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Blood group typing from whole-genome sequencing data

Many questions can be explored thanks to whole-genome data. The aim of this study was to overcome their main limits, software availability and database accuracy, and estimate the feasibility of red blood cell (RBC) antigen typing from whole-genome sequencing (WGS) data. We analyzed whole-genome data...

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Autores principales: Paganini, Julien, Nagy, Peter L., Rouse, Nicholas, Gouret, Philippe, Chiaroni, Jacques, Picard, Chistophe, Di Cristofaro, Julie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660531/
https://www.ncbi.nlm.nih.gov/pubmed/33180819
http://dx.doi.org/10.1371/journal.pone.0242168
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author Paganini, Julien
Nagy, Peter L.
Rouse, Nicholas
Gouret, Philippe
Chiaroni, Jacques
Picard, Chistophe
Di Cristofaro, Julie
author_facet Paganini, Julien
Nagy, Peter L.
Rouse, Nicholas
Gouret, Philippe
Chiaroni, Jacques
Picard, Chistophe
Di Cristofaro, Julie
author_sort Paganini, Julien
collection PubMed
description Many questions can be explored thanks to whole-genome data. The aim of this study was to overcome their main limits, software availability and database accuracy, and estimate the feasibility of red blood cell (RBC) antigen typing from whole-genome sequencing (WGS) data. We analyzed whole-genome data from 79 individuals for HLA-DRB1 and 9 RBC antigens. Whole-genome sequencing data was analyzed with software allowing phasing of variable positions to define alleles or haplotypes and validated for HLA typing from next-generation sequencing data. A dedicated database was set up with 1648 variable positions analyzed in KEL (KEL), ACKR1 (FY), SLC14A1 (JK), ACHE (YT), ART4 (DO), AQP1 (CO), CD44 (IN), SLC4A1 (DI) and ICAM4 (LW). Whole-genome sequencing typing was compared to that previously obtained by amplicon-based monoallelic sequencing and by SNaPshot analysis. Whole-genome sequencing data were also explored for other alleles. Our results showed 93% of concordance for blood group polymorphisms and 91% for HLA-DRB1. Incorrect typing and unresolved results confirm that WGS should be considered reliable with read depths strictly above 15x. Our results supported that RBC antigen typing from WGS is feasible but requires improvements in read depth for SNV polymorphisms typing accuracy. We also showed the potential for WGS in screening donors with rare blood antigens, such as weak JK alleles. The development of WGS analysis in immunogenetics laboratories would offer personalized care in the management of RBC disorders.
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spelling pubmed-76605312020-11-18 Blood group typing from whole-genome sequencing data Paganini, Julien Nagy, Peter L. Rouse, Nicholas Gouret, Philippe Chiaroni, Jacques Picard, Chistophe Di Cristofaro, Julie PLoS One Research Article Many questions can be explored thanks to whole-genome data. The aim of this study was to overcome their main limits, software availability and database accuracy, and estimate the feasibility of red blood cell (RBC) antigen typing from whole-genome sequencing (WGS) data. We analyzed whole-genome data from 79 individuals for HLA-DRB1 and 9 RBC antigens. Whole-genome sequencing data was analyzed with software allowing phasing of variable positions to define alleles or haplotypes and validated for HLA typing from next-generation sequencing data. A dedicated database was set up with 1648 variable positions analyzed in KEL (KEL), ACKR1 (FY), SLC14A1 (JK), ACHE (YT), ART4 (DO), AQP1 (CO), CD44 (IN), SLC4A1 (DI) and ICAM4 (LW). Whole-genome sequencing typing was compared to that previously obtained by amplicon-based monoallelic sequencing and by SNaPshot analysis. Whole-genome sequencing data were also explored for other alleles. Our results showed 93% of concordance for blood group polymorphisms and 91% for HLA-DRB1. Incorrect typing and unresolved results confirm that WGS should be considered reliable with read depths strictly above 15x. Our results supported that RBC antigen typing from WGS is feasible but requires improvements in read depth for SNV polymorphisms typing accuracy. We also showed the potential for WGS in screening donors with rare blood antigens, such as weak JK alleles. The development of WGS analysis in immunogenetics laboratories would offer personalized care in the management of RBC disorders. Public Library of Science 2020-11-12 /pmc/articles/PMC7660531/ /pubmed/33180819 http://dx.doi.org/10.1371/journal.pone.0242168 Text en © 2020 Paganini et al 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 use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Paganini, Julien
Nagy, Peter L.
Rouse, Nicholas
Gouret, Philippe
Chiaroni, Jacques
Picard, Chistophe
Di Cristofaro, Julie
Blood group typing from whole-genome sequencing data
title Blood group typing from whole-genome sequencing data
title_full Blood group typing from whole-genome sequencing data
title_fullStr Blood group typing from whole-genome sequencing data
title_full_unstemmed Blood group typing from whole-genome sequencing data
title_short Blood group typing from whole-genome sequencing data
title_sort blood group typing from whole-genome sequencing data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660531/
https://www.ncbi.nlm.nih.gov/pubmed/33180819
http://dx.doi.org/10.1371/journal.pone.0242168
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