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A yeast-optimized single-cell transcriptomics platform elucidates how mycophenolic acid and guanine alter global mRNA levels

Stochastic gene expression leads to inherent variability in expression outcomes even in isogenic single-celled organisms grown in the same environment. The Drop-Seq technology facilitates transcriptomic studies of individual mammalian cells, and it has had transformative effects on the characterizat...

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Autores principales: Urbonaite, Guste, Lee, Jimmy Tsz Hang, Liu, Ping, Parada, Guillermo E., Hemberg, Martin, Acar, Murat
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8245502/
https://www.ncbi.nlm.nih.gov/pubmed/34193958
http://dx.doi.org/10.1038/s42003-021-02320-w
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author Urbonaite, Guste
Lee, Jimmy Tsz Hang
Liu, Ping
Parada, Guillermo E.
Hemberg, Martin
Acar, Murat
author_facet Urbonaite, Guste
Lee, Jimmy Tsz Hang
Liu, Ping
Parada, Guillermo E.
Hemberg, Martin
Acar, Murat
author_sort Urbonaite, Guste
collection PubMed
description Stochastic gene expression leads to inherent variability in expression outcomes even in isogenic single-celled organisms grown in the same environment. The Drop-Seq technology facilitates transcriptomic studies of individual mammalian cells, and it has had transformative effects on the characterization of cell identity and function based on single-cell transcript counts. However, application of this technology to organisms with different cell size and morphology characteristics has been challenging. Here we present yeastDrop-Seq, a yeast-optimized platform for quantifying the number of distinct mRNA molecules in a cell-specific manner in individual yeast cells. Using yeastDrop-Seq, we measured the transcriptomic impact of the lifespan-extending compound mycophenolic acid and its epistatic agent guanine. Each treatment condition had a distinct transcriptomic footprint on isogenic yeast cells as indicated by distinct clustering with clear separations among the different groups. The yeastDrop-Seq platform facilitates transcriptomic profiling of yeast cells for basic science and biotechnology applications.
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spelling pubmed-82455022021-07-20 A yeast-optimized single-cell transcriptomics platform elucidates how mycophenolic acid and guanine alter global mRNA levels Urbonaite, Guste Lee, Jimmy Tsz Hang Liu, Ping Parada, Guillermo E. Hemberg, Martin Acar, Murat Commun Biol Article Stochastic gene expression leads to inherent variability in expression outcomes even in isogenic single-celled organisms grown in the same environment. The Drop-Seq technology facilitates transcriptomic studies of individual mammalian cells, and it has had transformative effects on the characterization of cell identity and function based on single-cell transcript counts. However, application of this technology to organisms with different cell size and morphology characteristics has been challenging. Here we present yeastDrop-Seq, a yeast-optimized platform for quantifying the number of distinct mRNA molecules in a cell-specific manner in individual yeast cells. Using yeastDrop-Seq, we measured the transcriptomic impact of the lifespan-extending compound mycophenolic acid and its epistatic agent guanine. Each treatment condition had a distinct transcriptomic footprint on isogenic yeast cells as indicated by distinct clustering with clear separations among the different groups. The yeastDrop-Seq platform facilitates transcriptomic profiling of yeast cells for basic science and biotechnology applications. Nature Publishing Group UK 2021-06-30 /pmc/articles/PMC8245502/ /pubmed/34193958 http://dx.doi.org/10.1038/s42003-021-02320-w Text en © The Author(s) 2021, corrected publication 2021 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Urbonaite, Guste
Lee, Jimmy Tsz Hang
Liu, Ping
Parada, Guillermo E.
Hemberg, Martin
Acar, Murat
A yeast-optimized single-cell transcriptomics platform elucidates how mycophenolic acid and guanine alter global mRNA levels
title A yeast-optimized single-cell transcriptomics platform elucidates how mycophenolic acid and guanine alter global mRNA levels
title_full A yeast-optimized single-cell transcriptomics platform elucidates how mycophenolic acid and guanine alter global mRNA levels
title_fullStr A yeast-optimized single-cell transcriptomics platform elucidates how mycophenolic acid and guanine alter global mRNA levels
title_full_unstemmed A yeast-optimized single-cell transcriptomics platform elucidates how mycophenolic acid and guanine alter global mRNA levels
title_short A yeast-optimized single-cell transcriptomics platform elucidates how mycophenolic acid and guanine alter global mRNA levels
title_sort yeast-optimized single-cell transcriptomics platform elucidates how mycophenolic acid and guanine alter global mrna levels
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8245502/
https://www.ncbi.nlm.nih.gov/pubmed/34193958
http://dx.doi.org/10.1038/s42003-021-02320-w
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