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Single-cell RNA-seq variant analysis for exploration of genetic heterogeneity in cancer
Inter- and intra-tumour heterogeneity is caused by genetic and non-genetic factors, leading to severe clinical implications. High-throughput sequencing technologies provide unprecedented tools to analyse DNA and RNA in single cells and explore both genetic heterogeneity and phenotypic variation betw...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6606766/ https://www.ncbi.nlm.nih.gov/pubmed/31267007 http://dx.doi.org/10.1038/s41598-019-45934-1 |
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author | Fasterius, Erik Uhlén, Mathias Al-Khalili Szigyarto, Cristina |
author_facet | Fasterius, Erik Uhlén, Mathias Al-Khalili Szigyarto, Cristina |
author_sort | Fasterius, Erik |
collection | PubMed |
description | Inter- and intra-tumour heterogeneity is caused by genetic and non-genetic factors, leading to severe clinical implications. High-throughput sequencing technologies provide unprecedented tools to analyse DNA and RNA in single cells and explore both genetic heterogeneity and phenotypic variation between cells in tissues and tumours. Simultaneous analysis of both DNA and RNA in the same cell is, however, still in its infancy. We have thus developed a method to extract and analyse information regarding genetic heterogeneity that affects cellular biology from single-cell RNA-seq data. The method enables both comparisons and clustering of cells based on genetic variation in single nucleotide variants, revealing cellular subpopulations corroborated by gene expression-based methods. Furthermore, the results show that lymph node metastases have lower levels of genetic heterogeneity compared to their original tumours with respect to variants affecting protein function. The analysis also revealed three previously unknown variants common across cancer cells in glioblastoma patients. These results demonstrate the power and versatility of scRNA-seq variant analysis and highlight it as a useful complement to already existing methods, enabling simultaneous investigations of both gene expression and genetic variation. |
format | Online Article Text |
id | pubmed-6606766 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-66067662019-07-14 Single-cell RNA-seq variant analysis for exploration of genetic heterogeneity in cancer Fasterius, Erik Uhlén, Mathias Al-Khalili Szigyarto, Cristina Sci Rep Article Inter- and intra-tumour heterogeneity is caused by genetic and non-genetic factors, leading to severe clinical implications. High-throughput sequencing technologies provide unprecedented tools to analyse DNA and RNA in single cells and explore both genetic heterogeneity and phenotypic variation between cells in tissues and tumours. Simultaneous analysis of both DNA and RNA in the same cell is, however, still in its infancy. We have thus developed a method to extract and analyse information regarding genetic heterogeneity that affects cellular biology from single-cell RNA-seq data. The method enables both comparisons and clustering of cells based on genetic variation in single nucleotide variants, revealing cellular subpopulations corroborated by gene expression-based methods. Furthermore, the results show that lymph node metastases have lower levels of genetic heterogeneity compared to their original tumours with respect to variants affecting protein function. The analysis also revealed three previously unknown variants common across cancer cells in glioblastoma patients. These results demonstrate the power and versatility of scRNA-seq variant analysis and highlight it as a useful complement to already existing methods, enabling simultaneous investigations of both gene expression and genetic variation. Nature Publishing Group UK 2019-07-02 /pmc/articles/PMC6606766/ /pubmed/31267007 http://dx.doi.org/10.1038/s41598-019-45934-1 Text en © The Author(s) 2019 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Fasterius, Erik Uhlén, Mathias Al-Khalili Szigyarto, Cristina Single-cell RNA-seq variant analysis for exploration of genetic heterogeneity in cancer |
title | Single-cell RNA-seq variant analysis for exploration of genetic heterogeneity in cancer |
title_full | Single-cell RNA-seq variant analysis for exploration of genetic heterogeneity in cancer |
title_fullStr | Single-cell RNA-seq variant analysis for exploration of genetic heterogeneity in cancer |
title_full_unstemmed | Single-cell RNA-seq variant analysis for exploration of genetic heterogeneity in cancer |
title_short | Single-cell RNA-seq variant analysis for exploration of genetic heterogeneity in cancer |
title_sort | single-cell rna-seq variant analysis for exploration of genetic heterogeneity in cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6606766/ https://www.ncbi.nlm.nih.gov/pubmed/31267007 http://dx.doi.org/10.1038/s41598-019-45934-1 |
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