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HLA Diversity in the 1000 Genomes Dataset
The 1000 Genomes Project aims to provide a deep characterization of human genome sequence variation by sequencing at a level that should allow the genome-wide detection of most variants with frequencies as low as 1%. However, in the major histocompatibility complex (MHC), only the top 10 most freque...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4079705/ https://www.ncbi.nlm.nih.gov/pubmed/24988075 http://dx.doi.org/10.1371/journal.pone.0097282 |
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author | Gourraud, Pierre-Antoine Khankhanian, Pouya Cereb, Nezih Yang, Soo Young Feolo, Michael Maiers, Martin D. Rioux, John Hauser, Stephen Oksenberg, Jorge |
author_facet | Gourraud, Pierre-Antoine Khankhanian, Pouya Cereb, Nezih Yang, Soo Young Feolo, Michael Maiers, Martin D. Rioux, John Hauser, Stephen Oksenberg, Jorge |
author_sort | Gourraud, Pierre-Antoine |
collection | PubMed |
description | The 1000 Genomes Project aims to provide a deep characterization of human genome sequence variation by sequencing at a level that should allow the genome-wide detection of most variants with frequencies as low as 1%. However, in the major histocompatibility complex (MHC), only the top 10 most frequent haplotypes are in the 1% frequency range whereas thousands of haplotypes are present at lower frequencies. Given the limitation of both the coverage and the read length of the sequences generated by the 1000 Genomes Project, the highly variable positions that define HLA alleles may be difficult to identify. We used classical Sanger sequencing techniques to type the HLA-A, HLA-B, HLA-C, HLA-DRB1 and HLA-DQB1 genes in the available 1000 Genomes samples and combined the results with the 103,310 variants in the MHC region genotyped by the 1000 Genomes Project. Using pairwise identity-by-descent distances between individuals and principal component analysis, we established the relationship between ancestry and genetic diversity in the MHC region. As expected, both the MHC variants and the HLA phenotype can identify the major ancestry lineage, informed mainly by the most frequent HLA haplotypes. To some extent, regions of the genome with similar genetic or similar recombination rate have similar properties. An MHC-centric analysis underlines departures between the ancestral background of the MHC and the genome-wide picture. Our analysis of linkage disequilibrium (LD) decay in these samples suggests that overestimation of pairwise LD occurs due to a limited sampling of the MHC diversity. This collection of HLA-specific MHC variants, available on the dbMHC portal, is a valuable resource for future analyses of the role of MHC in population and disease studies. |
format | Online Article Text |
id | pubmed-4079705 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-40797052014-07-08 HLA Diversity in the 1000 Genomes Dataset Gourraud, Pierre-Antoine Khankhanian, Pouya Cereb, Nezih Yang, Soo Young Feolo, Michael Maiers, Martin D. Rioux, John Hauser, Stephen Oksenberg, Jorge PLoS One Research Article The 1000 Genomes Project aims to provide a deep characterization of human genome sequence variation by sequencing at a level that should allow the genome-wide detection of most variants with frequencies as low as 1%. However, in the major histocompatibility complex (MHC), only the top 10 most frequent haplotypes are in the 1% frequency range whereas thousands of haplotypes are present at lower frequencies. Given the limitation of both the coverage and the read length of the sequences generated by the 1000 Genomes Project, the highly variable positions that define HLA alleles may be difficult to identify. We used classical Sanger sequencing techniques to type the HLA-A, HLA-B, HLA-C, HLA-DRB1 and HLA-DQB1 genes in the available 1000 Genomes samples and combined the results with the 103,310 variants in the MHC region genotyped by the 1000 Genomes Project. Using pairwise identity-by-descent distances between individuals and principal component analysis, we established the relationship between ancestry and genetic diversity in the MHC region. As expected, both the MHC variants and the HLA phenotype can identify the major ancestry lineage, informed mainly by the most frequent HLA haplotypes. To some extent, regions of the genome with similar genetic or similar recombination rate have similar properties. An MHC-centric analysis underlines departures between the ancestral background of the MHC and the genome-wide picture. Our analysis of linkage disequilibrium (LD) decay in these samples suggests that overestimation of pairwise LD occurs due to a limited sampling of the MHC diversity. This collection of HLA-specific MHC variants, available on the dbMHC portal, is a valuable resource for future analyses of the role of MHC in population and disease studies. Public Library of Science 2014-07-02 /pmc/articles/PMC4079705/ /pubmed/24988075 http://dx.doi.org/10.1371/journal.pone.0097282 Text en © 2014 Gourraud 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Gourraud, Pierre-Antoine Khankhanian, Pouya Cereb, Nezih Yang, Soo Young Feolo, Michael Maiers, Martin D. Rioux, John Hauser, Stephen Oksenberg, Jorge HLA Diversity in the 1000 Genomes Dataset |
title |
HLA Diversity in the 1000 Genomes Dataset |
title_full |
HLA Diversity in the 1000 Genomes Dataset |
title_fullStr |
HLA Diversity in the 1000 Genomes Dataset |
title_full_unstemmed |
HLA Diversity in the 1000 Genomes Dataset |
title_short |
HLA Diversity in the 1000 Genomes Dataset |
title_sort | hla diversity in the 1000 genomes dataset |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4079705/ https://www.ncbi.nlm.nih.gov/pubmed/24988075 http://dx.doi.org/10.1371/journal.pone.0097282 |
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