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Partitioning stable and unstable expression level variation in cell populations: A theoretical framework and its application to the T cell receptor
Phenotypic variation in the copy number of gene products expressed by cells or tissues has been the focus of intense investigation. To what extent the observed differences in cellular expression levels are persistent or transient is an intriguing question. Here, we develop a quantitative framework t...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7498022/ https://www.ncbi.nlm.nih.gov/pubmed/32841238 http://dx.doi.org/10.1371/journal.pcbi.1007910 |
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author | Guzella, Thiago S. Barreto, Vasco M. Carneiro, Jorge |
author_facet | Guzella, Thiago S. Barreto, Vasco M. Carneiro, Jorge |
author_sort | Guzella, Thiago S. |
collection | PubMed |
description | Phenotypic variation in the copy number of gene products expressed by cells or tissues has been the focus of intense investigation. To what extent the observed differences in cellular expression levels are persistent or transient is an intriguing question. Here, we develop a quantitative framework that resolves the expression variation into stable and unstable components. The difference between the expression means in two cohorts isolated from any cell population is shown to converge to an asymptotic value, with a characteristic time, τ(T), that measures the timescale of the unstable dynamics. The asymptotic difference in the means, relative to the initial value, measures the stable proportion of the original population variance [Image: see text] . Empowered by this insight, we analysed the T-cell receptor (TCR) expression variation in CD4 T cells. About 70% of TCR expression variance is stable in a diverse polyclonal population, while over 80% of the variance in an isogenic TCR transgenic population is volatile. In both populations the TCR levels fluctuate with a characteristic time of 32 hours. This systematic characterisation of the expression variation dynamics, relying on time series of cohorts’ means, can be combined with technologies that measure gene or protein expression in single cells or in bulk. |
format | Online Article Text |
id | pubmed-7498022 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-74980222020-09-24 Partitioning stable and unstable expression level variation in cell populations: A theoretical framework and its application to the T cell receptor Guzella, Thiago S. Barreto, Vasco M. Carneiro, Jorge PLoS Comput Biol Research Article Phenotypic variation in the copy number of gene products expressed by cells or tissues has been the focus of intense investigation. To what extent the observed differences in cellular expression levels are persistent or transient is an intriguing question. Here, we develop a quantitative framework that resolves the expression variation into stable and unstable components. The difference between the expression means in two cohorts isolated from any cell population is shown to converge to an asymptotic value, with a characteristic time, τ(T), that measures the timescale of the unstable dynamics. The asymptotic difference in the means, relative to the initial value, measures the stable proportion of the original population variance [Image: see text] . Empowered by this insight, we analysed the T-cell receptor (TCR) expression variation in CD4 T cells. About 70% of TCR expression variance is stable in a diverse polyclonal population, while over 80% of the variance in an isogenic TCR transgenic population is volatile. In both populations the TCR levels fluctuate with a characteristic time of 32 hours. This systematic characterisation of the expression variation dynamics, relying on time series of cohorts’ means, can be combined with technologies that measure gene or protein expression in single cells or in bulk. Public Library of Science 2020-08-25 /pmc/articles/PMC7498022/ /pubmed/32841238 http://dx.doi.org/10.1371/journal.pcbi.1007910 Text en © 2020 Guzella et al 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 author and source are credited. |
spellingShingle | Research Article Guzella, Thiago S. Barreto, Vasco M. Carneiro, Jorge Partitioning stable and unstable expression level variation in cell populations: A theoretical framework and its application to the T cell receptor |
title | Partitioning stable and unstable expression level variation in cell populations: A theoretical framework and its application to the T cell receptor |
title_full | Partitioning stable and unstable expression level variation in cell populations: A theoretical framework and its application to the T cell receptor |
title_fullStr | Partitioning stable and unstable expression level variation in cell populations: A theoretical framework and its application to the T cell receptor |
title_full_unstemmed | Partitioning stable and unstable expression level variation in cell populations: A theoretical framework and its application to the T cell receptor |
title_short | Partitioning stable and unstable expression level variation in cell populations: A theoretical framework and its application to the T cell receptor |
title_sort | partitioning stable and unstable expression level variation in cell populations: a theoretical framework and its application to the t cell receptor |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7498022/ https://www.ncbi.nlm.nih.gov/pubmed/32841238 http://dx.doi.org/10.1371/journal.pcbi.1007910 |
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