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FISH - Fluorescent In-situ Hybridization

FISH - Fluorescent In-situ Hybridization

Fluorescence in situ hybridization, or FISH, was developed in the early 1980s and has quickly become one of the most widely used techniques in cytogenetics. Labeled probes are used to bind complementary DNA or RNA sequences on a chromosome or in a region within a cell. Earlier, the probes could only be obtained by cloning or reverse transcription of a DNA template. Currently, the probe oligonucleotides can be synthesized synthetically. Additionally, with the advancement of optical techniques,...

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Updated: Sep 28, 2025

Development of automated imaging and analysis for zebrafish chemical screens.

Development of automated imaging and analysis for zebrafish chemical screens.

Published on: June 24, 2010

FISH-quant v2: a scalable and modular tool for smFISH image analysis.

Arthur Imbert^1,2,3, Wei Ouyang⁴, Adham Safieddine⁵

¹Centre for Computational Biology (CBIO), MINES ParisTech, PSL University, 75272 Paris Cedex 06, France.

RNA (New York, N.Y.)

|March 29, 2022

Summary

This summary is machine-generated.

FISH-quant v2 is a user-friendly tool for analyzing single-molecule RNA fluorescence in situ hybridization (smFISH) data. It reveals diverse RNA localization patterns and significant cell-to-cell heterogeneity in gene expression.

Keywords:

RNA localization image analysis smFISH transcription

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Last Updated: Sep 28, 2025

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Area of Science:

Molecular Biology
Genetics
Bioinformatics

Background:

Gene expression control relies on regulating RNA abundance and localization.
Single-molecule RNA fluorescence in situ hybridization (smFISH) is crucial for quantitative single-cell gene expression studies.
Large-scale smFISH necessitates advanced data analysis tools.

Purpose of the Study:

To introduce FISH-quant v2, a modular and user-friendly software for analyzing large-scale smFISH data.
To enable segmentation, RNA detection, cluster decomposition, and localization quantification.
To visualize single-cell and population-level RNA distribution patterns.

Main Methods:

Development of FISH-quant v2, a software package for smFISH image analysis.
Implementation of algorithms for nuclei and cell segmentation.
Inclusion of modules for isolated RNA detection and dense RNA cluster decomposition.
Features for quantifying RNA localization and visualizing results.

Main Results:

FISH-quant v2 successfully processed large-scale smFISH datasets.
The tool enabled detailed analysis of subcellular RNA localization patterns.
Analysis revealed substantial cell-to-cell heterogeneity in RNA expression and localization.

Conclusions:

FISH-quant v2 is a versatile tool for smFISH data analysis, suitable for both experts and non-experts.
The software facilitates the exploration of complex gene expression dynamics.
The findings highlight significant biological variability in RNA localization within cell populations.