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Use of a targeted, combinatorial next-generation sequencing approach for the study of bicuspid aortic valve
BACKGROUND: Bicuspid aortic valve (BAV) is the most common type of congenital heart disease with a population prevalence of 1-2%. While BAV is known to be highly heritable, mutations in single genes (such as GATA5 and NOTCH1) have been reported in few human BAV cases. Traditional gene sequencing met...
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/PMC4181662/ https://www.ncbi.nlm.nih.gov/pubmed/25260786 http://dx.doi.org/10.1186/1755-8794-7-56 |
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author | Bonachea, Elizabeth M Zender, Gloria White, Peter Corsmeier, Don Newsom, David Fitzgerald-Butt, Sara Garg, Vidu McBride, Kim L |
author_facet | Bonachea, Elizabeth M Zender, Gloria White, Peter Corsmeier, Don Newsom, David Fitzgerald-Butt, Sara Garg, Vidu McBride, Kim L |
author_sort | Bonachea, Elizabeth M |
collection | PubMed |
description | BACKGROUND: Bicuspid aortic valve (BAV) is the most common type of congenital heart disease with a population prevalence of 1-2%. While BAV is known to be highly heritable, mutations in single genes (such as GATA5 and NOTCH1) have been reported in few human BAV cases. Traditional gene sequencing methods are time and labor intensive, while next-generation high throughput sequencing remains costly for large patient cohorts and requires extensive bioinformatics processing. Here we describe an approach to targeted multi-gene sequencing with combinatorial pooling of samples from BAV patients. METHODS: We studied a previously described cohort of 78 unrelated subjects with echocardiogram-identified BAV. Subjects were identified as having isolated BAV or BAV associated with coarctation of aorta (BAV-CoA). BAV cusp fusion morphology was defined as right-left cusp fusion, right non-coronary cusp fusion, or left non-coronary cusp fusion. Samples were combined into 19 pools using a uniquely overlapping combinatorial design; a given mutation could be attributed to a single individual on the basis of which pools contained the mutation. A custom gene capture of 97 candidate genes was sequenced on the Illumina HiSeq 2000. Multistep bioinformatics processing was performed for base calling, variant identification, and in-silico analysis of putative disease-causing variants. RESULTS: Targeted capture identified 42 rare, non-synonymous, exonic variants involving 35 of the 97 candidate genes. Among these variants, in-silico analysis classified 33 of these variants as putative disease-causing changes. Sanger sequencing confirmed thirty-one of these variants, found among 16 individuals. There were no significant differences in variant burden among BAV fusion phenotypes or isolated BAV versus BAV-CoA. Pathway analysis suggests a role for the WNT signaling pathway in human BAV. CONCLUSION: We successfully developed a pooling and targeted capture strategy that enabled rapid and cost effective next generation sequencing of target genes in a large patient cohort. This approach identified a large number of putative disease-causing variants in a cohort of patients with BAV, including variants in 26 genes not previously associated with human BAV. The data suggest that BAV heritability is complex and polygenic. Our pooling approach saved over $39,350 compared to an unpooled, targeted capture sequencing strategy. |
format | Online Article Text |
id | pubmed-4181662 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-41816622014-10-03 Use of a targeted, combinatorial next-generation sequencing approach for the study of bicuspid aortic valve Bonachea, Elizabeth M Zender, Gloria White, Peter Corsmeier, Don Newsom, David Fitzgerald-Butt, Sara Garg, Vidu McBride, Kim L BMC Med Genomics Research Article BACKGROUND: Bicuspid aortic valve (BAV) is the most common type of congenital heart disease with a population prevalence of 1-2%. While BAV is known to be highly heritable, mutations in single genes (such as GATA5 and NOTCH1) have been reported in few human BAV cases. Traditional gene sequencing methods are time and labor intensive, while next-generation high throughput sequencing remains costly for large patient cohorts and requires extensive bioinformatics processing. Here we describe an approach to targeted multi-gene sequencing with combinatorial pooling of samples from BAV patients. METHODS: We studied a previously described cohort of 78 unrelated subjects with echocardiogram-identified BAV. Subjects were identified as having isolated BAV or BAV associated with coarctation of aorta (BAV-CoA). BAV cusp fusion morphology was defined as right-left cusp fusion, right non-coronary cusp fusion, or left non-coronary cusp fusion. Samples were combined into 19 pools using a uniquely overlapping combinatorial design; a given mutation could be attributed to a single individual on the basis of which pools contained the mutation. A custom gene capture of 97 candidate genes was sequenced on the Illumina HiSeq 2000. Multistep bioinformatics processing was performed for base calling, variant identification, and in-silico analysis of putative disease-causing variants. RESULTS: Targeted capture identified 42 rare, non-synonymous, exonic variants involving 35 of the 97 candidate genes. Among these variants, in-silico analysis classified 33 of these variants as putative disease-causing changes. Sanger sequencing confirmed thirty-one of these variants, found among 16 individuals. There were no significant differences in variant burden among BAV fusion phenotypes or isolated BAV versus BAV-CoA. Pathway analysis suggests a role for the WNT signaling pathway in human BAV. CONCLUSION: We successfully developed a pooling and targeted capture strategy that enabled rapid and cost effective next generation sequencing of target genes in a large patient cohort. This approach identified a large number of putative disease-causing variants in a cohort of patients with BAV, including variants in 26 genes not previously associated with human BAV. The data suggest that BAV heritability is complex and polygenic. Our pooling approach saved over $39,350 compared to an unpooled, targeted capture sequencing strategy. BioMed Central 2014-09-26 /pmc/articles/PMC4181662/ /pubmed/25260786 http://dx.doi.org/10.1186/1755-8794-7-56 Text en Copyright © 2014 Bonachea et al.; licensee BioMed Central Ltd. 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 work is properly credited. 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 | Research Article Bonachea, Elizabeth M Zender, Gloria White, Peter Corsmeier, Don Newsom, David Fitzgerald-Butt, Sara Garg, Vidu McBride, Kim L Use of a targeted, combinatorial next-generation sequencing approach for the study of bicuspid aortic valve |
title | Use of a targeted, combinatorial next-generation sequencing approach for the study of bicuspid aortic valve |
title_full | Use of a targeted, combinatorial next-generation sequencing approach for the study of bicuspid aortic valve |
title_fullStr | Use of a targeted, combinatorial next-generation sequencing approach for the study of bicuspid aortic valve |
title_full_unstemmed | Use of a targeted, combinatorial next-generation sequencing approach for the study of bicuspid aortic valve |
title_short | Use of a targeted, combinatorial next-generation sequencing approach for the study of bicuspid aortic valve |
title_sort | use of a targeted, combinatorial next-generation sequencing approach for the study of bicuspid aortic valve |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4181662/ https://www.ncbi.nlm.nih.gov/pubmed/25260786 http://dx.doi.org/10.1186/1755-8794-7-56 |
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