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RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

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Updated: Sep 10, 2025

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

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

Published on: May 23, 2018

Stereo-cell: Spatial enhanced-resolution single-cell sequencing with high-density DNA nanoball-patterned arrays.

Sha Liao^1,2,3, Xiaoxi Zhou¹, Chuanyu Liu^1,4,5,6,7

¹State Key Laboratory of Genome and Multi-omics Technologies, BGI Research, Shenzhen, China.

Science (New York, N.Y.)

|August 21, 2025

Summary

This summary is machine-generated.

Stereo-cell is a new single-cell sequencing platform that overcomes limitations of existing methods. This technology offers scalable, unbiased cell capture and high-fidelity transcriptome profiling for broader single-cell research applications.

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Last Updated: Sep 10, 2025

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Area of Science:

Genomics
Molecular Biology
Biotechnology

Background:

Single-cell sequencing advances cellular heterogeneity studies but faces limitations in throughput, uniformity, cell size flexibility, and extensibility.
Existing platforms struggle to balance scalability with high-fidelity transcriptome profiling and multi-modal integration.

Purpose of the Study:

Introduce Stereo-cell, a novel spatial enhanced-resolution single-cell sequencing platform.
Address limitations in current single-cell technologies regarding scalability, unbiased capture, and multi-modal integration.
Expand the applications of single-cell research through a flexible and high-performance platform.

Main Methods:

Utilizes high-density DNA nanoball (DNB)-patterned arrays for enhanced spatial resolution and cell capture.
Enables scalable and unbiased cell capture across a wide input range.
Integrates with imaging-based modalities and multiomics strategies (e.g., immunofluorescence, epitope profiling).

Main Results:

Achieves high-fidelity transcriptome profiling with scalable and unbiased cell capture.
Demonstrates compatibility with profiling extracellular vesicles, microstructures, and large cells.
Facilitates in situ analysis of cell-cell interactions, cellular microenvironments, and subcellular transcript localization.

Conclusions:

Stereo-cell provides a flexible and extensible framework for advancing single-cell research.
The platform overcomes throughput, uniformity, and cell size limitations of existing methods.
Enables deeper insights into cellular complexity, spatial organization, and molecular interactions.