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Related Experiment Video

Updated: Mar 7, 2026

En face Cryosectioning of Mouse Retina for High-dimensional Spatial Molecular Analysis

En face Cryosectioning of Mouse Retina for High-dimensional Spatial Molecular Analysis

Published on: July 8, 2025

Spatial transcriptomic analysis of cryosectioned tissue samples with Geo-seq.

Jun Chen^1,2, Shengbao Suo^3,4, Patrick Pl Tam⁵

¹State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, China.

Nature Protocols

|February 17, 2017

Summary

This summary is machine-generated.

Geo-seq combines laser capture microdissection and single-cell RNA-sequencing to analyze spatial gene expression. This method reveals cellular heterogeneity and spatial variance simultaneously, offering insights into biological and pathological processes.

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Last Updated: Mar 7, 2026

En face Cryosectioning of Mouse Retina for High-dimensional Spatial Molecular Analysis

En face Cryosectioning of Mouse Retina for High-dimensional Spatial Molecular Analysis

Published on: July 8, 2025

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

Cryosectioning of Contiguous Regions of a Single Mouse Skeletal Muscle for Gene Expression and Histological Analyses

Cryosectioning of Contiguous Regions of a Single Mouse Skeletal Muscle for Gene Expression and Histological Analyses

Published on: December 12, 2016

Area of Science:

Molecular Biology
Genomics
Spatial Transcriptomics

Background:

Conventional gene expression studies often lose spatial information.
Single-cell analysis reveals heterogeneity but lacks positional context.
Understanding spatial attributes is crucial for cellular properties.

Purpose of the Study:

To introduce Geo-seq, a novel method combining LCM and single-cell RNA-seq.
To enable simultaneous elucidation of cellular heterogeneity and spatial variance.
To profile transcriptome information from small cell populations while retaining spatial data.

Main Methods:

Geo-seq integrates laser capture microdissection (LCM) with single-cell RNA-sequencing (scRNA-seq).
The protocol allows transcriptome profiling from limited cell numbers.
Native spatial information is preserved throughout the process.

Main Results:

Geo-seq successfully investigated the spatial transcriptome in mouse early embryo, mouse brain, and pathological liver and sperm tissues.
The method demonstrated the ability to analyze cellular heterogeneity and spatial variance concurrently.
Transcriptome data was successfully obtained from small cell samples with preserved spatial context.

Conclusions:

Geo-seq offers a powerful approach for studying spatial transcriptomics.
The method has broad applications in addressing biological and pathological questions.
Geo-seq facilitates the investigation of prospective cell fates, biological functions, and gene regulatory networks in a spatial context.