Skip to main content

RNAscope™ ISH Services to Simplify Multiple Region of Interest (ROI) Analysis for Neuroscience Research

Uncover Complex Biology with Precise Spatial Insights and Expert Support

Focusing on specific brain regions in neuroscience research is crucial because different regions of the brain have specialized neural circuits and connectivity patterns that are responsible for different cognitive functions, behaviors or disease states.

RNAscope ISH assay experts from ACD’s Professional Assay Services (PAS) team perform complex sectioning enabling neuroscientists to analyze specific mRNA markers within cross-sections of brain regions.

Why Partner with Us?

Checklist icon

Guaranteed Performance

RNAscope experts perform complex sectioning, assay and analysis.

Quality Control Icon

Save Time and Lab Space

Experiments are performed in a streamlined and efficient manner so you can focus your efforts of other aspects of the project.

target

One Stop Shop

Choose from a wide array of services options from end-to-end options or ala carte based on your project needs.

Understanding Gene Expression and Protein Localization Patterns in Different ROIs of the Brain

RNAscope ROI Analysis Performed by In-House Services Team

 

RNAscope ROI Analysis of Brain Workflow

Fig. RNAscope ISH PAS ROI Analysis for Neuroscience. Sectioning of mouse brain in the coronal plane. 10% NBF fixed whole brain or brain hemispheres are initially grossed into multiple blocks (approximately 5mm in thickness). Depending on the requested regions of interests (ROIs), 5 µm sections from specific blocks are collected at specific depths to capture the ROI(s) using a brain atlas as a guide. H&E staining is utilized to confirm the presence of the ROI prior to performing marker analysis. Representative image of how the brain is cut into four separate pieces. Each piece is embedded into a separate block and sections are then collected around cuts 1, 2 and 3 to capture the indicated ROIs.

Gain useful insights into ROI analysis and uncover data that you may miss when looking at single cross-sections.