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Experimental and bioinformatics considerations in cancer application of single cell genomics
Single cell genomics offers an unprecedented resolution to interrogate genetic heterogeneity in a patient’s tumour at the intercellular level. However, the DNA yield per cell is insufficient for today’s sequencing library preparation protocols. This necessitates DNA amplification which is a key sour...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7788095/ https://www.ncbi.nlm.nih.gov/pubmed/33489004 http://dx.doi.org/10.1016/j.csbj.2020.12.021 |
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author | Tan, Joanna Hui Juan Kong, Say Li Tai, Joyce A. Poh, Huay Mei Yao, Fei Sia, Yee Yen Lim, Edwin Kok Hao Takano, Angela Maria Tan, Daniel Shao-Weng Javed, Asif Hillmer, Axel M. |
author_facet | Tan, Joanna Hui Juan Kong, Say Li Tai, Joyce A. Poh, Huay Mei Yao, Fei Sia, Yee Yen Lim, Edwin Kok Hao Takano, Angela Maria Tan, Daniel Shao-Weng Javed, Asif Hillmer, Axel M. |
author_sort | Tan, Joanna Hui Juan |
collection | PubMed |
description | Single cell genomics offers an unprecedented resolution to interrogate genetic heterogeneity in a patient’s tumour at the intercellular level. However, the DNA yield per cell is insufficient for today’s sequencing library preparation protocols. This necessitates DNA amplification which is a key source of experimental noise. We provide an evaluation of two protocols using micro-fluidics based amplification for whole exome sequencing, which is an experimental scenario commonly used in single cell genomics. The results highlight their respective biases and relative strengths in identification of single nucleotide variations. Towards this end, we introduce a workflow SoVaTSiC, which allows for quality evaluation and somatic variant identification of single cell data. As proof of concept, the framework was applied to study a lung adenocarcinoma tumour. The analysis provides insights into tumour phylogeny by identifying key mutational events in lung adenocarcinoma evolution. The consequence of this inference is supported by the histology of the tumour and demonstrates usefulness of the approach. |
format | Online Article Text |
id | pubmed-7788095 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-77880952021-01-22 Experimental and bioinformatics considerations in cancer application of single cell genomics Tan, Joanna Hui Juan Kong, Say Li Tai, Joyce A. Poh, Huay Mei Yao, Fei Sia, Yee Yen Lim, Edwin Kok Hao Takano, Angela Maria Tan, Daniel Shao-Weng Javed, Asif Hillmer, Axel M. Comput Struct Biotechnol J Research Article Single cell genomics offers an unprecedented resolution to interrogate genetic heterogeneity in a patient’s tumour at the intercellular level. However, the DNA yield per cell is insufficient for today’s sequencing library preparation protocols. This necessitates DNA amplification which is a key source of experimental noise. We provide an evaluation of two protocols using micro-fluidics based amplification for whole exome sequencing, which is an experimental scenario commonly used in single cell genomics. The results highlight their respective biases and relative strengths in identification of single nucleotide variations. Towards this end, we introduce a workflow SoVaTSiC, which allows for quality evaluation and somatic variant identification of single cell data. As proof of concept, the framework was applied to study a lung adenocarcinoma tumour. The analysis provides insights into tumour phylogeny by identifying key mutational events in lung adenocarcinoma evolution. The consequence of this inference is supported by the histology of the tumour and demonstrates usefulness of the approach. Research Network of Computational and Structural Biotechnology 2020-12-23 /pmc/articles/PMC7788095/ /pubmed/33489004 http://dx.doi.org/10.1016/j.csbj.2020.12.021 Text en © 2020 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Tan, Joanna Hui Juan Kong, Say Li Tai, Joyce A. Poh, Huay Mei Yao, Fei Sia, Yee Yen Lim, Edwin Kok Hao Takano, Angela Maria Tan, Daniel Shao-Weng Javed, Asif Hillmer, Axel M. Experimental and bioinformatics considerations in cancer application of single cell genomics |
title | Experimental and bioinformatics considerations in cancer application of single cell genomics |
title_full | Experimental and bioinformatics considerations in cancer application of single cell genomics |
title_fullStr | Experimental and bioinformatics considerations in cancer application of single cell genomics |
title_full_unstemmed | Experimental and bioinformatics considerations in cancer application of single cell genomics |
title_short | Experimental and bioinformatics considerations in cancer application of single cell genomics |
title_sort | experimental and bioinformatics considerations in cancer application of single cell genomics |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7788095/ https://www.ncbi.nlm.nih.gov/pubmed/33489004 http://dx.doi.org/10.1016/j.csbj.2020.12.021 |
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