Spatial Rna Detection
Spatial Rna Detection - Related Videos
09:12
Calcified Artery Preparation and Processing with Preserved Morphology and RNA for Digital Spatial Profiling
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2026
This protocol includes a step-by-step workflow for calcified vascular specimens: tissue handling, decalcification, RNA validation, calcification level detection, and region-of-interest selection strategies on the Nanostring GeoMx Digital Spatial Profiler (DSP). The goal is to present a comprehensive method for preserving vascular tissue morphology and RNA for reliable spatial transcriptomic analysis.
02:42
RNA CISH Signal Detection: A Technique to Detect Chromogenic Signals During RNA In Situ Hybridization in Intact Tissue Specimens
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2023
This video presents the protocol for signal detection during RNA chromogenic in situ hybridization. This technique can be used to diagnose an active oncogenic infection visually in an intact tissue specimen.
10:34
Detection of RNA-binding Proteins by In Vitro RNA Pull-down in Adipocyte Culture
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Cited by 19 •
2016
An RNA pull-down protocol is optimized here for detection of interactions between RNA-binding proteins (RBPs) and noncoding as well as coding RNAs. An RNA fragment from androgen receptor (AR) was used as an example to demonstrate how to retrieve its RBP from lystate of primary brown adipocytes.
08:50
A Nonsequencing Approach for the Rapid Detection of RNA Editing
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2022
Rapid detection and reliable quantification of RNA editing events at a genomic scale remain challenging and currently rely on direct RNA sequencing methods. The protocol described here uses microtemperature gradient gel electrophoresis (µTGGE) as a simple, quick, and portable method of detecting RNA editing.
11:54
Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
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Cited by 8 •
2017
We demonstrate a microfluidic platform with an integrated surface electrode network that combines resistive pulse sensing (RPS) with code division multiple access (CDMA), to multiplex detection and sizing of particles in multiple microfluidic channels.
FAQs
Its key analytical value is retaining the position of each transcript signal, so expression can be interpreted within a cell or tissue region rather than as an isolated molecular measurement. In cancer research, this links gene activity to tumor and immune cell states, heterogeneous microenvironments, invasive regions, and treatment responses.
Labeled probes hybridize to selected target transcripts and can be read through imaging. Sequencing-based approaches instead use spatially assigned barcodes, allowing transcript identities to be connected to positions after sequencing. These alternatives preserve the central relationship between RNA identity and location while using different readout strategies.
The workflow begins by fixing tissue sections or intact specimens and then permeabilizing them before probe or barcode exposure. Within the described method, these preparation steps establish the sample state needed for molecular access while retaining the specimen’s spatial context, which is necessary for assigning signals to cells or tissue regions.
Researchers prepare a tissue section or intact specimen, fix and permeabilize it, and expose the sample to labeled probes or sequencing-based barcodes. After target recognition, imaging or sequencing reads the molecular signals and assigns them to cellular or tissue positions, producing a spatial map of transcript distribution.
It is especially useful when the biological question depends on where expression occurs. In cancer studies, spatial measurements can distinguish tumor and immune cell states across heterogeneous microenvironments, then relate those patterns to invasive regions or treatment responses. This added context supports biomarker discovery and more precise models of tumor biology.
The maps reveal how gene activity is organized across cells and tissue regions, allowing investigators to compare molecular patterns with cancer-associated organization. They can identify localized states, examine relationships between tumor and immune compartments, and connect transcript distributions with invasion or response patterns, generating evidence for biomarkers and refined tumor models.