential for numerous clinical and research applications, high-resolution human leukocyte antigen (HLA) typing remains challenging and laboratory tests are also time-consuming and labour intensive. With next-generation sequencing data becoming widely accessible, on-demand in silico HLA typing offers an economical and efficient alternative.

Results

In this study we evaluate the HLA typing accuracy and efficiency of five computational HLA typing methods by comparing their predictions against a curated set of > 1000 published polymerase chain reaction-derived HLA genotypes on three different data sets (whole genome sequencing, whole exome sequencing and transcriptomic sequencing data). The highest accuracy at clinically relevant resolution (four digits) we observe is 81% on RNAseq data by PHLAT and 99% accuracy by OptiType when limited to Class I genes only. We also observed variability between the tools for resource consumption, with runtime ranging from an average of 5 h (HLAminer) to 7 min (seq2HLA) and memory from 12.8 GB (HLA-VBSeq) to 0.46 GB (HLAminer) per sample.

While a minimal coverage is required, other factors also determine prediction accuracy and the results between tools do not correlate well. Therefore, by combining tools, there is the potential to develop a highly accurate ensemble method that is able to deliver fast, economical HLA typing from existing sequencing data.

Genetic and phenotypic landscape of the major histocompatibilty complex region in the Japanese population

To perform detailed fine-mapping of the major-histocompatibility-complex region, we conducted next-generation sequencing (NGS)-based typing of the 33 human leukocyte antigen (HLA) genes in 1,120 individuals of Japanese ancestry, providing a high-resolution allele catalog and linkage-disequilibrium structure of both classical and nonclassical HLA genes. Together with population-specific deep-whole-genome-sequencing data (n = 1,276), we conducted NGS-based HLA, single-nucleotide-variant and indel imputation of large-scale genome-wide-association-study data from 166,190 Japanese individuals. A phenome-wide association study assessing 106 clinical phenotypes identified abundant, significant genotype-phenotype associations across 52 phenotypes. Fine-mapping highlighted multiple association patterns conferring independent risks from classical HLA genes. Region-wide heritability estimates and genetic-correlation network analysis elucidated the polygenic architecture shared across the phenotypes.

Inverse PCR to perform long-distance haplotyping: main applications to improve preimplantation genetic diagnosis in hemophilia

Among other applications of long-distance haplotype phasing in clinical genetics, determination of linked DNA markers as surrogate for problematic structural variants (e.g., repeat-mediated rearrangements) is essential to perform diagnosis from low-quality DNA samples. We describe a next-of-kin-independent (physical) phasing approach based on inverse-PCR (iPCR) paired-end amplification (PI). This method enables typing the multialleles of the short tandem repeat (STR) F8Int21[CA]n at the F8-intron 21, as a surrogate DNA marker for the F8-intron 22 inversion (Inv22), the hemophilia A-causative hotspot, within the transmitted haplotype in informative carriers. We provide proof-of-concept by blindly validating the PI approach in 15 carrier mother/affected-son duos. Every F8Int21[CA]n STR allele determined in phase with the Inv22 allele in the female carriers from the informative duos was confirmed in the hemizygous proband (P = 0.00003). A second surrogate STR locus at the F8-IVS22 was obtained by the PI approach improving severe-HA preimplantation genetic diagnosis by augmenting heterozygosity in Inv22 carriers bypassing the requirement for family linkage analysis. The ability of the PI-assay to combine other marker pairs was demonstrated by haplotyping a SNV (F8:c.6118T > C) with a >28kb-distant F8-IVS22 STR. The PI approach has proven flexibility to target different marker pairs and has potential for multiplex characterization of iPCR products by massively parallel sequencing.

ALPHLARD: a Bayesian method for analyzing HLA genes from whole genome sequence data

Background

Although human leukocyte antigen (HLA) genotyping based on amplicon, whole exome sequence (WES), and RNA sequence data has been achieved in recent years, accurate genotyping from whole genome sequence (WGS) data remains a challenge due to the low depth. Furthermore, there is no method to identify the sequences of unknown HLA types not registered in HLA databases.

Results

We developed a Bayesian model, called ALPHLARD, that collects reads potentially generated from HLA genes and accurately determines a pair of HLA types for each of HLA-A, -B, -C, -DPA1, -DPB1, -DQA1, -DQB1, and -DRB1 genes at 3rd field resolution. Furthermore, ALPHLARD can detect rare germline variants not stored in HLA databases and call somatic mutations from paired normal and tumor sequence data. We illustrate the capability of ALPHLARD using 253 WES data and 25 WGS data from Illumina platforms. By comparing the results of HLA genotyping from SBT and amplicon sequencing methods, ALPHLARD achieved 98.8% for WES data and 98.5% for WGS data at 2nd field resolution. We also detected three somatic point mutations and one case of loss of heterozygosity in the HLA genes from the WGS data.

Conclusions

ALPHLARD showed good performance for HLA genotyping even from low-coverage data. It also has a potential to detect rare germline variants and somatic mutations in HLA genes. It would help to fill in the current gaps in HLA reference databases and unveil the immunological significance of somatic mutations identified in HLA genes.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5169-9) contains supplementary material, which is available to authorized users.

Revisiting the potential power of human leukocyte antigen (HLA) genes on relationship testing by massively parallel sequencing-based HLA typing in an extended family

The human leukocyte antigen (HLA) genes are the most polymorphic genes in the human genome and have great power in forensic applications, especially in relationship testing and personal identification. However, the extreme polymorphism of HLA has made unambiguous genotyping of these genes very challenging and resulted in the limited application in relationship testing. Fortunately, massively parallel sequencing (MPS) technology offers the promise of unambiguous and high-throughput HLA typing. In this study, 11 HLA genes were typed in one extended family residing in North China and encompassing six generations. Phase-resolved genotypes for HLA genes were generated and HLA haplotype structure was defined. The paternity/kinship index, or in other words, likelihood ratio (LR) was calculated. A total of 88 alleles were identified, of which eight alleles were newly discovered. The inheritance of HLA alleles followed Mendelian law. With the discovery of new HLA alleles and three recombination events, a total of eleven new HLA haplotypes were identified in this population. LR distribution showed that, when HLA alleles were applied, the Log₁₀LR for a single locus could reach very high and the median average Log₁₀LRs of HLA genes were much higher than that of short tandem repeat loci. The result showed that high-throughput HLA genotyping could be achieved rapidly by MPS, and the contribution of HLA genes on system performance could be high, which may be applied as a supplement in forensic genetics studies. This study was also valuable in demonstrating the genetic mechanisms governing the generation of polymorphisms of the HLA genes.

Reference Grade Characterization of Polymorphisms in Full-Length HLA Class I and II Genes With Short-Read Sequencing on the ION PGM System and Long-Reads Generated by Single Molecule, Real-Time Sequencing on the PacBio Platform

Although NGS technologies fuel advances in high-throughput HLA genotyping methods for identification and classification of HLA genes to assist with precision medicine efforts in disease and transplantation, the efficiency of these methods are impeded by the absence of adequately-characterized high-frequency HLA allele reference sequence databases for the highly polymorphic HLA gene system. Here, we report on producing a comprehensive collection of full-length HLA allele sequences for eight classical HLA loci found in the Japanese population. We augmented the second-generation short read data generated by the Ion Torrent technology with long amplicon spanning consensus reads delivered by the third-generation SMRT sequencing method to create reference grade high-quality sequences of HLA class I and II gene alleles resolved at the genomic coding and non-coding level. Forty-six DNAs were obtained from a reference set used previously to establish the HLA allele frequency data in Japanese subjects. The samples included alleles with a collective allele frequency in the Japanese population of more than 99.2%. The HLA loci were independently amplified by long-range PCR using previously designed HLA-locus specific primers and subsequently sequenced using SMRT and Ion PGM sequencers. The mapped long and short-reads were used to produce a reference library of consensus HLA allelic sequences with the help of the reference-aware software tool LAA for SMRT Sequencing. A total of 253 distinct alleles were determined for 46 healthy subjects. Of them, 137 were novel alleles: 101 SNVs and/or indels and 36 extended alleles at a partial or full-length level. Comparing the HLA sequences from the perspective of nucleotide diversity revealed that HLA-DRB1 was the most divergent among the eight HLA genes, and that the HLA-DPB1 gene sequences diverged into two distinct groups, DP2 and DP5, with evidence of independent polymorphisms generated in exon 2. We also identified two specific intronic variations in HLA-DRB1 that might be involved in rheumatoid arthritis. In conclusion, full-length HLA allele sequencing by third-generation and second-generation technologies has provided polymorphic gene reference sequences at a genomic allelic resolution including allelic variations assigned up to the field-4 level for a stronger foundation in precision medicine and HLA-related disease and transplantation studies.

Full-length next-generation sequencing of HLA class I and II genes in a cohort from Thailand

The human leukocyte antigen (HLA) genes are highly variable and are known to play an important role in disease outcomes, including infectious diseases. Prior knowledge of HLA polymorphisms in a population usually forms the basis for an effective case-control study design. As a prelude to future disease association analyses, we report HLA class I and II diversity in 334 unrelated donors from a Dengue vaccine efficacy trial conducted in Thailand. Long-range PCR amplification of six HLA loci was performed on DNA extracted from saliva samples. HLA-A, -B, -C, -DPB1, -DQB1 and -DRB1 were genotyped using a next-generation sequencing method presented at the 17th International HLA and Immunogenetics Workshop. In total, we identified 201 HLA alleles, including 35 HLA-A, 57 HLA-B, 28 HLA-C, 24 HLA-DPB1, 21 HLA-DQB1 and 36 HLA-DRB1 alleles. Very common HLA alleles with frequencies greater than 10 percent were A∗11:01:01, A∗33:03:01, A∗24:02:01, B∗46:01:01, C∗07:02:01, C∗01:02:01, C∗08:01:01, DPB1∗05:01:01, DPB1∗13:01:01, DPB1∗04:01:01, DPB1∗02:01:02, DQB1∗03:01:01, DQB1∗05:02:01, DQB1∗03:03:02, DRB1∗12:02:01, DRB1∗09:01:02, and DRB1∗15:02:01. A novel HLA allele, B∗15:450, had a non-synonymous substitution and occurred in more than one donor. Population-based full-length NGS HLA typing is more conclusive and provides a sound foundation for exploring disease association in a given population.

Long reads: their purpose and place

In recent years long-read technologies have moved from being a niche and specialist field to a point of relative maturity likely to feature frequently in the genomic landscape. Analogous to next generation sequencing, the cost of sequencing using long-read technologies has materially dropped whilst the instrument throughput continues to increase. Together these changes present the prospect of sequencing large numbers of individuals with the aim of fully characterizing genomes at high resolution. In this article, we will endeavour to present an introduction to long-read technologies showing: what long reads are; how they are distinct from short reads; why long reads are useful and how they are being used. We will highlight the recent developments in this field, and the applications and potential of these technologies in medical research, and clinical diagnostics and therapeutics.

Hla-mapper: An application to optimize the mapping of HLA sequences produced by massively parallel sequencing procedures

A challenging task when more than one HLA gene is evaluated together by second-generation sequencing is to achieve a reliable read mapping. The polymorphic and repetitive nature of HLA genes might bias the read mapping process, usually underestimating variability at very polymorphic segments, or overestimating variability at some segments. To overcome this issue we developed hla-mapper, which takes into account HLA sequences derived from the IPD-IMGT/HLA database and unpublished HLA sequences to apply a scoring system. This comprehends the evaluation of each read pair, addressing them to the most likely HLA gene they were derived from. Hla-mapper provides a reliable map of HLA sequences, allowing accurate downstream analysis such as variant calling, haplotype inference, and allele typing. Moreover, hla-mapper supports whole genome, exome, and targeted sequencing data. To assess the software performance in comparison with traditional mapping algorithms, we used three different simulated datasets to compare the results obtained with hla-mapper, BWA MEM, and Bowtie2. Overall, hla-mapper presented a superior performance, mainly for the classical HLA class I genes, minimizing wrong mapping and cross-mapping that are typically observed when using BWA MEM or Bowtie2 with a single reference genome.

Accurate Typing of Human Leukocyte Antigen Class I Genes by Oxford Nanopore Sequencing

Oxford Nanopore Technologies' MinION has expanded the current DNA sequencing toolkit by delivering long read lengths and extreme portability. The MinION has the potential to enable expedited point-of-care human leukocyte antigen (HLA) typing, an assay routinely used to assess the immunologic compatibility between organ donors and recipients, but the platform's high error rate makes it challenging to type alleles with accuracy. We developed and validated accurate typing of HLA by Oxford nanopore (Athlon), a bioinformatic pipeline that i) maps nanopore reads to a database of known HLA alleles, ii) identifies candidate alleles with the highest read coverage at different resolution levels that are represented as branching nodes and leaves of a tree structure, iii) generates consensus sequences by remapping the reads to the candidate alleles, and iv) calls the final diploid genotype by blasting consensus sequences against the reference database. Using two independent data sets generated on the R9.4 flow cell chemistry, Athlon achieved a 100% accuracy in class I HLA typing at the two-field resolution.

Multiplexed Nanopore Sequencing of HLA-B Locus in Māori and Pacific Island Samples

The human leukocyte antigen (HLA) system encodes the human major histocompatibility complex (MHC). HLA-B is the most polymorphic gene in the MHC class I region and many HLA-B alleles have been associated with adverse drug reactions (ADRs) and disease susceptibility. The frequency of such HLA-B alleles varies by ethnicity, and therefore it is important to understand the prevalence of such alleles in different population groups. Research into HLA involvement in ADRs would be facilitated by improved methods for genotyping key HLA-B alleles. Here, we describe an approach to HLA-B typing using next generation sequencing (NGS) on the MinION™ nanopore sequencer, combined with data analysis with the SeqNext-HLA software package. The nanopore sequencer offers the advantages of long-read capability and single molecule reads, which can facilitate effective haplotyping. We developed this method using reference samples as well as individuals of New Zealand Māori or Pacific Island descent, because HLA-B diversity in these populations is not well understood. We demonstrate here that nanopore sequencing of barcoded, pooled, 943 bp polymerase chain reaction (PCR) amplicons of 49 DNA samples generated ample read depth for all samples. HLA-B alleles were assigned to all samples at high-resolution with very little ambiguity. Our method is a scaleable and efficient approach for genotyping HLA-B and potentially any other HLA locus. Finally, we report our findings on HLA-B genotypes of this cohort, which adds to our understanding of HLA-B allele frequencies among Māori and Pacific Island people.

Clinical pharmacogenomics testing in the era of next generation sequencing: challenges and opportunities for precision medicine

INTRODUCTION

The rapid development and dramatic decrease in cost of sequencing techniques have ushered the implementation of genomic testing in patient care. Next generation DNA sequencing (NGS) techniques have been used increasingly in clinical laboratories to scan the whole or part of the human genome in order to facilitate diagnosis and/or prognostics of genetic disease. Despite many hurdles and debates, pharmacogenomics (PGx) is believed to be an area of genomic medicine where precision medicine could have immediate impact in the near future. Areas covered: This review focuses on lessons learned through early attempts of clinically implementing PGx testing; the challenges and opportunities that PGx testing brings to precision medicine in the era of NGS. Expert commentary: Replacing targeted analysis approach with NGS for PGx testing is neither technically feasible nor necessary currently due to several technical limitations and uncertainty involved in interpreting variants of uncertain significance for PGx variants. However, reporting PGx variants out of clinical whole exome or whole genome sequencing (WES/WGS) might represent additional benefits for patients who are tested by WES/WGS.

A novel HLA-C allele, HLA-C*07:02:01:17N, with an alternative splice site

We describe the identification of alternatively expressed HLA allele C*07:02:01:17N.

Characterizing alleles with large deletions using region specific extraction

Two novel HLA class II alleles, DRB4*03:01N and DQB1*03:276N, containing large deletions were identified during routine typing. Extraction of DNA encompassing the deletions was carried out with a panel of capture oligonucleotides followed by whole genome amplification. Next generation DNA sequencing was then used to characterize the sequences. DRB4*03:01N has a 16 kilobase pair deletion stretching upstream from intron 2 toward centromeric DRB8. DQB1*03:276N has two deletions separated by 844 nucleotides. The first deletion (3.7 kilobase pairs) is upstream of intron 1 and the second deletion removes 3.3 kilobase pairs further upstream towards centromeric DQA2.

Genetic Association in the HLA Region

The MHC/HLA region has been consistently associated with a large number of complex traits, including but not limited to, most immune-mediated ones. Efforts to pinpoint drivers of this commonly encountered association peak at the short arm of chromosome 6, however, have been challenging, owing to the high density of genes and the long and extended linkage disequilibrium that are characteristic of this region.The development of methods to impute classical HLA alleles and amino acids from SNP genotyping data has offered an important additional layer of information to the investigators seeking to fine map the signal in the region. As a result, imputation-aided association analyses are now typically employed to shed light on the relationship of this locus with disease susceptibility and response to drugs.In this chapter we discuss how the signal in the HLA region can be interrogated in practice, from performing the imputation to understanding its output and to incorporating it into downstream analysis. In addition, we recount some of the analytical approaches that are commonly used and suggest ways in which the findings from such imputation-aided analyses can be interpreted.

A genomic perspective on HLA evolution

Several decades of research have convincingly shown that classical human leukocyte antigen (HLA) loci bear signatures of natural selection. Despite this conclusion, many questions remain regarding the type of selective regime acting on these loci, the time frame at which selection acts, and the functional connections between genetic variability and natural selection. In this review, we argue that genomic datasets, in particular those generated by next-generation sequencing (NGS) at the population scale, are transforming our understanding of HLA evolution. We show that genomewide data can be used to perform robust and powerful tests for selection, capable of identifying both positive and balancing selection at HLA genes. Importantly, these tests have shown that natural selection can be identified at both recent and ancient timescales. We discuss how findings from genomewide association studies impact the evolutionary study of HLA genes, and how genomic data can be used to survey adaptive change involving interaction at multiple loci. We discuss the methodological developments which are necessary to correctly interpret genomic analyses involving the HLA region. These developments include adapting the NGS analysis framework so as to deal with the highly polymorphic HLA data, as well as developing tools and theory to search for signatures of selection, quantify differentiation, and measure admixture within the HLA region. Finally, we show that high throughput analysis of molecular phenotypes for HLA genes-namely transcription levels-is now a feasible approach and can add another dimension to the study of genetic variation.

High-Throughput Contiguous Full-Length Next-Generation Sequencing of HLA Class I and II Genes from 96 Donors in a Single MiSeq Run

The human leukocyte antigen (HLA) genes regulate and drive the immune system, and are among the most polymorphic loci in the human genome. HLA diversity is known to play an important role in transplantation and disease association studies. There are multiple approaches to DNA-based HLA genotyping and recent advances in next-generation sequencing (NGS) technologies have facilitated the development of whole gene sequencing methods. We describe an accurate, efficient, scalable, and cost-effective approach to contiguously amplify and sequence full-length genes of six HLA class I and II loci from 96 individuals on a single Illumina MiSeq run.

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.