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Related Experiment Video

Updated: Dec 14, 2025

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq
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Parallel bimodal single-cell sequencing of transcriptome and chromatin accessibility.

Qiao Rui Xing1,2, Chadi A El Farran1,3, Ying Ying Zeng1,2

  • 1Epigenetics and Cell Fates Laboratory, Institute of Molecular and Cell Biology, A*STAR, Singapore 138673, Singapore.

Genome Research
|July 24, 2020
PubMed
Summary

We developed ASTAR-seq, a sensitive method for single-cell transcriptome and chromatin accessibility profiling. This technique reveals regulatory networks and gene-element links across diverse cell states.

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Area of Science:

  • Single-cell multi-omics
  • Epigenetics
  • Gene regulation

Background:

  • Understanding cell fate requires joint analysis of gene expression and chromatin accessibility.
  • Existing methods face limitations in simultaneous profiling within individual cells.

Purpose of the Study:

  • To develop and validate ASTAR-seq, a sensitive, automated assay for simultaneous single-cell transcriptome and chromatin accessibility measurement.
  • To apply ASTAR-seq to diverse cell types and states to explore regulatory landscapes.

Main Methods:

  • Developed ASTAR-seq, an automated assay for joint profiling.
  • Applied ASTAR-seq to mouse embryonic stem cells (mESCs), human cell lines, and primary cord blood cells.
  • Analyzed transcriptional and chromatin accessibility data to identify cell-state-specific regulatory elements and networks.

Main Results:

  • ASTAR-seq successfully profiled transcriptome and chromatin accessibility in single cells across various biological contexts.
  • Identified unique cis-regulatory elements and target genes linked to specific cell states.
  • Constructed transcription factor-centered regulatory networks and interactomes for different cell populations.

Conclusions:

  • ASTAR-seq provides a powerful tool for dissecting gene regulation and cell fate determination at the single-cell level.
  • The method enables comprehensive mapping of transcriptional and epigenetic landscapes, advancing our understanding of cellular heterogeneity.