ArticleNature biotechnology2020
Sci-fate characterizes the dynamics of gene expression in single cells.
Article in Nature biotechnology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 95 papers, 1 of them a synthesis that pooled it.
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Who cites it
95 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The genetic and biochemical determinants of mRNA degradation rates in mammals.Genome biology · 2022Pooled it
- Computational approaches for multimodal lineage tracing.Nature reviews. Genetics · 2026Review
- Massively Parallel Profiling of Single-Cell RNA Dynamics Using Well-TEMP-seq.Current protocols · 2026Article
- Spatial mapping of RNA turnover kinetics in the mouse brain.Nature neuroscience · 2026Article
- Using the simple telegraph model to decipher transcriptional burst regulation across genome-wide data.iScience · 2026Article
- CellRank: consistent and data view agnostic fate mapping for single-cell genomics.Nature protocols · 2026Review
- Dynamic Landscape Analysis of cell fate decisions provides predictive models of neural development from single-cell data.PLoS biology · 2026Article
- In vivo single-cell RNA metabolic labeling resolves early transcriptional responders in the regenerating zebrafish heart.Nature communications · 2026Article
- Benchmarking RNA velocity methods across 17 independent studies.Cell reports methods · 2026Article
- Spatially resolved in situ profiling of mRNA life cycle at transcriptome scale in intact cells and tissues using STARmap PLUS, RIBOmap and TEMPOmap.Nature protocols · 2026Review
- Transcript-guided targeted cell enrichment for scalable single-nucleus RNA sequencing.Cell genomics · 2026Article
- stVCR: spatiotemporal dynamics of single cells.Nature methods · 2026Article
- Spatial mapping of RNA turnover kinetics and regulatory landscapes of mRNA stability in the mammalian brain.bioRxiv : the preprint server for biology · 2026Article
- A convenient single-cell assay for the newly synthesized transcriptome reveals FLI1 regulon downregulation during T cell activation.Cell reports methods · 2026Article
- Metal Ions Within the Neuro-Immune-Tumor Axis.Journal of immunology research · 2026Review
- Fundamental errors in RNA velocity arising from the omission of cell growth.bioRxiv : the preprint server for biology · 2025Article
- JNK activation dynamics drive distinct gene expression patterns over time mediated by mRNA stability.NPJ systems biology and applications · 2025Article
- scIVNL-seq resolves in vivo single-cell RNA dynamics of immune cells during Salmonella infection.Nature communications · 2025Article
- GraphVelo allows for accurate inference of multimodal velocities and molecular mechanisms for single cells.Nature communications · 2025Article
- Deciphering direct transcriptional effects of epigenetic compounds through large-scale new RNA profiling.Nature communications · 2025Article
35 more citing papers are in PubMed but not listed here.
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5 authors.
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Abstract
Gene expression programs change over time, differentiation and development, and in response to stimuli. However, nearly all techniques for profiling gene expression in single cells do not directly capture transcriptional dynamics. In the present study, we present a method for combined single-cell combinatorial indexing and messenger RNA labeling (sci-fate), which uses combinatorial cell indexing and 4-thiouridine labeling of newly synthesized mRNA to concurrently profile the whole and newly synthesized transcriptome in each of many single cells. We used sci-fate to study the cortisol response in >6,000 single cultured cells. From these data, we quantified the dynamics of the cell cycle and glucocorticoid receptor activation, and explored their intersection. Finally, we developed software to infer and analyze cell-state transitions. We anticipate that sci-fate will be broadly applicable to quantitatively characterize transcriptional dynamics in diverse systems.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.