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EM-mosaic detects mosaic point mutations that contribute to congenital heart disease
BACKGROUND: The contribution of somatic mosaicism, or genetic mutations arising after oocyte fertilization, to congenital heart disease (CHD) is not well understood. Further, the relationship between mosaicism in blood and cardiovascular tissue has not been determined. METHODS: We developed a new co...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7189690/ https://www.ncbi.nlm.nih.gov/pubmed/32349777 http://dx.doi.org/10.1186/s13073-020-00738-1 |
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author | Hsieh, Alexander Morton, Sarah U. Willcox, Jon A. L. Gorham, Joshua M. Tai, Angela C. Qi, Hongjian DePalma, Steven McKean, David Griffin, Emily Manheimer, Kathryn B. Bernstein, Daniel Kim, Richard W. Newburger, Jane W. Porter, George A. Srivastava, Deepak Tristani-Firouzi, Martin Brueckner, Martina Lifton, Richard P. Goldmuntz, Elizabeth Gelb, Bruce D. Chung, Wendy K. Seidman, Christine E. Seidman, J. G. Shen, Yufeng |
author_facet | Hsieh, Alexander Morton, Sarah U. Willcox, Jon A. L. Gorham, Joshua M. Tai, Angela C. Qi, Hongjian DePalma, Steven McKean, David Griffin, Emily Manheimer, Kathryn B. Bernstein, Daniel Kim, Richard W. Newburger, Jane W. Porter, George A. Srivastava, Deepak Tristani-Firouzi, Martin Brueckner, Martina Lifton, Richard P. Goldmuntz, Elizabeth Gelb, Bruce D. Chung, Wendy K. Seidman, Christine E. Seidman, J. G. Shen, Yufeng |
author_sort | Hsieh, Alexander |
collection | PubMed |
description | BACKGROUND: The contribution of somatic mosaicism, or genetic mutations arising after oocyte fertilization, to congenital heart disease (CHD) is not well understood. Further, the relationship between mosaicism in blood and cardiovascular tissue has not been determined. METHODS: We developed a new computational method, EM-mosaic (Expectation-Maximization-based detection of mosaicism), to analyze mosaicism in exome sequences derived primarily from blood DNA of 2530 CHD proband-parent trios. To optimize this method, we measured mosaic detection power as a function of sequencing depth. In parallel, we analyzed our cohort using MosaicHunter, a Bayesian genotyping algorithm-based mosaic detection tool, and compared the two methods. The accuracy of these mosaic variant detection algorithms was assessed using an independent resequencing method. We then applied both methods to detect mosaicism in cardiac tissue-derived exome sequences of 66 participants for which matched blood and heart tissue was available. RESULTS: EM-mosaic detected 326 mosaic mutations in blood and/or cardiac tissue DNA. Of the 309 detected in blood DNA, 85/97 (88%) tested were independently confirmed, while 7/17 (41%) candidates of 17 detected in cardiac tissue were confirmed. MosaicHunter detected an additional 64 mosaics, of which 23/46 (50%) among 58 candidates from blood and 4/6 (67%) of 6 candidates from cardiac tissue confirmed. Twenty-five mosaic variants altered CHD-risk genes, affecting 1% of our cohort. Of these 25, 22/22 candidates tested were confirmed. Variants predicted as damaging had higher variant allele fraction than benign variants, suggesting a role in CHD. The estimated true frequency of mosaic variants above 10% mosaicism was 0.14/person in blood and 0.21/person in cardiac tissue. Analysis of 66 individuals with matched cardiac tissue available revealed both tissue-specific and shared mosaicism, with shared mosaics generally having higher allele fraction. CONCLUSIONS: We estimate that ~ 1% of CHD probands have a mosaic variant detectable in blood that could contribute to cardiac malformations, particularly those damaging variants with relatively higher allele fraction. Although blood is a readily available DNA source, cardiac tissues analyzed contributed ~ 5% of somatic mosaic variants identified, indicating the value of tissue mosaicism analyses. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13073-020-00738-1) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-7189690 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-71896902020-05-04 EM-mosaic detects mosaic point mutations that contribute to congenital heart disease Hsieh, Alexander Morton, Sarah U. Willcox, Jon A. L. Gorham, Joshua M. Tai, Angela C. Qi, Hongjian DePalma, Steven McKean, David Griffin, Emily Manheimer, Kathryn B. Bernstein, Daniel Kim, Richard W. Newburger, Jane W. Porter, George A. Srivastava, Deepak Tristani-Firouzi, Martin Brueckner, Martina Lifton, Richard P. Goldmuntz, Elizabeth Gelb, Bruce D. Chung, Wendy K. Seidman, Christine E. Seidman, J. G. Shen, Yufeng Genome Med Research BACKGROUND: The contribution of somatic mosaicism, or genetic mutations arising after oocyte fertilization, to congenital heart disease (CHD) is not well understood. Further, the relationship between mosaicism in blood and cardiovascular tissue has not been determined. METHODS: We developed a new computational method, EM-mosaic (Expectation-Maximization-based detection of mosaicism), to analyze mosaicism in exome sequences derived primarily from blood DNA of 2530 CHD proband-parent trios. To optimize this method, we measured mosaic detection power as a function of sequencing depth. In parallel, we analyzed our cohort using MosaicHunter, a Bayesian genotyping algorithm-based mosaic detection tool, and compared the two methods. The accuracy of these mosaic variant detection algorithms was assessed using an independent resequencing method. We then applied both methods to detect mosaicism in cardiac tissue-derived exome sequences of 66 participants for which matched blood and heart tissue was available. RESULTS: EM-mosaic detected 326 mosaic mutations in blood and/or cardiac tissue DNA. Of the 309 detected in blood DNA, 85/97 (88%) tested were independently confirmed, while 7/17 (41%) candidates of 17 detected in cardiac tissue were confirmed. MosaicHunter detected an additional 64 mosaics, of which 23/46 (50%) among 58 candidates from blood and 4/6 (67%) of 6 candidates from cardiac tissue confirmed. Twenty-five mosaic variants altered CHD-risk genes, affecting 1% of our cohort. Of these 25, 22/22 candidates tested were confirmed. Variants predicted as damaging had higher variant allele fraction than benign variants, suggesting a role in CHD. The estimated true frequency of mosaic variants above 10% mosaicism was 0.14/person in blood and 0.21/person in cardiac tissue. Analysis of 66 individuals with matched cardiac tissue available revealed both tissue-specific and shared mosaicism, with shared mosaics generally having higher allele fraction. CONCLUSIONS: We estimate that ~ 1% of CHD probands have a mosaic variant detectable in blood that could contribute to cardiac malformations, particularly those damaging variants with relatively higher allele fraction. Although blood is a readily available DNA source, cardiac tissues analyzed contributed ~ 5% of somatic mosaic variants identified, indicating the value of tissue mosaicism analyses. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13073-020-00738-1) contains supplementary material, which is available to authorized users. BioMed Central 2020-04-29 /pmc/articles/PMC7189690/ /pubmed/32349777 http://dx.doi.org/10.1186/s13073-020-00738-1 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data. |
spellingShingle | Research Hsieh, Alexander Morton, Sarah U. Willcox, Jon A. L. Gorham, Joshua M. Tai, Angela C. Qi, Hongjian DePalma, Steven McKean, David Griffin, Emily Manheimer, Kathryn B. Bernstein, Daniel Kim, Richard W. Newburger, Jane W. Porter, George A. Srivastava, Deepak Tristani-Firouzi, Martin Brueckner, Martina Lifton, Richard P. Goldmuntz, Elizabeth Gelb, Bruce D. Chung, Wendy K. Seidman, Christine E. Seidman, J. G. Shen, Yufeng EM-mosaic detects mosaic point mutations that contribute to congenital heart disease |
title | EM-mosaic detects mosaic point mutations that contribute to congenital heart disease |
title_full | EM-mosaic detects mosaic point mutations that contribute to congenital heart disease |
title_fullStr | EM-mosaic detects mosaic point mutations that contribute to congenital heart disease |
title_full_unstemmed | EM-mosaic detects mosaic point mutations that contribute to congenital heart disease |
title_short | EM-mosaic detects mosaic point mutations that contribute to congenital heart disease |
title_sort | em-mosaic detects mosaic point mutations that contribute to congenital heart disease |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7189690/ https://www.ncbi.nlm.nih.gov/pubmed/32349777 http://dx.doi.org/10.1186/s13073-020-00738-1 |
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