ArticleNature communications2023
Well-TEMP-seq as a microwell-based strategy for massively parallel profiling of single-cell temporal RNA dynamics.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 49 citations in OpenAlex.
- Massively Parallel Profiling of Single-Cell RNA Dynamics Using Well-TEMP-seq.Current protocols · 2026Article
- stVCR: spatiotemporal dynamics of single cells.Nature methods · 2026Article
- A convenient single-cell assay for the newly synthesized transcriptome reveals FLI1 regulon downregulation during T cell activation.Cell reports methods · 2026Article
- High-Resolution Multiplexed Sequencing of Single-Cell Full-length Transcriptome Via Combinational Barcoded Tn5 Transposon Insertion.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Expanding and improving analyses of nucleotide recoding RNA-seq experiments with the EZbakR suite.PLoS computational biology · 2025Article
- Recent advances in biomarker detection of oral squamous cell carcinoma.Frontiers in oncology · 2025Review
- Transcriptome and Temporal Transcriptome Analyses in Single Cells.International journal of molecular sciences · 2024Review
- Dyna-vivo-seq unveils cellular RNA dynamics during acute kidney injury via in vivo metabolic RNA labeling-based scRNA-seq.Nature communications · 2024Article
- Storm: Incorporating transient stochastic dynamics to infer the RNA velocity with metabolic labeling information.PLoS computational biology · 2024Article
- Single-cell sequencing to multi-omics: technologies and applications.Biomarker research · 2024Review
- Identifying cell types by lasso-constraint regularized Gaussian graphical model based on weighted distance penalty.Briefings in bioinformatics · 2024Article
- Advance and Application of Single-cell Transcriptomics in Auditory Research.Neuroscience bulletin · 2024Review
- CellRank 2: unified fate mapping in multiview single-cell data.Nature methods · 2024Article
- Microfluidic Biochips for Single-Cell Isolation and Single-Cell Analysis of Multiomics and Exosomes.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Review
- Next-Generation Sequencing-Based Spatial Transcriptomics: A Perspective from Barcoding Chemistry.JACS Au · 2024Review
- A dynamical perspective: moving towards mechanism in single-cell transcriptomics.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Review
- Powerful and accurate detection of temporal gene expression patterns from multi-sample multi-stage single-cell transcriptomics data with TDEseq.Genome biology · 2024Article
- Beyond single cells: microfluidics empowering multiomics analysis.Analytical and bioanalytical chemistry · 2024Review
- Recent advancements in single-cell metabolic analysis for pharmacological research.Journal of pharmaceutical analysis · 2023Review
- Microfluidic design in single-cell sequencing and application to cancer precision medicine.Cell reports methods · 2023Review
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single-cell RNA sequencing (scRNA-seq) reveals the transcriptional heterogeneity of cells, but the static snapshots fail to reveal the time-resolved dynamics of transcription. Herein, we develop Well-TEMP-seq, a high-throughput, cost-effective, accurate, and efficient method for massively parallel profiling the temporal dynamics of single-cell gene expression. Well-TEMP-seq combines metabolic RNA labeling with scRNA-seq method Well-paired-seq to distinguish newly transcribed RNAs marked by T-to-C substitutions from pre-existing RNAs in each of thousands of single cells. The Well-paired-seq chip ensures a high single cell/barcoded bead pairing rate (~80%) and the improved alkylation chemistry on beads greatly alleviates chemical conversion-induced cell loss (~67.5% recovery). We further apply Well-TEMP-seq to profile the transcriptional dynamics of colorectal cancer cells exposed to 5-AZA-CdR, a DNA-demethylating drug. Well-TEMP-seq unbiasedly captures the RNA dynamics and outperforms the splicing-based RNA velocity method. We anticipate that Well-TEMP-seq will be broadly applicable to unveil the dynamics of single-cell gene expression in diverse biological processes.
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Registered trials
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.