Abstract
The serial nature of reactions involved in the RNA life-cycle motivates the incorporation of delays in models of transcriptional dynamics. The models couple a transcriptional process to a fairly general set of delayed monomolecular reactions with no feedback. We provide numerical strategies for calculating the RNA copy number distributions induced by these models, and solve several systems with splicing, degradation, and catalysis. An analysis of single-cell and single-nucleus RNA sequencing data using these models reveals that the kinetics of nuclear export do not appear to require invocation of a non-Markovian waiting time.
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Data availability
All scripts used to process data and generate the figures are located at https://github.com/pachterlab/GYP_2022. This GitHub repository also contains the MATLAB scripts used to generate the functions reported in Sections S1.5.1 and S1.7. The raw count matrices, as well as the intermediate results of the workflow, are available on Zenodo as package 8122410.
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Acknowledgements
G.G. thanks Dr. John J. Vastola and Catherine Felce for valuable discussions. The MCMC inference procedure was based on the algorithm developed by Dr. John J. Vastola and Meichen Fang (Gorin et al. 2022). G.G. and L.P. were partially funded by the National Institutes of Health Grants U19MH114830 and 5UM1HG012077-02. S.Y. was supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1745301. A part of the reported results were obtained during a Data Sciences Co-op with Celsius Therapeutics, Inc. The DNA and RNA illustrations are derived from the DNA Twemoji by Twitter, Inc., used under CC-BY 4.0.
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Gorin, G., Yoshida, S. & Pachter, L. Assessing Markovian and Delay Models for Single-Nucleus RNA Sequencing. Bull Math Biol 85, 114 (2023). https://doi.org/10.1007/s11538-023-01213-9
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DOI: https://doi.org/10.1007/s11538-023-01213-9