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Next-generation linkage and association methods applied to hypertension: a multifaceted approach to the analysis of sequence data
To realize the full potential of next-generation sequencing, it is important to consider multiple sources of genetic information, including inheritance, association, and bioinformatics. To illustrate the promise of such an approach, we applied our next-generation linkage and association (NGLA) metho...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4143636/ https://www.ncbi.nlm.nih.gov/pubmed/25519364 http://dx.doi.org/10.1186/1753-6561-8-S1-S111 |
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author | Stewart, William CL Huang, Yungui Greenberg, David A Vieland, Veronica J |
author_facet | Stewart, William CL Huang, Yungui Greenberg, David A Vieland, Veronica J |
author_sort | Stewart, William CL |
collection | PubMed |
description | To realize the full potential of next-generation sequencing, it is important to consider multiple sources of genetic information, including inheritance, association, and bioinformatics. To illustrate the promise of such an approach, we applied our next-generation linkage and association (NGLA) methods to the sequence data of a large 57-member Mexican American family with hypertension. Our results show that OSBPL10--a disease susceptibility gene for dyslipidemia--may also influence systolic blood pressure (SBP). In particular, our NGLA dense single-nucleotide polymorphism (SNP) analysis identified a 2.5-megabase (Mb) region that strongly cosegregates with low SBP (maximum posterior probability of linkage [PPL] = 68%). Furthermore, using the posterior probability of linkage disequilibrium (PPLD), we fine-mapped this region and identified 12 SBP-associated variants (PPLD ranging between 4% and 14%) that comprise a rare, 4-site haplotype. This haplotype extends into the candidate gene, OSBPL10 (oxysterol-binding protein-like 10). In contrast to our NGLA methods, a commonly used filter-based approach identified 23 variants with little evidence for spatial clustering around any particular gene or region of interest. |
format | Online Article Text |
id | pubmed-4143636 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-41436362014-09-02 Next-generation linkage and association methods applied to hypertension: a multifaceted approach to the analysis of sequence data Stewart, William CL Huang, Yungui Greenberg, David A Vieland, Veronica J BMC Proc Proceedings To realize the full potential of next-generation sequencing, it is important to consider multiple sources of genetic information, including inheritance, association, and bioinformatics. To illustrate the promise of such an approach, we applied our next-generation linkage and association (NGLA) methods to the sequence data of a large 57-member Mexican American family with hypertension. Our results show that OSBPL10--a disease susceptibility gene for dyslipidemia--may also influence systolic blood pressure (SBP). In particular, our NGLA dense single-nucleotide polymorphism (SNP) analysis identified a 2.5-megabase (Mb) region that strongly cosegregates with low SBP (maximum posterior probability of linkage [PPL] = 68%). Furthermore, using the posterior probability of linkage disequilibrium (PPLD), we fine-mapped this region and identified 12 SBP-associated variants (PPLD ranging between 4% and 14%) that comprise a rare, 4-site haplotype. This haplotype extends into the candidate gene, OSBPL10 (oxysterol-binding protein-like 10). In contrast to our NGLA methods, a commonly used filter-based approach identified 23 variants with little evidence for spatial clustering around any particular gene or region of interest. BioMed Central 2014-06-17 /pmc/articles/PMC4143636/ /pubmed/25519364 http://dx.doi.org/10.1186/1753-6561-8-S1-S111 Text en Copyright © 2014 Stewart et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 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 | Proceedings Stewart, William CL Huang, Yungui Greenberg, David A Vieland, Veronica J Next-generation linkage and association methods applied to hypertension: a multifaceted approach to the analysis of sequence data |
title | Next-generation linkage and association methods applied to hypertension: a multifaceted approach to the analysis of sequence data |
title_full | Next-generation linkage and association methods applied to hypertension: a multifaceted approach to the analysis of sequence data |
title_fullStr | Next-generation linkage and association methods applied to hypertension: a multifaceted approach to the analysis of sequence data |
title_full_unstemmed | Next-generation linkage and association methods applied to hypertension: a multifaceted approach to the analysis of sequence data |
title_short | Next-generation linkage and association methods applied to hypertension: a multifaceted approach to the analysis of sequence data |
title_sort | next-generation linkage and association methods applied to hypertension: a multifaceted approach to the analysis of sequence data |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4143636/ https://www.ncbi.nlm.nih.gov/pubmed/25519364 http://dx.doi.org/10.1186/1753-6561-8-S1-S111 |
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