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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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Related Experiment Video

Updated: Jun 5, 2026

Using an Automated 3D-tracking System to Record Individual and Shoals of Adult Zebrafish

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zFISHer: Automated 3D Registration, Detection, and Colocalization with Interactive Curation for Sequential

Seth Staller¹, Virginia Valentine¹, Steven Burden¹

¹St. Jude Children's Research Hospital, Memphis, TN 38105, USA.

Biorxiv : the Preprint Server for Biology

|June 4, 2026

Summary

zFISHer automates the analysis of 3D FISH images, overcoming bottlenecks in puncta colocalization. This open-source tool streamlines molecular profiling by enabling efficient, accurate, and interactive 3D image processing.

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Last Updated: Jun 5, 2026

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Robust 3D DNA FISH Using Directly Labeled Probes

Robust 3D DNA FISH Using Directly Labeled Probes

Published on: August 15, 2013

Area of Science:

Biotechnology
Microscopy
Bioinformatics

Background:

Analyzing three-dimensional (3D) datasets from sequential multiplexed fluorescence in situ hybridization (FISH) for puncta colocalization is a labor-intensive bottleneck.
Spatially resolved molecular profiling in cell monolayers using FISH requires efficient 3D data analysis.

Purpose of the Study:

To develop an open-source application, zFISHer, for automated and interactive analysis of sequential FISH image data.
To overcome the limitations of manual puncta colocalization analysis in 3D FISH datasets.

Main Methods:

zFISHer utilizes the napari viewer for an end-to-end analysis pipeline.
Includes automated nuclear segmentation, puncta detection on unaligned z-stacks, and multi-round image registration with optional B-spline deformable warping.
Features a "Fishing Hook" raycasting algorithm for precise 3D puncta centroid localization and sub-voxel volume optimization.

Main Results:

zFISHer provides complete automation of sequential FISH image processing with interactive user-curation tools.
Achieves precise transformation of puncta coordinates into aligned space and consensus nuclei generation.
Enables pairwise and tri-channel colocalization analysis with statistics and high-throughput batch processing.

Conclusions:

zFISHer offers a comprehensive solution for analyzing 3D FISH data, significantly reducing analysis time and improving accuracy.
The application's automated and interactive features facilitate efficient molecular profiling and colocalization studies.
zFISHer is freely available as open-source software, promoting wider adoption in biological research.