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Genome-wide segregation of single nucleotide and structural variants into single cancer cells
BACKGROUND: Single-cell genome sequencing provides high-resolution details of the clonal genomic modifications that occur during cancer initiation, progression, and ongoing evolution as patients undergo treatment. One limitation of current single-cell sequencing strategies is a suboptimal capacity t...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5702214/ https://www.ncbi.nlm.nih.gov/pubmed/29178827 http://dx.doi.org/10.1186/s12864-017-4286-1 |
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author | Easton, John Gonzalez-Pena, Veronica Yergeau, Donald Ma, Xiaotu Gawad, Charles |
author_facet | Easton, John Gonzalez-Pena, Veronica Yergeau, Donald Ma, Xiaotu Gawad, Charles |
author_sort | Easton, John |
collection | PubMed |
description | BACKGROUND: Single-cell genome sequencing provides high-resolution details of the clonal genomic modifications that occur during cancer initiation, progression, and ongoing evolution as patients undergo treatment. One limitation of current single-cell sequencing strategies is a suboptimal capacity to detect all classes of single-nucleotide and structural variants in the same cells. RESULTS: Here we present a new approach for determining comprehensive variant profiles of single cells using a microfluidic amplicon-based strategy to detect structural variant breakpoint sequences instead of using relative read depth to infer copy number changes. This method can reconstruct the clonal architecture and mutational history of a malignancy using all classes and sizes of somatic variants, providing more complete details of the temporal changes in mutational classes and processes that led to the development of a malignant neoplasm. Using this approach, we interrogated cells from a patient with leukemia, determining that processes producing structural variation preceded single nucleotide changes in the development of that malignancy. CONCLUSIONS: All classes and sizes of genomic variants can be efficiently detected in single cancer cells using our new method, enabling the ordering of distinct classes of mutations during tumor evolution. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-017-4286-1) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5702214 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-57022142017-12-04 Genome-wide segregation of single nucleotide and structural variants into single cancer cells Easton, John Gonzalez-Pena, Veronica Yergeau, Donald Ma, Xiaotu Gawad, Charles BMC Genomics Methodology Article BACKGROUND: Single-cell genome sequencing provides high-resolution details of the clonal genomic modifications that occur during cancer initiation, progression, and ongoing evolution as patients undergo treatment. One limitation of current single-cell sequencing strategies is a suboptimal capacity to detect all classes of single-nucleotide and structural variants in the same cells. RESULTS: Here we present a new approach for determining comprehensive variant profiles of single cells using a microfluidic amplicon-based strategy to detect structural variant breakpoint sequences instead of using relative read depth to infer copy number changes. This method can reconstruct the clonal architecture and mutational history of a malignancy using all classes and sizes of somatic variants, providing more complete details of the temporal changes in mutational classes and processes that led to the development of a malignant neoplasm. Using this approach, we interrogated cells from a patient with leukemia, determining that processes producing structural variation preceded single nucleotide changes in the development of that malignancy. CONCLUSIONS: All classes and sizes of genomic variants can be efficiently detected in single cancer cells using our new method, enabling the ordering of distinct classes of mutations during tumor evolution. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-017-4286-1) contains supplementary material, which is available to authorized users. BioMed Central 2017-11-25 /pmc/articles/PMC5702214/ /pubmed/29178827 http://dx.doi.org/10.1186/s12864-017-4286-1 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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 | Methodology Article Easton, John Gonzalez-Pena, Veronica Yergeau, Donald Ma, Xiaotu Gawad, Charles Genome-wide segregation of single nucleotide and structural variants into single cancer cells |
title | Genome-wide segregation of single nucleotide and structural variants into single cancer cells |
title_full | Genome-wide segregation of single nucleotide and structural variants into single cancer cells |
title_fullStr | Genome-wide segregation of single nucleotide and structural variants into single cancer cells |
title_full_unstemmed | Genome-wide segregation of single nucleotide and structural variants into single cancer cells |
title_short | Genome-wide segregation of single nucleotide and structural variants into single cancer cells |
title_sort | genome-wide segregation of single nucleotide and structural variants into single cancer cells |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5702214/ https://www.ncbi.nlm.nih.gov/pubmed/29178827 http://dx.doi.org/10.1186/s12864-017-4286-1 |
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