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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...

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Autores principales: Segawa, Hidenobu, Kukita, Yoji, Kato, Kikuya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5704545/
https://www.ncbi.nlm.nih.gov/pubmed/29179676
http://dx.doi.org/10.1186/s12864-017-4300-7
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author Segawa, Hidenobu
Kukita, Yoji
Kato, Kikuya
author_facet Segawa, Hidenobu
Kukita, Yoji
Kato, Kikuya
author_sort Segawa, Hidenobu
collection PubMed
description 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.
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spelling pubmed-57045452017-12-05 HLA genotyping by next-generation sequencing of complementary DNA Segawa, Hidenobu Kukita, Yoji Kato, Kikuya BMC Genomics Methodology Article 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. BioMed Central 2017-11-28 /pmc/articles/PMC5704545/ /pubmed/29179676 http://dx.doi.org/10.1186/s12864-017-4300-7 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology Article
Segawa, Hidenobu
Kukita, Yoji
Kato, Kikuya
HLA genotyping by next-generation sequencing of complementary DNA
title HLA genotyping by next-generation sequencing of complementary DNA
title_full HLA genotyping by next-generation sequencing of complementary DNA
title_fullStr HLA genotyping by next-generation sequencing of complementary DNA
title_full_unstemmed HLA genotyping by next-generation sequencing of complementary DNA
title_short HLA genotyping by next-generation sequencing of complementary DNA
title_sort hla genotyping by next-generation sequencing of complementary dna
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5704545/
https://www.ncbi.nlm.nih.gov/pubmed/29179676
http://dx.doi.org/10.1186/s12864-017-4300-7
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