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| Status |
Public on Jun 26, 2020 |
| Title |
A yeast-optimized single-cell transcriptomics platform elucidates how mycophenolic acid and guanine alter global mRNA levels |
| Organisms |
Saccharomyces bayanus; Saccharomyces cerevisiae |
| Experiment type |
Expression profiling by high throughput sequencing
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| Summary |
The ability to measure the number of gene-specific mRNA molecules in individual mammalian cells has transformed the transcriptomics field. Among the key technologies enabling single-cell mRNA sequencing has been Droplet Sequencing (Drop-Seq). While this method works efficiently for mammalian cells, its direct application to yeast cells has been problematic due to cell-type specific differences such as size, doublet formation rate, and cell wall. Here we introduce YeastDropSeq, a single-cell RNA sequencing method for the study of transcriptomics in yeast. We modified and optimized the original Drop-Seq method to address the issues that emerged from smaller cell sizes and the presence of a cell wall in yeast. We also quantified the rate of doublet formation through a species-mixing experiment. As proof-of-principle application of the YeastDropSeq, we investigated the transcriptomic effects of mycophenolic acid (MPA), a lifespan-extending compound that decreases de novo GMP synthesis. We compared transcript levels between cells treated with MPA and cells treated with DMSO and/or guanine, MPA’s epistatic agent. We discovered that isogenic populations of yeast cells contain transcriptionally distinct subpopulations and that the subpopulation structures were maintained despite the different treatment conditions. We found that cells treated with MPA experience an upregulation of genes coding for proteins involved in DNA replication stress-response, antioxidation, pre-RNA processing, and translation initiation. Conversely, a downregulation of mRNA expression was observed for genes encoding translation initiation and elongation factors, the 40S and 60S ribosomal subunits, and for genes involved in metal transport and mitochondrial function. Additionally, we elucidated that expression levels of several genes of unknown function were affected by the MPA treatment. YeastDropSeq will accelerate biological discovery by facilitating droplet-based transcriptomics of yeast cells.
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| Overall design |
There are 4 samples analyzed. One sample, DMSO, is the control. The other samples: Guanine, Guanine and Mycophenolic acid, and Mycophenolic acid are treated conditions
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| Contributor(s) |
Urbonaite G, Acar M, Liu P |
| Citation missing |
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| |
| Submission date |
Jan 31, 2020 |
| Last update date |
Jul 11, 2020 |
| Contact name |
Guste Urbonaite |
| E-mail(s) |
guste.urbonaite@yale.edu
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| Phone |
8609384422
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| Organization name |
Yale University
|
| Department |
Molecular and Cellular Biology
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| Lab |
Murat Acar
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| Street address |
300 Heffernan Drive, ISTC, Rm 117
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| City |
West Haven |
| State/province |
CT |
| ZIP/Postal code |
06115 |
| Country |
USA |
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| Platforms (2) |
| GPL17342 |
Illumina HiSeq 2500 (Saccharomyces cerevisiae) |
| GPL28108 |
Illumina HiSeq 2500 (Saccharomyces bayanus; Saccharomyces cerevisiae) |
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| Samples (5)
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| Relations |
| BioProject |
PRJNA604244 |
| SRA |
SRP246374 |
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