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Cell Specific Gene Expression

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Related Experiment Video

Updated: Jun 4, 2025

Transcriptome Analysis of Single Cells

Transcriptome Analysis of Single Cells

Published on: April 25, 2011

Transcriptome and Temporal Transcriptome Analyses in Single Cells.

Jun Lyu¹, Chongyi Chen¹

¹Laboratory of Biochemistry and Molecular Biology, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.

International Journal of Molecular Sciences

|December 17, 2024

Summary

This summary is machine-generated.

Single-cell RNA sequencing (scRNA-seq) advancements improve gene expression analysis. New methods integrate RNA metabolic labeling for temporal transcriptome profiling, revealing dynamic biological processes and cell fate.

Keywords:

RNA metabolic labeling newly synthesized RNA detection single-cell temporal transcriptome analysis single-cell transcriptome analysis

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Last Updated: Jun 4, 2025

Transcriptome Analysis of Single Cells

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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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Published on: March 7, 2018

Area of Science:

Biotechnology
Molecular Biology
Genomics

Background:

Single-cell RNA sequencing (scRNA-seq) is crucial for biomedical research, enabling gene regulation and tissue organization studies.
Recent technological improvements have significantly enhanced scRNA-seq performance, including chemistry and methodology.
RNA metabolic labeling integrated with scRNA-seq allows temporal transcriptome profiling.

Purpose of the Study:

To review chemical principles and design improvements enhancing single-cell transcriptome analysis.
To illustrate RNA metabolic labeling for detecting newly synthesized transcripts.
To summarize advancements in single-cell temporal transcriptome analysis.

Main Methods:

Review of chemical principles and design improvements in scRNA-seq.
Illustration of RNA metabolic labeling techniques.
Summary of recent advancements in temporal transcriptome analysis.

Main Results:

Enhanced single-molecule capture efficiency and RNA quantification accuracy.
Increased cellular throughput in single-cell transcriptome analysis.
Development of strategies for precise quantification of newly synthesized transcripts.

Conclusions:

Single-cell temporal transcriptome analysis provides novel insights into RNA kinetics and cell fate.
Key applications in transcriptome and temporal transcriptome analyses are highlighted.
Continued advancements promise deeper understanding of dynamic biological processes.