Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

DNA Microarrays

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

Reporter Genes

Reporter Genes

Reporter genes are a type of protein-coding gene that are often tagged to a gene of interest. Once inside a target cell, reporter genes usually produce visually identifiable characteristics like fluorescence and luminescence when expressed along with the gene of interest. Thus, reporter genes “report” the presence or absence of genes of interest in an organism, determine the gene expression pattern, or track the physical location of a DNA segment or protein in the cell.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

NeoCircle: pre- and post-operative circulating tumor DNA dynamics predicts survival in neoadjuvant-treated early breast cancer.

EMBO molecular medicine·2026

Same author

Germline Pathogenic Variants in Breast Cancer-Predisposing Genes Among Early-Onset Female and Male Breast Cancer in Ethiopia.

JCO global oncology·2026

Same author

Correction: Lien et al. Sample Preparation Approach Influences PAM50 Risk of Recurrence Score in Early Breast Cancer. <i>Cancers</i> 2021, <i>13</i>, 6118.

Cancers·2026

Same author

Homologous recombination deficiency in primary ER-positive and HER2-negative breast cancer.

Communications medicine·2026

Same author

Molecular profiling of the Basal-like intrinsic molecular subtype in primary ER-positive HER2-negative breast cancer.

Genome medicine·2025

Same author

Clinical potential of whole-genome data linked to mortality statistics in patients with breast cancer in the UK: a retrospective analysis.

The Lancet. Oncology·2025

Same journal

Erratum for the Research Article "Detecting supramolecular organic nanoparticles during heat wave".

Science (New York, N.Y.)·2026

Same journal

Local signals, systemic decline.

Science (New York, N.Y.)·2026

Same journal

The mechanics of liver regeneration.

Science (New York, N.Y.)·2026

Same journal

Computing in a memory with physics.

Science (New York, N.Y.)·2026

Same journal

Retraction.

Science (New York, N.Y.)·2026

Same journal

Making time.

Science (New York, N.Y.)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 6, 2026

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

Visualization and analysis of gene expression in tissue sections by spatial transcriptomics.

Patrik L Ståhl¹, Fredrik Salmén², Sanja Vickovic²

¹Department of Cell and Molecular Biology, Karolinska Institute, SE-171 77 Stockholm, Sweden. Science for Life Laboratory, Division of Gene Technology, KTH Royal Institute of Technology, SE-106 91 Stockholm, Sweden.

Science (New York, N.Y.)

|July 2, 2016

Summary

This summary is machine-generated.

Spatial transcriptomics enables visualization and quantitative analysis of messenger RNAs (mRNAs) within tissue sections. This new method maintains spatial resolution, offering valuable insights for biomedical research and diagnostics.

More Related Videos

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq

Published on: October 31, 2025

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

Related Experiment Videos

Last Updated: May 6, 2026

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

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq

Published on: October 31, 2025

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

Area of Science:

Molecular Biology
Genomics
Biomedical Research

Background:

Analyzing protein or messenger RNA (mRNA) patterns in tissues is crucial for research and diagnostics.
Current methods typically visualize only a few proteins or genes at once.

Purpose of the Study:

To develop a strategy for visualizing and quantitatively analyzing the transcriptome with spatial resolution in tissue sections.
To enable novel bioinformatics analyses for research and diagnostics.

Main Methods:

Developed a "spatial transcriptomics" strategy.
Positioned histological sections on arrayed reverse transcription primers with unique positional barcodes.
Generated high-quality RNA-sequencing data with maintained 2D positional information.

Main Results:

Successfully visualized and quantitatively analyzed the transcriptome with spatial resolution.
Obtained high-quality RNA-sequencing data from mouse brain and human breast cancer tissues.
Demonstrated the maintenance of two-dimensional positional information.

Conclusions:

Spatial transcriptomics provides quantitative gene expression data and mRNA distribution visualization within tissue sections.
This technique offers valuable new bioinformatics analysis capabilities.
The method is applicable to both biomedical research and diagnostic applications.