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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...

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Related Experiment Video

Updated: May 29, 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

Integrating Tissue Microarray to GeoMx^® Digital Spatial Profiler : Spatial Transcriptomics Assay with Bioinformatics

Deshica Dechamma¹, Manju Moorthy¹, Vijayalakshmi Bhat¹

¹Theracues Innovations Pvt Ltd., Bangalore, Karnataka, India.

Methods in Molecular Biology (Clifton, N.J.)

|February 3, 2025

Summary

This summary is machine-generated.

Spatial transcriptomics, a revolutionary tool, profiles gene expression within cellular microenvironments. This chapter details the Next-Generation Sequencing (NGS) assay protocol for Digital Spatial Profiler (DSP) and its bioinformatics analysis for enhanced disease research.

Keywords:

Abs (antibodies)Bioinformatics analysis for spatial transcriptomics Cancer Transcriptome Atlas (CTA)Digital Spatial Profiler (DSP)Fixed frozen (FxF)Formalin-fixed Fresh frozen (FF)ROI (region of interest)Spatial biology Tissue microarray (TMA)Transcriptomics Whole Transcriptome Atlas (WTA)next-generation sequencing (NGS)paraffin-embedded (FFPE) specimens

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Area of Science:

Genomics and Molecular Biology
Bioinformatics and Computational Biology
Cellular and Tissue Biology

Background:

Gene expression studies have evolved from bulk methods to single-cell and now spatial transcriptomics.
Spatial transcriptomics preserves spatial information, enabling analysis of cellular microenvironments.
This technology is crucial for understanding complex biological mechanisms and diseases.

Purpose of the Study:

To delineate the Next-Generation Sequencing (NGS) assay protocol for the Digital Spatial Profiler (DSP).
To outline the associated bioinformatics analysis for spatial transcriptomics data.
To focus on integrating tissue microarrays, bioinformatics pipelines, and statistical approaches for GeoMx RNA assays.

Main Methods:

Detailed description of the NGS assay protocol for Digital Spatial Profiler (DSP).
Explanation of bioinformatics pipelines and statistical approaches specific to GeoMx RNA assays.
Integration of tissue microarrays for spatial gene expression analysis.

Main Results:

Provides a comprehensive guide to running a DSP RNA assay.
Highlights common errors and troubleshooting for the assay.
Emphasizes the importance of using the latest user guides and documentation.

Conclusions:

Spatial transcriptomics, particularly with DSP and GeoMx RNA assays, is revolutionizing fields like oncology, developmental biology, and neuroscience.
The chapter provides practical guidance on implementing and analyzing spatial transcriptomics data.
Accurate data analysis and adherence to updated protocols are critical for reliable results.