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High-Resolution Sequencing and Modeling Identifies Distinct Dynamic RNA Regulatory Strategies
Open accessAbstract
Cells control dynamic transitions in transcript levels by regulating transcription, processing, and/or degradation through an integrated regulatory strategy. Here, we combine RNA metabolic labeling, rRNA-depleted RNA-seq, and DRiLL, a novel computational framework, to quantify the level; editing sites; and transcription, processing, and degradation rates of each transcript at a splice junction resolution during the LPS response of mouse dendritic cells. Four key regulatory strategies, dominated by RNA transcription changes, generate most temporal gene expression patterns. Noncanonical strategies that also employ dynamic posttranscriptional regulation control only a minority of genes, but provide unique signal processing features. We validate Tristetraprolin (TTP) as a major regulator of RNA degradation in one noncanonical strategy. Applying DRiLL to the regulation of noncoding RNAs and to zebrafish embryogenesis demonstrates its broad utility. Our study provides a new quantitative approach to discover transcriptional and posttranscriptional events that control dynamic changes in transcript levels using RNA sequencing data.
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“Rapid changes in microglial signature gene expression is consistent with rates reported for global mRNA turnover in macrophage-like dendritic cells stimulated with LPS (Rabani et al., 2014).”
From Diverse Requirements for Microglial Survival, Specification, and Function Revealed by Defined-Medium Cultures (2017) · cites this paper as Rabani et al., 2014
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“While our study does not directly address which steps in mRNA regulation account for this, our related work on the RNA life cycle during the first 3 hours in LPS stimulated DCs suggests that transcriptional changes may in turn dominate differential mRNA expression, whereas dynamic changes in RNA processing or degradation affect only a minority of genes, albeit with important functions (46).”
From Dynamic profiling of the protein life cycle in response to pathogens (2015) · cites this paper as [46]
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“These methods hold promise for elucidating the epigenetic controls of cellular identity186,187.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [186]
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“reflecting the enrichment of nascent transcripts in the nucleus3,13–16”
From Massively parallel single-nucleus RNA-seq with DroNc-seq (2017) · cites this paper as [14]
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Metadata
- Authors
- Rabani, M., Raychowdhury, R., Jovanovic, M., Rooney, M., Stumpo, D. J., Pauli, A., Hacohen, N., Schier, A. F., Blackshear, P. J., Friedman, N., Amit, I., & Regev, A.
- Affiliations
- Broad Institute (US)
- National Institutes of Health (US)
- Harvard University (US)
- Hebrew University of Jerusalem (IL)
- Weizmann Institute of Science (IL)
- Corresponding author
- Regev, Aviv
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2014-12
- Volume
- 159
- Issue
- 7
- Pages
- 1698-1710
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC4272607
- OpenAlex
- W1972255859
- Cited by
- 226
- References
- 53
- Citations by year
- 2026: 9 · 2025: 13 · 2024: 14 · 2023: 19 · 2022: 30 · 2021: 23 · 2020: 19 · 2019: 19 · 2018: 21 · 2017: 25 · 2016: 21 · 2015: 12 · 2014: 1
- FWCI
- 8.07
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-nd)
- edoc (University of Basel) (submittedVersion)
- PMC
- Funders
- Howard Hughes Medical Institute
- National Institutes of Health (DP1OD003958)
- National Human Genome Research Institute (P50HG006193)
- National Cancer Institute (DP1CA174427)
- National Institute of General Medical Sciences (R01GM056211)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (K99HD076935)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- RNA metabolism, post-transcriptional regulation, RNA degradation, RNA editing, transcription rate, RNA processing, lipopolysaccharide response, dendritic cells, drills, tristetraprolin, non-coding RNA regulation, zebrafish embryonic development, transcriptome dynamics
- MeSH terms
- Animals, Computer Simulation, Dendritic Cells, Kinetics, Lipopolysaccharides, RNA Processing, Post-Transcriptional, Transcription, Genetic, Zebrafish, Sequence Analysis, RNA, Gene Expression Profiling, RNA Stability, RNA, Untranslated, Mice, Tristetraprolin
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