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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 an...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4477639/ https://www.ncbi.nlm.nih.gov/pubmed/25753671 http://dx.doi.org/10.1093/nar/gkv184 |
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author | Wittig, Michael Anmarkrud, Jarl A. Kässens, Jan C. Koch, Simon Forster, Michael Ellinghaus, Eva Hov, Johannes R. Sauer, Sascha Schimmler, Manfred Ziemann, Malte Görg, Siegfried Jacob, Frank Karlsen, Tom H. Franke, Andre |
author_facet | Wittig, Michael Anmarkrud, Jarl A. Kässens, Jan C. Koch, Simon Forster, Michael Ellinghaus, Eva Hov, Johannes R. Sauer, Sascha Schimmler, Manfred Ziemann, Malte Görg, Siegfried Jacob, Frank Karlsen, Tom H. Franke, Andre |
author_sort | Wittig, Michael |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4477639 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-44776392015-06-29 Development of a high-resolution NGS-based HLA-typing and analysis pipeline Wittig, Michael Anmarkrud, Jarl A. Kässens, Jan C. Koch, Simon Forster, Michael Ellinghaus, Eva Hov, Johannes R. Sauer, Sascha Schimmler, Manfred Ziemann, Malte Görg, Siegfried Jacob, Frank Karlsen, Tom H. Franke, Andre Nucleic Acids Res Methods Online 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. Oxford University Press 2015-06-23 2015-03-09 /pmc/articles/PMC4477639/ /pubmed/25753671 http://dx.doi.org/10.1093/nar/gkv184 Text en © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methods Online Wittig, Michael Anmarkrud, Jarl A. Kässens, Jan C. Koch, Simon Forster, Michael Ellinghaus, Eva Hov, Johannes R. Sauer, Sascha Schimmler, Manfred Ziemann, Malte Görg, Siegfried Jacob, Frank Karlsen, Tom H. Franke, Andre Development of a high-resolution NGS-based HLA-typing and analysis pipeline |
title | Development of a high-resolution NGS-based HLA-typing and analysis pipeline |
title_full | Development of a high-resolution NGS-based HLA-typing and analysis pipeline |
title_fullStr | Development of a high-resolution NGS-based HLA-typing and analysis pipeline |
title_full_unstemmed | Development of a high-resolution NGS-based HLA-typing and analysis pipeline |
title_short | Development of a high-resolution NGS-based HLA-typing and analysis pipeline |
title_sort | development of a high-resolution ngs-based hla-typing and analysis pipeline |
topic | Methods Online |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4477639/ https://www.ncbi.nlm.nih.gov/pubmed/25753671 http://dx.doi.org/10.1093/nar/gkv184 |
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