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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...

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Autores principales: Stewart, William CL, Huang, Yungui, Greenberg, David A, Vieland, Veronica J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
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.
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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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