Dataset Information

Bioinformatics Strategies, Challenges, and Opportunities for Next Generation Sequencing-Based HLA Genotyping.

ABSTRACT: The advent of next generation sequencing (NGS) has altered the face of genotyping the human leukocyte antigen (HLA) system in clinical, stem cell donor registry, and research contexts. NGS has led to a dramatically increased sequencing throughput at high accuracy, while being more time and cost efficient than precursor technologies. This has led to a broader and deeper profiling of the key genes in the human immunogenetic make-up. The rapid evolution of sequencing technologies is evidenced by the development of varied short-read sequencing platforms with differing read lengths and sequencing capacities to long-read sequencing platforms capable of profiling full genes without fragmentation. Concomitantly, there has been development of a diverse set of computational analyses and software tools developed to deal with the various strengths and limitations of the sequencing data generated by the different sequencing platforms. This review surveys the different modalities involved in generating NGS HLA profiling sequence data. It systematically describes various computational approaches that have been developed to achieve HLA genotyping to different degrees of resolution. At each stage, this review enumerates the drawbacks and advantages of each of the platforms and analysis approaches, thus providing a comprehensive picture of the current state of HLA genotyping technologies.

SUBMITTER: Klasberg S

PROVIDER: S-EPMC6876610 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Bioinformatics Strategies, Challenges, and Opportunities for Next Generation Sequencing-Based HLA Genotyping.

Klasberg Steffen S Surendranath Vineeth V Lange Vinzenz V Schöfl Gerhard G

Transfusion medicine and hemotherapy : offizielles Organ der Deutschen Gesellschaft fur Transfusionsmedizin und Immunhamatologie 20190906 5

The advent of next generation sequencing (NGS) has altered the face of genotyping the human leukocyte antigen (HLA) system in clinical, stem cell donor registry, and research contexts. NGS has led to a dramatically increased sequencing throughput at high accuracy, while being more time and cost efficient than precursor technologies. This has led to a broader and deeper profiling of the key genes in the human immunogenetic make-up. The rapid evolution of sequencing technologies is evidenced by th ...[more]

PMID: 31832057

Similar Datasets

Project description: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.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.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.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.

Project description:BackgroundHIV genotyping has had a significant impact on the care and treatment of HIV/AIDS. At a clinical level, the test guides physicians on the choice of treatment regimens. At the surveillance level, it informs policy on consolidated treatment guidelines and microbial resistance control strategies. Until recently, the conventional test has utilized the Sanger sequencing (SS) method. Unlike Next Generation Sequencing (NGS), SS is limited by low data throughput and the inability of detecting low abundant drug-resistant variants. NGS can improve sensitivity and quantitatively identify low-abundance variants; in addition, it has the potential to improve efficiency as well as lowering costs when samples are batched. Despite the NGS benefits, its utilization in clinical drug resistance profiling is faced with mixed reactions. These are largely based on a lack of a consensus regarding the quality control strategy. Nonetheless, transitional views suggest validating the method against the gold-standard SS. Therefore, we present a validation report of an NGS-based in-house HIV genotyping method against the SS method in Uganda.ResultsSince there were no established proficiency test panels for NGS-based HIV genotyping, 15 clinical plasma samples for routine care were utilized. The use of clinical samples allowed for accuracy and precision studies. The workflow involved four main steps; viral RNA extraction, targeted amplicon generation, amplicon sequencing and data analysis. Accuracy of 98% with an average percentage error of 3% was reported for the NGS based assay against the SS platform demonstrating similar performance. The coefficient of variation (CV) findings for both the inter-run and inter-personnel precision showed no variability (CV ≤ 0%) at the relative abundance of ≥ 20%. For both inter-run and inter-personnel, a variation that affected the precision was observed at 1% frequency. Overall, for all the frequencies, CV registered a small range of (0-2%).ConclusionThe NGS-based in-house HIV genotyping method fulfilled the minimum requirements that support its utilization for drug resistance profiling in a clinical setting of a low-income country. For more inclusive quality control studies, well-characterized wet panels need to be established.

Dataset Information

Bioinformatics Strategies, Challenges, and Opportunities for Next Generation Sequencing-Based HLA Genotyping.

Publications

Bioinformatics Strategies, Challenges, and Opportunities for Next Generation Sequencing-Based HLA Genotyping.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets