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Related Concept Videos

RNA-seq03:21

RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
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Related Experiment Video

Updated: Nov 9, 2025

Multiplexed Barcoding Image Analysis for Immunoprofiling and Spatial Mapping Characterization in the Single-Cell Analysis of Paraffin Tissue Samples
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Multiplexed Barcoding Image Analysis for Immunoprofiling and Spatial Mapping Characterization in the Single-Cell Analysis of Paraffin Tissue Samples

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Compressed sensing for highly efficient imaging transcriptomics.

Brian Cleary1, Brooke Simonton2, Jon Bezney2

  • 1Broad Institute of MIT and Harvard, Cambridge, MA, USA. bcleary@broadinstitute.org.

Nature Biotechnology
|April 16, 2021
PubMed
Summary
This summary is machine-generated.

Composite In Situ Imaging (CISI) enables faster spatial gene expression mapping by analyzing gene modules instead of individual genes. This significantly improves efficiency for large-scale tissue analysis.

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

  • Molecular Biology
  • Genomics
  • Bioimaging

Background:

  • Current spatial imaging methods for tissues are limited by long imaging times due to the number of proteins or genes analyzed.
  • Existing techniques can identify approximately 100 proteins or RNAs at single-cell resolution.

Purpose of the Study:

  • To develop a novel method for spatial gene expression mapping that significantly reduces imaging time and increases efficiency.
  • To leverage inherent structures in gene expression across cells and tissues to optimize imaging protocols.

Main Methods:

  • Introduced Composite In Situ Imaging (CISI), a method that uses composite measurements of gene modules.
  • Defined gene modules detected by imaging probes for subsets of genes, followed by data decompression to recover individual gene expression.
  • Reduced imaging time by eliminating the need for spot-level resolution, allowing for lower magnification acquisition.

Main Results:

  • Achieved approximately 500-fold greater efficiency compared to current spatial imaging methods.
  • Successfully recovered spatial abundance of 37 individual genes from 11 composite measurements across 12 mouse brain sections.
  • Mapped gene expression across 180 mm² of tissue, encompassing 476,276 cells.

Conclusions:

  • Composite In Situ Imaging (CISI) offers a highly efficient approach for large-scale spatial gene expression analysis.
  • The method accurately reconstructs gene expression patterns, overcoming limitations of current imaging technologies.
  • CISI enables faster and more comprehensive spatial transcriptomic studies in complex biological samples.