Distinguished Speaker Series: Estimation of mRNA transcription and decay rates using single-cell RNA sequencing
Prof. David Gresham, Faculty Director of Bioinformatics, Center of Genomics & Systems Biology, New York University
Edmond J. Safra Center for Bioinformatics
School of Zoology
DISTINGUISHED SPEAKER SERIES SEMINAR
Prof. David Gresham
Faculty Director of Bioinformatics, Center of Genomics & Systems Biology, New York University
"Estimation of mRNA transcription and decay rates using single-cell RNA sequencing"
Thursday, March 30 2023, at 15:00
(Refreshments from 14:50)
Sherman building, Hall 002, Life Sciences, TAU
Abstract: Cells respond to environmental and developmental stimuli by regulated changes in the rate of mRNA transcription and decay. Determining transcription and mRNA decay rates typically requires metabolic labeling (e.g. 4-thiouracil) to distinguish extant and nascent RNA. Here, we developed an approach to simultaneous estimation of per gene transcription and decay parameters by quantifying the transcriptome of individual yeast (Saccharomyces cerevisiae) cells using single cell RNA sequencing (scRNAseq). Using a continuous-sampling experimental design over an 80 minute period, we measured expression of 180,000 individual cells using scRNAseq prior to, and in response to, rapamycin treatment. Each cell was then assigned a position in temporal space representing both position in the cell cycle and response to rapamycin. Using the temporally ordered gene expression states we estimate the rates of change for each transcript on a per-cell basis within the local time neighborhood resulting in an estimate of RNA velocity. Estimates of RNA velocity were then used to compute transcriptional and mRNA decay rates, and their variation, as a function of time. Our estimates of mRNA decay rates are in good agreement with estimates using metabolic labeling. We identify several classes of transcripts for which transcription and mRNA decay rates change during progression of the cell cycle and in response to rapamycin treatment. Our results point to highly dynamic regulation of mRNA transcription and decay rates throughout the cell cycle and in response to environmental stimuli. Finally, we use the dynamic parameters as components of a model to learn the dynamic, organism-scale gene regulatory network that controls yeast gene expression during the cell cycle and in response to stress.
Host: Dr. Yoav Ram, School of Zoology, Faculty of Life Sciences, TAU