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Related Experiment Video

Updated: Dec 1, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

Integrating single-cell RNA-seq and imaging with SCOPE-seq2.

Zhouzerui Liu¹, Jinzhou Yuan¹, Anna Lasorella^2,3,4

¹Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, 10032, USA.

Scientific Reports

|November 11, 2020

Summary

This summary is machine-generated.

We present SCOPE-seq2, an enhanced method for linking live cell imaging with single-cell RNA sequencing. This scalable technique improves throughput and accuracy for analyzing cellular phenotypes and gene expression, particularly in complex samples like glioblastoma.

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Last Updated: Dec 1, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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Published on: January 10, 2019

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

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Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

Area of Science:

Biotechnology
Genomics
Cell Biology

Background:

Live cell imaging offers direct phenotypic insights not easily captured by transcriptomics alone.
Current methods for integrating microscopy with single-cell RNA sequencing (scRNA-seq) face scalability limitations.

Purpose of the Study:

To introduce an upgraded, scalable method (SCOPE-seq2) for combining single-cell imaging and gene expression profiling.
To enhance throughput, molecular capture efficiency, and linking accuracy in multi-modal single-cell analysis.

Main Methods:

Development of improved optically decodable mRNA capture beads.
Implementation of a streamlined and scalable optical decoding process.
Application of SCOPE-seq2 to primary human glioblastoma cells for multi-modal profiling.

Main Results:

SCOPE-seq2 demonstrates substantial improvements in throughput, capture efficiency, and linking accuracy.
The method successfully profiles fluorescence, morphology, and gene expression in individual glioblastoma cells.
Analysis revealed correlations between imaging features and cellular identity within the tumor sample.

Conclusions:

SCOPE-seq2 provides a scalable and accurate platform for integrating live cell imaging with scRNA-seq.
This technology enables deeper understanding of cellular phenotypes and their relationship to gene expression.
The findings highlight the utility of SCOPE-seq2 for dissecting cellular heterogeneity in complex diseases like glioblastoma.