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

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.

HLA genotyping by next-generation sequencing of complementary DNA

Background

Genotyping of the human leucocyte antigen (HLA) is indispensable for various medical treatments. However, unambiguous genotyping is technically challenging due to high polymorphism of the corresponding genomic region. Next-generation sequencing is changing the landscape of genotyping. In addition to high throughput of data, its additional advantage is that DNA templates are derived from single molecules, which is a strong merit for the phasing problem. Although most currently developed technologies use genomic DNA, use of cDNA could enable genotyping with reduced costs in data production and analysis. We thus developed an HLA genotyping system based on next-generation sequencing of cDNA.

Methods

Each HLA gene was divided into 3 or 4 target regions subjected to PCR amplification and subsequent sequencing with Ion Torrent PGM. The sequence data were then subjected to an automated analysis. The principle of the analysis was to construct candidate sequences generated from all possible combinations of variable bases and arrange them in decreasing order of the number of reads. Upon collecting candidate sequences from all target regions, 2 haplotypes were usually assigned. Cases not assigned 2 haplotypes were forwarded to 4 additional processes: selection of candidate sequences applying more stringent criteria, removal of artificial haplotypes, selection of candidate sequences with a relaxed threshold for sequence matching, and countermeasure for incomplete sequences in the HLA database.

Results

The genotyping system was evaluated using 30 samples; the overall accuracy was 97.0% at the field 3 level and 98.3% at the G group level. With one sample, genotyping of DPB1 was not completed due to short read size. We then developed a method for complete sequencing of individual molecules of the DPB1 gene, using the molecular barcode technology.

Conclusion

The performance of the automatic genotyping system was comparable to that of systems developed in previous studies. Thus, next-generation sequencing of cDNA is a viable option for HLA genotyping.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4300-7) contains supplementary material, which is available to authorized users.

Sequence-Based Genotyping of Expressed Swine Leukocyte Antigen Class I Alleles by Next-Generation Sequencing Reveal Novel Swine Leukocyte Antigen Class I Haplotypes and Alleles in Belgian, Danish, and Kenyan Fattening Pigs and Göttingen Minipigs

The need for typing of the swine leukocyte antigen (SLA) is increasing with the expanded use of pigs as models for human diseases and organ-transplantation experiments, their use in infection studies, and for design of veterinary vaccines. Knowledge of SLA sequences is furthermore a prerequisite for the prediction of epitope binding in pigs. The low number of known SLA class I alleles and the limited knowledge of their prevalence in different pig breeds emphasizes the need for efficient SLA typing methods. This study utilizes an SLA class I-typing method based on next-generation sequencing of barcoded PCR amplicons. The amplicons were generated with universal primers and predicted to resolve 68-88% of all known SLA class I alleles dependent on amplicon size. We analyzed the SLA profiles of 72 pigs from four different pig populations; Göttingen minipigs and Belgian, Kenyan, and Danish fattening pigs. We identified 67 alleles, nine previously described haplotypes and 15 novel haplotypes. The highest variation in SLA class I profiles was observed in the Danish pigs and the lowest among the Göttingen minipig population, which also have the highest percentage of homozygote individuals. Highlighting the fact that there are still numerous unknown SLA class I alleles to be discovered, a total of 12 novel SLA class I alleles were identified. Overall, we present new information about known and novel alleles and haplotypes and their prevalence in the tested pig populations.

HLA-HD: An accurate HLA typing algorithm for next-generation sequencing data

The accurate typing of human leukocyte antigen (HLA) alleles is critical for a variety of medical applications, such as genomic studies of multifactorial diseases, including immune system and inflammation-related disorders, and donor selection in organ transplantation and regenerative medicine. Here, we developed a new algorithm for determining HLA alleles using next-generation sequencing (NGS) results. The method consists of constructing an extensive dictionary of HLA alleles, precise mapping of the NGS reads, and calculating a score based on weighted read counts to select the most suitable pair of alleles. The developed algorithm compares the score of all allele pairs, taking into account variation not only in the domain for antigen presentation (G-DOMAIN), but also outside this domain. Using this method, HLA alleles could be determined with 6-digit precision. We showed that our method was more accurate than other NGS-based methods and revealed limitations of the conventional HLA typing technologies. Furthermore, we determined the complete genomic sequence of an HLA-A-like-pseudogene when we assembled NGS reads that had caused arguable typing, and found its identity with HLA-Y*02:01. The accuracy of the HLA-A allele typing was improved after the HLA-Y*02:01 sequence was included in the HLA allele dictionary.

Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study

An increasing number of genome-wide association (GWA) studies are now using the higher resolution 1000 Genomes Project reference panel (1000G) for imputation, with the expectation that 1000G imputation will lead to the discovery of additional associated loci when compared to HapMap imputation. In order to assess the improvement of 1000G over HapMap imputation in identifying associated loci, we compared the results of GWA studies of circulating fibrinogen based on the two reference panels. Using both HapMap and 1000G imputation we performed a meta-analysis of 22 studies comprising the same 91,953 individuals. We identified six additional signals using 1000G imputation, while 29 loci were associated using both HapMap and 1000G imputation. One locus identified using HapMap imputation was not significant using 1000G imputation. The genome-wide significance threshold of 5×10-8 is based on the number of independent statistical tests using HapMap imputation, and 1000G imputation may lead to further independent tests that should be corrected for. When using a stricter Bonferroni correction for the 1000G GWA study (P-value < 2.5×10-8), the number of loci significant only using HapMap imputation increased to 4 while the number of loci significant only using 1000G decreased to 5. In conclusion, 1000G imputation enabled the identification of 20% more loci than HapMap imputation, although the advantage of 1000G imputation became less clear when a stricter Bonferroni correction was used. More generally, our results provide insights that are applicable to the implementation of other dense reference panels that are under development.

Combining one-step Sanger sequencing with phasing probe hybridization for HLA class I typing yields rapid, G-group resolution predicting 99% of unique full length protein sequences

BACKGROUND

Sanger-based DNA sequencing of exons 2+3 of HLA class I alleles from a heterozygote frequently results in two or more alternative genotypes. This study was undertaken to reduce the time and effort required to produce a single high resolution HLA genotype.

MATERIALS AND METHODS

Samples were typed in parallel by Sanger sequencing and oligonucleotide probe hybridization. This workflow, together with optimization of analysis software, was tested and refined during the typing of over 42,000 volunteers for an unrelated hematopoietic progenitor cell donor registry. Next generation DNA sequencing (NGS) was applied to over 1000 of these samples to identify the alleles present within the G group designations.

RESULTS

Single genotypes at G level resolution were obtained for over 95% of the loci without additional assays. The vast majority of alleles identified (>99%) were the primary allele giving the G groups their name. Only 0.7% of the alleles identified encoded protein variants that were not detected by a focus on the antigen recognition domain (ARD)-encoding exons.

CONCLUSION

Our combined method routinely provides biologically relevant typing resolution at the level of the ARD. It can be applied to both single samples or to large volume typing supporting either bone marrow or solid organ transplantation using technologies currently available in many HLA laboratories.

Application of High-Throughput Next-Generation Sequencing for HLA Typing on Buccal Extracted DNA: Results from over 10,000 Donor Recruitment Samples

Background

Unambiguous HLA typing is important in hematopoietic stem cell transplantation (HSCT), HLA disease association studies, and solid organ transplantation. However, current molecular typing methods only interrogate the antigen recognition site (ARS) of HLA genes, resulting in many cis-trans ambiguities that require additional typing methods to resolve. Here we report high-resolution HLA typing of 10,063 National Marrow Donor Program (NMDP) registry donors using long-range PCR by next generation sequencing (NGS) approach on buccal swab DNA.

Methods

Multiplex long-range PCR primers amplified the full-length of HLA class I genes (A, B, C) from promotor to 3’ UTR. Class II genes (DRB1, DQB1) were amplified from exon 2 through part of exon 4. PCR amplicons were pooled and sheared using Covaris fragmentation. Library preparation was performed using the Illumina TruSeq Nano kit on the Beckman FX automated platform. Each sample was tagged with a unique barcode, followed by 2×250 bp paired-end sequencing on the Illumina MiSeq. HLA typing was assigned using Omixon Twin software that combines two independent computational algorithms to ensure high confidence in allele calling. Consensus sequence and typing results were reported in Histoimmunogenetics Markup Language (HML) format. All homozygous alleles were confirmed by Luminex SSO typing and exon novelties were confirmed by Sanger sequencing.

Results

Using this automated workflow, over 10,063 NMDP registry donors were successfully typed under high-resolution by NGS. Despite known challenges of nucleic acid degradation and low DNA concentration commonly associated with buccal-based specimens, 97.8% of samples were successfully amplified using long-range PCR. Among these, 98.2% were successfully reported by NGS, with an accuracy rate of 99.84% in an independent blind Quality Control audit performed by the NDMP. In this study, NGS-HLA typing identified 23 null alleles (0.023%), 92 rare alleles (0.091%) and 42 exon novelties (0.042%).

Conclusion

Long-range, unambiguous HLA genotyping is achievable on clinical buccal swab-extracted DNA. Importantly, full-length gene sequencing and the ability to curate full sequence data will permit future interrogation of the impact of introns, expanded exons, and other gene regulatory sequences on clinical outcomes in transplantation.

Impact of post-alignment processing in variant discovery from whole exome data

Background

GATK Best Practices workflows are widely used in large-scale sequencing projects and recommend post-alignment processing before variant calling. Two key post-processing steps include the computationally intensive local realignment around known INDELs and base quality score recalibration (BQSR). Both have been shown to reduce erroneous calls; however, the findings are mainly supported by the analytical pipeline that incorporates BWA and GATK UnifiedGenotyper. It is not known whether there is any benefit of post-processing and to what extent the benefit might be for pipelines implementing other methods, especially given that both mappers and callers are typically updated. Moreover, because sequencing platforms are upgraded regularly and the new platforms provide better estimations of read quality scores, the need for post-processing is also unknown. Finally, some regions in the human genome show high sequence divergence from the reference genome; it is unclear whether there is benefit from post-processing in these regions.

Results

We used both simulated and NA12878 exome data to comprehensively assess the impact of post-processing for five or six popular mappers together with five callers. Focusing on chromosome 6p21.3, which is a region of high sequence divergence harboring the human leukocyte antigen (HLA) system, we found that local realignment had little or no impact on SNP calling, but increased sensitivity was observed in INDEL calling for the Stampy + GATK UnifiedGenotyper pipeline. No or only a modest effect of local realignment was detected on the three haplotype-based callers and no evidence of effect on Novoalign. BQSR had virtually negligible effect on INDEL calling and generally reduced sensitivity for SNP calling that depended on caller, coverage and level of divergence. Specifically, for SAMtools and FreeBayes calling in the regions with low divergence, BQSR reduced the SNP calling sensitivity but improved the precision when the coverage is insufficient. However, in regions of high divergence (e.g., the HLA region), BQSR reduced the sensitivity of both callers with little gain in precision rate. For the other three callers, BQSR reduced the sensitivity without increasing the precision rate regardless of coverage and divergence level.

Conclusions

We demonstrated that the gain from post-processing is not universal; rather, it depends on mapper and caller combination, and the benefit is influenced further by sequencing depth and divergence level. Our analysis highlights the importance of considering these key factors in deciding to apply the computationally intensive post-processing to Illumina exome data.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1279-z) contains supplementary material, which is available to authorized users.

An analytical workflow for accurate variant discovery in highly divergent regions

Background

Current variant discovery methods often start with the mapping of short reads to a reference genome; yet, their performance deteriorates in genomic regions where the reads are highly divergent from the reference sequence. This is particularly problematic for the human leukocyte antigen (HLA) region on chromosome 6p21.3. This region is associated with over 100 diseases, but variant calling is hindered by the extreme divergence across different haplotypes.

Results

We simulated reads from chromosome 6 exonic regions over a wide range of sequence divergence and coverage depth. We systematically assessed combinations between five mappers and five callers for their performance on simulated data and exome-seq data from NA12878, a well-studied individual in which multiple public call sets have been generated. Among those combinations, the number of known SNPs differed by about 5 % in the non-HLA regions of chromosome 6 but over 20 % in the HLA region. Notably, GSNAP mapping combined with GATK UnifiedGenotyper calling identified about 20 % more known SNPs than most existing methods without a noticeable loss of specificity, with 100 % sensitivity in three highly polymorphic HLA genes examined. Much larger differences were observed among these combinations in INDEL calling from both non-HLA and HLA regions. We obtained similar results with our internal exome-seq data from a cohort of chronic lymphocytic leukemia patients.

Conclusions

We have established a workflow enabling variant detection, with high sensitivity and specificity, over the full spectrum of divergence seen in the human genome. Comparing to public call sets from NA12878 has highlighted the overall superiority of GATK UnifiedGenotyper, followed by GATK HaplotypeCaller and SAMtools, in SNP calling, and of GATK HaplotypeCaller and Platypus in INDEL calling, particularly in regions of high sequence divergence such as the HLA region. GSNAP and Novoalign are the ideal mappers in combination with the above callers. We expect that the proposed workflow should be applicable to variant discovery in other highly divergent regions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3045-z) contains supplementary material, which is available to authorized users.

Determining performance characteristics of an NGS-based HLA typing method for clinical applications

This study presents performance specifications of an in-house developed human leukocyte antigen (HLA) typing assay using next-generation sequencing (NGS) on the Illumina MiSeq platform. A total of 253 samples, previously characterized for HLA-A, -B, -C, -DRB1 and -DQB1 were included in this study, which were typed at high-resolution using a combination of Sanger sequencing, sequence-specific primer (SSP) and sequence-specific oligonucleotide probe (SSOP) technologies and recorded at the two-field level. Samples were selected with alleles that cover a high percentage of HLA specificities in each of five different race/ethnic groups: European, African-American, Asian Pacific Islander, Hispanic and Native American. Sequencing data were analyzed by two software programs, Omixon's target and GenDx's NGSengine. A number of metrics including allele balance, sensitivity, specificity, precision, accuracy and remaining ambiguity were assessed. Data analyzed by the two software systems are shown independently. The majority of alleles were identical in the exonic sequences (third field) with both programs for HLA-A, -B, -C and -DQB1 in 97.7% of allele determinations. Among the remaining discrepant genotype calls at least one of the analysis programs agreed with the reference typing. Upon additional manual analysis 100% of the 2530 alleles were concordant with the reference HLA genotypes; the remaining ambiguities did not exceed 0.8%. The results demonstrate the feasibility and significant benefit of HLA typing by NGS as this technology is highly accurate, eliminates virtually all ambiguities, provides complete sequencing information for the length of the HLA gene and forms the basis for utilizing a single methodology for HLA typing in the immunogenetics labs.

Complete haplotype phasing of the MHC and KIR loci with targeted HaploSeq

BACKGROUND

The MHC and KIR loci are clinically relevant regions of the genome. Typing the sequence of these loci has a wide range of applications including organ transplantation, drug discovery, pharmacogenomics and furthering fundamental research in immune genetics. Rapid advances in biochemical and next-generation sequencing (NGS) technologies have enabled several strategies for precise genotyping and phasing of candidate HLA alleles. Nonetheless, as typing of candidate HLA alleles alone reveals limited aspects of the genetics of MHC region, it is insufficient for the comprehensive utility of the aforementioned applications. For this reason, we believe phasing the entire MHC and KIR locus onto a single locus-spanning haplotype can be a critical improvement for better understanding transplantation biology.

RESULTS

Generating long-range (>1 Mb) phase information is traditionally very challenging. As proximity-ligation based methods of DNA sequencing preserves chromosome-span phase information, we have utilized this principle to demonstrate its utility towards generating full-length phasing of MHC and KIR loci in human samples. We accurately (~99%) reconstruct the complete haplotypes for over 90% of sequence variants (coding and non-coding) within these two loci that collectively span 4-megabases.

CONCLUSIONS

By haplotyping a majority of coding and non-coding alleles at the MHC and KIR loci in a single assay, this method has the potential to assist transplantation matching and facilitate investigation of the genetic basis of human immunity and disease.

References for Haplotype Imputation in the Big Data Era

Imputation is a powerful in silico approach to fill in those missing values in the big datasets. This process requires a reference panel, which is a collection of big data from which the missing information can be extracted and imputed. Haplotype imputation requires ethnicity-matched references; a mismatched reference panel will significantly reduce the quality of imputation. However, currently existing big datasets cover only a small number of ethnicities, there is a lack of ethnicity-matched references for many ethnic populations in the world, which has hampered the data imputation of haplotypes and its downstream applications. To solve this issue, several approaches have been proposed and explored, including the mixed reference panel, the internal reference panel and genotype-converted reference panel. This review article provides the information and comparison between these approaches. Increasing evidence showed that not just one or two genetic elements dictate the gene activity and functions; instead, cis-interactions of multiple elements dictate gene activity. Cis-interactions require the interacting elements to be on the same chromosome molecule, therefore, haplotype analysis is essential for the investigation of cis-interactions among multiple genetic variants at different loci, and appears to be especially important for studying the common diseases. It will be valuable in a wide spectrum of applications from academic research, to clinical diagnosis, prevention, treatment, and pharmaceutical industry.

HLA-genotyping of clinical specimens using Ion Torrent-based NGS

We have evaluated and validated the NXType™ workflow (One Lambda, Inc.) and the accompanying TypeStream™ software on the Ion Torrent Next Generation Sequencing (NGS) platform using a comprehensive testing panel. The panel consisted of 285 genomic DNA (gDNA) samples derived from four major ethnic populations and contained 59 PT samples and 226 clinical specimens. The total number of alleles from the six loci interrogated by NGS was 3420. This validation panel provided a wide range of HLA sequence variations including many rare alleles, new variants and homozygous alleles. The NXType™ system (reagents and software) was able to correctly genotype the vast majority of these specimens. The concordance rate between SBT-derived genotypes and those generated by TypeStream™ auto-analysis ranged from 99.5% to 99.8% for the HLA-A, B, C, DRB1 and DQB1 loci, and was 98.9% for HLA-DPB1. A strategy for data review was developed that would allow correction of most of the few remaining typing errors. The entire NGS workflow from gDNA amplification to genotype assignment could be completed within 3 working days. Through this validation study, the limitations and shortcomings of the platform, specific assay system, and software algorithm were also revealed for further evaluation and improvement.

The impact of next-generation sequencing technologies on HLA research

In the past decade, the development of next-generation sequencing (NGS) has paved the way for whole-genome analysis in individuals. Research on the human leukocyte antigen (HLA), an extensively studied molecule involved in immunity, has benefitted from NGS technologies. The HLA region, a 3.6-Mb segment of the human genome at 6p21, has been associated with more than 100 different diseases, primarily autoimmune diseases. Recently, the HLA region has received much attention because severe adverse effects of various drugs are associated with particular HLA alleles. Owing to the complex nature of the HLA genes, classical direct sequencing methods cannot comprehensively elucidate the genomic makeup of HLA genes. Thus far, several high-throughput HLA-typing methods using NGS have been developed. In HLA research, NGS facilitates complete HLA sequencing and is expected to improve our understanding of the mechanisms through which HLA genes are modulated, including transcription, regulation of gene expression and epigenetics. Most importantly, NGS may also permit the analysis of HLA-omics. In this review, we summarize the impact of NGS on HLA research, with a focus on the potential for clinical applications.

Distribution of HLA haplotypes across Japanese Archipelago: similarity, difference and admixture

The human leukocyte antigen (HLA) region is the most polymorphic region in the human genome. The polymorphic nature of the HLA region is thought to have been shaped from balancing selection. The complex migration events during the Out-of-Africa expansion have influenced geographic patterns of HLA allele frequencies and diversities across present-day human populations. Differences in the HLA allele frequency may contribute geographic differences in the susceptibility to many diseases, such as infectious, autoimmune and metabolic diseases. Here we briefly reviewed characteristics of frequency distribution of HLA alleles and haplotypes in Japanese population. A large part of HLA alleles and haplotypes that are common in Japanese are shared with neighboring Asian populations. The differentiations in HLA alleles and haplotypes across Japanese regional populations may provide clues to model for peopling of Japanese Archipelago and for design of genetic association studies. Finally, we introduce recent topics that new HLA alleles derived from ancient admixtures with Neanderthals and Denisovans are thought to have played an important role in the adaptation of modern humans to local pathogens during Out-of-Africa expansion.

Very long haplotype tracts characterized at high resolution from HLA homozygous cell lines

The HLA region of chromosome 6 contains the most polymorphic genes in humans. Spanning ~5 Mbp the densely packed region encompasses approximately 175 expressed genes including the highly polymorphic HLA class I and II loci. Most of the other genes and functional elements are also polymorphic, and many of them are directly implicated in immune function or immune-related disease. For these reasons, this complex genomic region is subject to intense scrutiny by researchers with the common goal of aiding further understanding and diagnoses of multiple immune-related diseases and syndromes. To aid assay development and characterization of the classical loci, a panel of cell lines partially or fully homozygous for HLA class I and II was assembled over time by the International Histocompatibility Working Group (IHWG). Containing a minimum of 88 unique HLA haplotypes, we show that this panel represents a significant proportion of European HLA allelic and haplotype diversity (60-95 %). Using a high-density whole genome array that includes 13,331 HLA region SNPs, we analyzed 99 IHWG cells to map the coordinates of the homozygous tracts at a fine scale. The mean homozygous tract length within chromosome 6 from these individuals is 21 Mbp. Within HLA, the mean haplotype length is 4.3 Mbp, and 65 % of the cell lines were shown to be homozygous throughout the entire region. In addition, four cell lines are homozygous throughout the complex KIR region of chromosome 19 (~250 kbp). The data we describe will provide a valuable resource for characterizing haplotypes, designing and refining imputation algorithms and developing assay controls.

Towards allele-level human leucocyte antigens genotyping - assessing two next-generation sequencing platforms: Ion Torrent Personal Genome Machine and Illumina MiSeq

Human leucocyte antigens (HLA) typing has been a challenge due to extreme polymorphism of the HLA genes and limitations of the current technologies and protocols used for their characterization. Recently, next-generation sequencing techniques have been shown to be a well-suited technology for the complete characterization of the HLA genes. However, a comprehensive assessment of the different platforms for HLA typing, describing the limitations and advantages of each of them, has not been presented. We have compared the Ion Torrent Personal Genome Machine (PGM) and Illumina MiSeq, currently the two most frequently used platforms for diagnostic applications, for a number of metrics including total output, quality score per position across the reads and error rates after alignment which can all affect the accuracy of HLA genotyping. For this purpose, we have used one homozygous and three heterozygous well-characterized samples, at HLA-A, HLA-B, HLA-C, HLA-DRB1 and HLA-DQB1. The total output of bases produced by the MiSeq was higher, and they have higher quality scores and a lower overall error rate than the PGM. The MiSeq also has a higher fidelity when sequencing through homopolymer regions up to 9 bp in length. The need to set phase between distant polymorphic sites was more readily achieved with MiSeq using paired-end sequencing of fragments that are longer than those obtained with PGM. Additionally, we have assessed the workflows of the different platforms for complexity of sample preparation, sequencer operation and turnaround time. The effects of data quality and quantity can impact the genotyping results; having an adequate amount of good quality data to analyse will be imperative for confident HLA genotyping. The overall turnaround time can be very comparable between the two platforms; however, the complexity of sample preparation is higher with PGM, while the actual sequencing time is longer with MiSeq.

An integrated genotyping approach for HLA and other complex genetic systems

Clinical immunogenetics laboratories performing routine sequencing of human leukocyte antigen (HLA) genes in support of hematopoietic cell transplantation are motivated to upgrade to next-generation sequencing (NGS) technology by its potential for cost savings as well as testing accuracy and flexibility. While NGS machines are available and simple to operate, there are few systems available that provide comprehensive sample preparation and data analysis workflows to complete the process. We report on the development and testing of the Integrated Genotyping System (IGS), which has been designed to specifically address the challenges associated with the adoption of NGS in clinical laboratories. To validate the system for a variety of sample DNA sources, we have tested 336 DNA specimens from whole blood, dried blood spots, buccal swabs, and lymphoblastoid cell lines. HLA class I and class II genotypes were derived from amplicon sequencing of HLA-A, -B, -C for exons 1-7 and HLA-DPA1, -DPB1, -DQA1, -DQB1, -DRB1, -DRB3, -DRB4, -DRB5 for exons 1-4. Additionally, to demonstrate the extensibility of the IGS to other genetic loci, KIR haplotyping of 93 samples was carried out in parallel with HLA typing using a workflow based on the HLA system. These results are discussed with respect to their applications in the clinical setting and consequent potential for advancing precision medicine.

HLA Typing for the Next Generation

Allele-level resolution data at primary HLA typing is the ideal for most histocompatibility testing laboratories. Many high-throughput molecular HLA typing approaches are unable to determine the phase of observed DNA sequence polymorphisms, leading to ambiguous results. The use of higher resolution methods is often restricted due to cost and time limitations. Here we report on the feasibility of using Pacific Biosciences’ Single Molecule Real-Time (SMRT) DNA sequencing technology for high-resolution and high-throughput HLA typing. Seven DNA samples were typed for HLA-A, -B and -C. The results showed that SMRT DNA sequencing technology was able to generate sequences that spanned entire HLA Class I genes that allowed for accurate allele calling. Eight novel genomic HLA class I sequences were identified, four were novel alleles, three were confirmed as genomic sequence extensions and one corrected an existing genomic reference sequence. This method has the potential to revolutionize the field of HLA typing. The clinical impact of achieving this level of resolution HLA typing data is likely to considerable, particularly in applications such as organ and blood stem cell transplantation where matching donors and recipients for their HLA is of utmost importance.

Cost-efficient multiplex PCR for routine genotyping of up to nine classical HLA loci in a single analytical run of multiple samples by next generation sequencing

Background

HLA genotyping by next generation sequencing (NGS) requires three basic steps, PCR, NGS, and allele assignment. Compared to the conventional methods, such as PCR-sequence specific oligonucleotide primers (SSOP) and -sequence based typing (SBT), PCR-NGS is extremely labor intensive and time consuming. In order to simplify and accelerate the NGS-based HLA genotyping method for multiple DNA samples, we developed and evaluated four multiplex PCR methods for genotyping up to nine classical HLA loci including HLA-A, HLA-B, HLA-C, HLA-DRB1/3/4/5, HLA-DQB1, and HLA-DPB1.

Results

We developed multiplex PCR methods using newly and previously designed middle ranged PCR primer sets for genotyping different combinations of HLA loci, (1) HLA-DRB1/3/4/5, (2) HLA-DQB1 (3.8 kb to 5.3 kb), (3) HLA-A, HLA-B, HLA-C, and (4) HLA-DPB1 (4.6 kb to 7.2 kb). The primer sets were designed to genotype polymorphic exons to the field 3 level or 6-digit typing. When we evaluated the PCR method for genotyping all nine HLA loci (9LOCI) using 46 Japanese reference subjects who represented a distribution of more than 99.5% of the HLA alleles at each of the nine HLA loci, all of the 276 alleles genotyped, except for HLA-DRB3/4/5 alleles, were consistent with known alleles assigned by the conventional methods together with relevant locus balance and no excessive allelic imbalance. One multiplex PCR method (9LOCI) was able to provide precise genotyping data even when only 1 ng of genomic DNA was used for the PCR as a sample template.

Conclusions

In this study, we have demonstrated that the multiplex PCR approach for NGS-based HLA genotyping could serve as an alternative routine HLA genotyping method, possibly replacing the conventional methods by providing an accelerated yet robust amplification step. The method also could provide significant merits for clinical applications with its ability to amplify lower quantity of samples and the cost-saving factors.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1514-4) contains supplementary material, which is available to authorized users.

Development of a high-resolution NGS-based HLA-typing and analysis pipeline

The human leukocyte antigen (HLA) complex contains the most polymorphic genes in the human genome. The classical HLA class I and II genes define the specificity of adaptive immune responses. Genetic variation at the HLA genes is associated with susceptibility to autoimmune and infectious diseases and plays a major role in transplantation medicine and immunology. Currently, the HLA genes are characterized using Sanger- or next-generation sequencing (NGS) of a limited amplicon repertoire or labeled oligonucleotides for allele-specific sequences. High-quality NGS-based methods are in proprietary use and not publicly available. Here, we introduce the first highly automated open-kit/open-source HLA-typing method for NGS. The method employs in-solution targeted capturing of the classical class I (HLA-A, HLA-B, HLA-C) and class II HLA genes (HLA-DRB1, HLA-DQA1, HLA-DQB1, HLA-DPA1, HLA-DPB1). The calling algorithm allows for highly confident allele-calling to three-field resolution (cDNA nucleotide variants). The method was validated on 357 commercially available DNA samples with known HLA alleles obtained by classical typing. Our results showed on average an accurate allele call rate of 0.99 in a fully automated manner, identifying also errors in the reference data. Finally, our method provides the flexibility to add further enrichment target regions.

HLA class II diversity in HIV-1 uninfected individuals from the placebo arm of the RV144 Thai vaccine efficacy trial

The RV144 HIV vaccine trial in Thailand elicited antibody responses to the envelope of HIV-1, which correlated significantly with the risk of HIV-1 acquisition. Human leukocyte antigen (HLA) class II molecules are essential in antigen presentation to CD4 T cells for activation of B cells to produce antibodies. We genotyped the classical HLA-DRB1, DQB1, and DPB1 genes in 450 individuals from the placebo arm of the RV144 study to determine the background allele and haplotype frequencies of these genes in this cohort. High-resolution 4 and 6-digit class II HLA typing data was generated using sequencing-based methods. The observed diversity for the HLA loci was 33 HLA-DRB1, 15 HLA-DQB1, and 26 HLA-DPB1 alleles. Common alleles with frequencies greater than 10% were DRB1*07:01, DRB1*09:01, DRB1*12:02, DRB1*15:02, DQB1*02:01/02, DQB1*03:01, DQB1*03:03, DQB1*05:01, DQB1*05:02, DPB1*04:01:01, DPB1*05:01:01, and DPB1*13:01:01. We identified 28 rare alleles with frequencies of less than 1% in the Thai individuals. Ambiguity for HLA-DPB1*28:01 in exon 2 was resolved to DPB1*296:01 by next-generation sequencing of all exons. Multi-locus haplotypes including HLA class I and II loci were reported in this study. This is the first comprehensive report of allele and haplotype frequencies of all three HLA class II genes from a Thai population. A high-resolution genotyping method such as next-generation sequencing avoids missing rare alleles and resolves ambiguous calls. The HLA class II genotyping data generated in this study will be beneficial not only for future disease association/vaccine efficacy studies related to the RV144 study, but also for similar studies in other diseases in the Thai population, as well as population genetics and transplantation studies.

HLA-VBSeq: accurate HLA typing at full resolution from whole-genome sequencing data

Background

Human leucocyte antigen (HLA) genes play an important role in determining the outcome of organ transplantation and are linked to many human diseases. Because of the diversity and polymorphisms of HLA loci, HLA typing at high resolution is challenging even with whole-genome sequencing data.

Results

We have developed a computational tool, HLA-VBSeq, to estimate the most probable HLA alleles at full (8-digit) resolution from whole-genome sequence data. HLA-VBSeq simultaneously optimizes read alignments to HLA allele sequences and abundance of reads on HLA alleles by variational Bayesian inference. We show the effectiveness of the proposed method over other methods through the analysis of predicting HLA types for HLA class I (HLA-A, -B and -C) and class II (HLA-DQA1,-DQB1 and -DRB1) loci from the simulation data of various depth of coverage, and real sequencing data of human trio samples.

Conclusions

HLA-VBSeq is an efficient and accurate HLA typing method using high-throughput sequencing data without the need of primer design for HLA loci. Moreover, it does not assume any prior knowledge about HLA allele frequencies, and hence HLA-VBSeq is broadly applicable to human samples obtained from a genetically diverse population.

Novel Approaches and Technologies in Molecular HLA Typing

The invention of the Polymerase Chain Reaction (PCR) has revolutionized molecular biology enabling gene isolation and characterization in hours rather than days. Scientists working in transplant diagnostics have proven to be pioneers in adapting this molecular technique to the clinical needs of histocompatibility testing. This chapter describes a number of novel genotyping technologies which have been used to address the challenges posed by genetic diversity seen in the extensive polymorphism in HLA genes. These novel approaches include single-stranded and duplex conformational analyses, real-time PCR, microarray hybridization, RNA-based sequencing, and the present day Next Generation Sequencing. The chapter concludes with a brief look at a possible next, Next Generation Sequencing system.

Haplotype-resolved whole-genome sequencing by contiguity-preserving transposition and combinatorial indexing

Haplotype-resolved genome sequencing enables the accurate interpretation of medically relevant genetic variation, deep inferences regarding population history and non-invasive prediction of fetal genomes. We describe an approach for genome-wide haplotyping based on contiguity-preserving transposition (CPT-seq) and combinatorial indexing. Tn5 transposition is used to modify DNA with adaptor and index sequences while preserving contiguity. After DNA dilution and compartmentalization, the transposase is removed, resolving the DNA into individually indexed libraries. The libraries in each compartment, enriched for neighboring genomic elements, are further indexed via PCR. Combinatorial 96-plex indexing at both the transposition and PCR stage enables the construction of phased synthetic reads from each of the nearly 10,000 'virtual compartments'. We demonstrate the feasibility of this method by assembling >95% of the heterozygous variants in a human genome into long, accurate haplotype blocks (N50 = 1.4-2.3 Mb). The rapid, scalable and cost-effective workflow could enable haplotype resolution to become routine in human genome sequencing.

High-throughput multiplex HLA genotyping by next-generation sequencing using multi-locus individual tagging

BACKGROUND

Unambiguous human leukocyte antigen (HLA) typing is important in transplant matching and disease association studies. High-resolution HLA typing that is not restricted to the peptide-binding region can decrease HLA allele ambiguities. Cost and technology constraints have hampered high-throughput and efficient high resolution unambiguous HLA typing. We have developed a method for HLA genotyping that preserves the very high-resolution that can be obtained by next-generation sequencing (NGS) but also achieves substantially increased efficiency. Unambiguous HLA-A, B, C and DRB1 genotypes can be determined for 96 individuals in a single run of the Illumina MiSeq.

RESULTS

Long-range amplification of full-length HLA genes from four loci was performed in separate polymerase chain reactions (PCR) using primers and PCR conditions that were optimized to reduce co-amplification of other HLA loci. Amplicons from the four HLA loci of each individual were then pooled and subjected to enzymatic library generation. All four loci of an individual were then tagged with one unique index combination. This multi-locus individual tagging (MIT) method combined with NGS enabled the four loci of 96 individuals to be analyzed in a single 500 cycle sequencing paired-end run of the Illumina-MiSeq. The MIT-NGS method generated sequence reads from the four loci were then discriminated using commercially available NGS HLA typing software. Comparison of the MIT-NGS with Sanger sequence-based HLA typing methods showed that all the ambiguities and discordances between the two methods were due to the accuracy of the MIT-NGS method.

CONCLUSIONS

The MIT-NGS method enabled accurate, robust and cost effective simultaneous analyses of four HLA loci per sample and produced 6 or 8-digit high-resolution unambiguous phased HLA typing data from 96 individuals in a single NGS run.

A Bead-based Normalization for Uniform Sequencing depth (BeNUS) protocol for multi-samples sequencing exemplified by HLA-B

BACKGROUND

Human leukocyte antigen (HLA) is a group of genes that are extremely polymorphic among individuals and populations and have been associated with more than 100 different diseases and adverse drug effects. HLA typing is accordingly an important tool in clinical application, medical research, and population genetics. We have previously developed a phase-defined HLA gene sequencing method using MiSeq sequencing.

RESULTS

Here we report a simple, high-throughput, and cost-effective sequencing method that includes normalized library preparation and adjustment of DNA molar concentration. We applied long-range PCR to amplify HLA-B for 96 samples followed by transposase-based library construction and multiplex sequencing with the MiSeq sequencer. After sequencing, we observed low variation in read percentages (0.2% to 1.55%) among the 96 demultiplexed samples. On this basis, all the samples were amenable to haplotype phasing using our phase-defined sequencing method. In our study, a sequencing depth of 800x was necessary and sufficient to achieve full phasing of HLA-B alleles with reliable assignment of the allelic sequence to the 8 digit level.

CONCLUSIONS

Our HLA sequencing method optimized for 96 multiplexing samples is highly time effective and cost effective and is especially suitable for automated multi-sample library preparation and sequencing.

DDBJ progress report: a new submission system for leading to a correct annotation

The DNA Data Bank of Japan (DDBJ; http://www.ddbj.nig.ac.jp) maintains and provides archival, retrieval and analytical resources for biological information. This database content is shared with the US National Center for Biotechnology Information (NCBI) and the European Bioinformatics Institute (EBI) within the framework of the International Nucleotide Sequence Database Collaboration (INSDC). DDBJ launched a new nucleotide sequence submission system for receiving traditional nucleotide sequence. We expect that the new submission system will be useful for many submitters to input accurate annotation and reduce the time needed for data input. In addition, DDBJ has started a new service, the Japanese Genotype–phenotype Archive (JGA), with our partner institute, the National Bioscience Database Center (NBDC). JGA permanently archives and shares all types of individual human genetic and phenotypic data. We also introduce improvements in the DDBJ services and databases made during the past year.