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Massively Parallel Profiling of Single-Cell RNA Dynamics Using Well-TEMP-seq.

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Τίτλος: Massively Parallel Profiling of Single-Cell RNA Dynamics Using Well-TEMP-seq.
Συγγραφείς: Wang D; MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, Fujian Key Laboratory of Chemical Biology, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, China.; These authors contributed equally to this work., Lv Q; School of Life Sciences, Xiamen University, Xiamen, China.; These authors contributed equally to this work., Lin S; MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, Fujian Key Laboratory of Chemical Biology, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, China.
Πηγή: Current protocols [Curr Protoc] 2026 Sep; Vol. 6 (9), pp. e70458.
Τύπος έκδοσης: Journal Article
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: John Wiley & Sons Country of Publication: United States NLM ID: 101773894 Publication Model: Print Cited Medium: Internet ISSN: 2691-1299 (Electronic) Linking ISSN: 26911299 NLM ISO Abbreviation: Curr Protoc Subsets: MEDLINE
Imprint Name(s): Original Publication: Hoboken, NJ : John Wiley & Sons, [2021]-
Ιατρικοί όροι (MeSH): Single-Cell Analysis*/methods , Sequence Analysis, RNA*/methods , RNA*/genetics , High-Throughput Nucleotide Sequencing*/methods , Gene Expression Profiling*/methods, Single-Cell Gene Expression Analysis ; Animals ; Humans
Περίληψη: Single-cell RNA sequencing (scRNA-seq) reveals the transcriptional heterogeneity of cells, revolutionizing our understanding of cellular processes. However, the static snapshots obtained from scRNA-seq fail to reveal the time-resolved dynamics of transcription, which impedes critical insights into various biological processes, such as cellular differentiation, embryonic development, disease progression, and responses to external stimuli. Here, we describe Well-TEMP-seq, a protocol for massively parallel profiling of the temporal dynamics of single-cell gene expression. Well-TEMP-seq combines metabolic RNA labeling with a microwell-based 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. Well-TEMP-seq is high-throughput, cost-effective, accurate, and provides a low cell loss rate and high single cell/bead pairing efficiency. More importantly, Well-TEMP-seq can be easily set up in other labs, and the loading of cells and beads can be easily accomplished by an optical microscope and a pipette. We believe that Well-TEMP-seq will be widely adopted and help researchers perform transformative research to unveil the dynamics of single-cell gene expression in diverse biological processes. © 2026 Wiley Periodicals LLC. Basic Protocol 1: Well-paired-seq chip fabrication Basic Protocol 2: Well-TEMP-seq sample processing Basic Protocol 3: Bioinformatics analysis.
(© 2026 Wiley Periodicals LLC.)
References: Nature. 2008 Mar 27;452(7186):423-8. (PMID: 18344981)
Nat Methods. 2020 Oct;17(10):991-1001. (PMID: 32868927)
Nat Rev Genet. 2011 Nov 03;12(12):833-45. (PMID: 22048664)
Dev Cell. 2004 Jan;6(1):117-31. (PMID: 14723852)
Nature. 2019 Jul;571(7765):419-423. (PMID: 31292545)
Small Methods. 2021 Jun;5(6):e2100111. (PMID: 34927917)
Lab Chip. 2021 Oct 12;21(20):3829-3849. (PMID: 34541590)
Nat Commun. 2023 Mar 7;14(1):1272. (PMID: 36882403)
Science. 2020 Mar 6;367(6482):1151-1156. (PMID: 32139547)
Small Methods. 2022 Jul;6(7):e2200341. (PMID: 35521945)
Curr Protoc. 2026 Sep;6(9):e70458. (PMID: 42671929)
Nat Biotechnol. 2020 Aug;38(8):980-988. (PMID: 32284584)
Nature. 2002 Jul 18;418(6895):293-300. (PMID: 12124616)
Nat Commun. 2019 Jul 17;10(1):3138. (PMID: 31316066)
Development. 2008 Mar;135(5):909-18. (PMID: 18263842)
Grant Information: 2025J09060 Natural Science Foundation of Fujian Province of China
Contributed Indexing: Keywords: 4‐thiouridine; gene expression dynamics; metabolic RNA labeling; microwell; single‐cell RNA sequencing
Substance Nomenclature: 63231-63-0 (RNA)
Entry Date(s): Date Created: 20260831 Date Completed: 20260831 Latest Revision: 20260902
Update Code: 20260902
PubMed Central ID: PMC13528962
DOI: 10.1002/cpz1.70458
PMID: 42671929
Βάση Δεδομένων: MEDLINE
FullText Text:
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  Data: Massively Parallel Profiling of Single-Cell RNA Dynamics Using Well-TEMP-seq.
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  Data: <searchLink fieldCode="AU" term="%22Wang+D%22">Wang D</searchLink>; MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, Fujian Key Laboratory of Chemical Biology, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, China.; These authors contributed equally to this work.<br /><searchLink fieldCode="AU" term="%22Lv+Q%22">Lv Q</searchLink>; School of Life Sciences, Xiamen University, Xiamen, China.; These authors contributed equally to this work.<br /><searchLink fieldCode="AU" term="%22Lin+S%22">Lin S</searchLink>; MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, Fujian Key Laboratory of Chemical Biology, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, China.
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  Data: Single-cell RNA sequencing (scRNA-seq) reveals the transcriptional heterogeneity of cells, revolutionizing our understanding of cellular processes. However, the static snapshots obtained from scRNA-seq fail to reveal the time-resolved dynamics of transcription, which impedes critical insights into various biological processes, such as cellular differentiation, embryonic development, disease progression, and responses to external stimuli. Here, we describe Well-TEMP-seq, a protocol for massively parallel profiling of the temporal dynamics of single-cell gene expression. Well-TEMP-seq combines metabolic RNA labeling with a microwell-based 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. Well-TEMP-seq is high-throughput, cost-effective, accurate, and provides a low cell loss rate and high single cell/bead pairing efficiency. More importantly, Well-TEMP-seq can be easily set up in other labs, and the loading of cells and beads can be easily accomplished by an optical microscope and a pipette. We believe that Well-TEMP-seq will be widely adopted and help researchers perform transformative research to unveil the dynamics of single-cell gene expression in diverse biological processes. © 2026 Wiley Periodicals LLC. Basic Protocol 1: Well-paired-seq chip fabrication Basic Protocol 2: Well-TEMP-seq sample processing Basic Protocol 3: Bioinformatics analysis.<br /> (© 2026 Wiley Periodicals LLC.)
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  Data: Nature. 2008 Mar 27;452(7186):423-8. (PMID: <searchLink fieldCode="PM" term="%2218344981%22">18344981)</searchLink><br />Nat Methods. 2020 Oct;17(10):991-1001. (PMID: <searchLink fieldCode="PM" term="%2232868927%22">32868927)</searchLink><br />Nat Rev Genet. 2011 Nov 03;12(12):833-45. (PMID: <searchLink fieldCode="PM" term="%2222048664%22">22048664)</searchLink><br />Dev Cell. 2004 Jan;6(1):117-31. (PMID: <searchLink fieldCode="PM" term="%2214723852%22">14723852)</searchLink><br />Nature. 2019 Jul;571(7765):419-423. (PMID: <searchLink fieldCode="PM" term="%2231292545%22">31292545)</searchLink><br />Small Methods. 2021 Jun;5(6):e2100111. (PMID: <searchLink fieldCode="PM" term="%2234927917%22">34927917)</searchLink><br />Lab Chip. 2021 Oct 12;21(20):3829-3849. (PMID: <searchLink fieldCode="PM" term="%2234541590%22">34541590)</searchLink><br />Nat Commun. 2023 Mar 7;14(1):1272. (PMID: <searchLink fieldCode="PM" term="%2236882403%22">36882403)</searchLink><br />Science. 2020 Mar 6;367(6482):1151-1156. (PMID: <searchLink fieldCode="PM" term="%2232139547%22">32139547)</searchLink><br />Small Methods. 2022 Jul;6(7):e2200341. (PMID: <searchLink fieldCode="PM" term="%2235521945%22">35521945)</searchLink><br />Curr Protoc. 2026 Sep;6(9):e70458. (PMID: <searchLink fieldCode="PM" term="%2242671929%22">42671929)</searchLink><br />Nat Biotechnol. 2020 Aug;38(8):980-988. (PMID: <searchLink fieldCode="PM" term="%2232284584%22">32284584)</searchLink><br />Nature. 2002 Jul 18;418(6895):293-300. (PMID: <searchLink fieldCode="PM" term="%2212124616%22">12124616)</searchLink><br />Nat Commun. 2019 Jul 17;10(1):3138. (PMID: <searchLink fieldCode="PM" term="%2231316066%22">31316066)</searchLink><br />Development. 2008 Mar;135(5):909-18. (PMID: <searchLink fieldCode="PM" term="%2218263842%22">18263842)</searchLink>
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