Production and Degradation Rate Papers
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After reviewing the data from this past year, it was found that production rates hold great significance in estimating GRNs. Trials with the initial toy network where P's were held constant gave much more accurate results than those where B's were held constant or no variables were held constant. Currently, these rates are based on the [2014 Neymotin paper], but since this paper is now 7 years old, we wanted to investigate if there were more updated methods for calculating or measuring production and degradation rates.
Potential papers of interest:
- Global SLAM-seq for accurate mRNA decay determination and identification of NMD targets
- Alalam, H., Zepeda-Martínez, J. A., & Sunnerhagen, P. (2022). Global SLAM-seq for accurate mRNA decay determination and identification of NMD targets. RNA, 28(6), 905-915.
- https://rnajournal-cshlp-org.electra.lmu.edu/content/28/6/905.full
- Saccharomyces cerevisiae Metabolic Labeling with 4-thiouracil and the Quantification of Newly Synthesized mRNA As a Proxy for RNA Polymerase II Activity
- Baptista, T., & Devys, D. (2018). Saccharomyces cerevisiae Metabolic Labeling with 4-thiouracil and the Quantification of Newly Synthesized mRNA As a Proxy for RNA Polymerase II Activity. JoVE, 140, e57982. https://doi.org/10.3791/57982
- https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6235584/
- Mechanisms of cellular mRNA transcript homeostasis
- Berry, S., & Pelkmans, L. (2022). Mechanisms of cellular mRNA transcript homeostasis. Trends in Cell Biology, 32(8), 655–668. https://doi.org/10.1016/j.tcb.2022.05.003
- https://www.sciencedirect.com/science/article/pii/S0962892422001209?casa_token=LvFWB4nxBVIAAAAA:YNrJ1qId-J136-jZLZh9td23xmD-yr5l9MIZs1EVMiwC6Q-oFDq9uc9W6N9P-WBQgH-P4qMQhDQ#bb0460
- Non-invasive measurement of mRNA decay reveals translation initiation as the major determinant of mRNA stability
- Chan, L. Y., Mugler, C. F., Heinrich, S., Vallotton, P., & Weis, K. (2018). Non-invasive measurement of mRNA decay reveals translation initiation as the major determinant of mRNA stability. eLife, 7, e32536. https://doi.org/10.7554/eLife.32536
- https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6152797/
- A Trans-Omics Comparison Reveals Common Gene Expression Strategies in Four Model Organisms and Exposes Similarities and Differences between Them
- Forés-Martos, J., Forte, A., García-Martínez, J., & Pérez-Ortín, J. E. (2021). A Trans-Omics Comparison Reveals Common Gene Expression Strategies in Four Model Organisms and Exposes Similarities and Differences between Them. Cells, 10(2), 334. https://doi.org/10.3390/cells10020334
- https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7914595/
- Estimating RNA dynamics using one time point for one sample in a single-pulse metabolic labeling experiment
- Hersch, M., Biasini, A., Marques, A. C., & Bergmann, S. (2022). Estimating RNA dynamics using one time point for one sample in a single-pulse metabolic labeling experiment. BMC Bioinformatics, 23(1), 147. https://doi.org/10.1186/s12859-022-04672-4
- https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-022-04672-4#citeas
- Stochastic system identification without an a priori chosen kinetic model-exploring feasible cell regulation with piecewise linear functions
- Hoffmann, M., & Galle, J. (2018). Stochastic system identification without an a priori chosen kinetic model-exploring feasible cell regulation with piecewise linear functions. NPJ systems biology and applications, 4, 15. https://doi.org/10.1038/s41540-018-0049-0
- https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5895840/
- Measuring mRNA Decay in Budding Yeast Using Single Molecule FISH
- Trcek, T., Rahman, S., & Zenklusen, D. (2018). Measuring mRNA Decay in Budding Yeast Using Single Molecule FISH. Methods in molecular biology (Clifton, N.J.), 1720, 35–54. https://doi.org/10.1007/978-1-4939-7540-2_4
- https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10773531/
Notes/questions:
- General
- Most papers address 4tU metabolic labeling as a method for determining degradation rate so this seems to be the current standard for this method
- Will continue to look for papers addressing production rates because they seem to be less common
- 1st and 4th paper seem to be most helpful
- Complex Degradation Processes Lead to Non-Exponential Decay Patterns and Age-Dependent Decay Rates of Messenger RNA addresses decay rates -> decay rate and half-life are mathematically related
- If production rate and synthesis rate are the same, the following papers may be useful
- Inference of gene regulation functions from dynamic transcriptome data
- Comparative dynamic transcriptome analysis (cDTA) reveals mutual feedback between mRNA synthesis and degradation -> reports both median mRNA half-life and median mRNA synthesis rate
- Global SLAM-seq for accurate mRNA decay determination and identification of NMD targets
- Method for global quantification of mRNA half-lives
- Figure out specifically what global means in this context
- Median half-life of 9.4 min for 67.5 open reading frames
- 4tU labeling like other papers
- Only addresses degradation, not production
- https://rnajournal-cshlp-org.electra.lmu.edu/content/28/6/905/F2.large.jpg -> this figure compares the half-life data from this paper to that of the Neymotin paper which is probably significant, but I am not sure that I know exactly what this figure is describing
- What is mRNA turnover?
- Method for global quantification of mRNA half-lives
- Saccharomyces cerevisiae Metabolic Labeling with 4-thiouracil and the Quantification of Newly Synthesized mRNA As a Proxy for RNA Polymerase II Activity
- May be helpful for production rates - "genome-wide quantification of mRNA synthesis, independently from mRNA decay, is the best direct reflection of RNA polymerase II transcriptional activity"
- Is the quantification of mRNA synthesis the same as production rates
- Also uses 4tU metabolic labeling
- Gives a detailed protocol for their methods
- Because of the focus on RNA polymerase activity, I don't think the results are particularly helpful
- Maybe I missed it, but I wasn't able to find data about production/synthesis rates specifically
- May be helpful for production rates - "genome-wide quantification of mRNA synthesis, independently from mRNA decay, is the best direct reflection of RNA polymerase II transcriptional activity"
- Mechanisms of cellular mRNA transcript homeostasis
- Discusses production and degradation rates for yeast
- I don't know if this paper will be helpful, however, because it discusses both of these factors in terms of how they relate to cell size and do not give the data outright but rather report how degradation and production rate trend dependent on cell size
- Interestingly, focused more on production rates because it stated that degradation rates are more difficult to measure
- This is not super significant, but I thought it was an interesting comment because it seems to contradict other findings
- Non-invasive measurement of mRNA decay reveals translation initiation as the major determinant of mRNA stability
- 4tU metabolic labeling to measure rates of transcription and decay
- Other papers also used this method -> it's less invasive and unlike previous methods, it won't affect organism physiology
- Found that mRNA has average half-life of 4.8 min and a median half-life of 3.6 min
- Different from what other papers said - maybe different reading frames or something else but it is a large discrepancy
- Bulk transcriptome has a half-life of ~13.1
- I don't know if this data is also helpful/also is this what they are talking about when they address global data?
- 4tU metabolic labeling to measure rates of transcription and decay
- A Trans-Omics Comparison Reveals Common Gene Expression Strategies in Four Model Organisms and Exposes Similarities and Differences between Them
- I thought this one might be helpful because it might be able to relate the data between papers that use organisms other than yeast to yeast data, but they used the Neymotin paper for yeast data so I don't think that it's that helpful
- Estimating RNA dynamics using one time point for one sample in a single-pulse metabolic labeling experiment
- Method performed on mouse embryonic stem cells so not completely relevant, but if applied to yeast I think this paper would be especially helpful
- Stochastic system identification without an a priori chosen kinetic model-exploring feasible cell regulation with piecewise linear functions
- Helpful discussion about calculation of production and degradation rate, but don't have the specific data that we can use
- Measuring mRNA Decay in Budding Yeast Using Single Molecule FISH
- gives method for quantifying mRNA decay rates but does not address production rates