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Spatially Compact Arrangement of Larval Zebrafish Sections for Spatial Transcriptomic Analysis

Spatially Compact Arrangement of Larval Zebrafish Sections for Spatial Transcriptomic Analysis

Published on: May 16, 2025

A unified pipeline for FISH spatial transcriptomics.

Cecilia Cisar¹, Nicholas Keener¹, Mathew Ruffalo²

¹Department of Biomolecular Engineering, School of Engineering, University of California, Santa Cruz, Santa Cruz, CA 95064, USA.

|September 18, 2023

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A new pipeline called PIPEFISH standardizes spatial transcriptomics analysis for fluorescence in situ hybridization (FISH) experiments. This open-source tool improves transcript annotation for MERFISH, seqFISH, and targeted in situ sequencing (ISS) data.

Area of Science:

Molecular Biology
Bioinformatics
Genomics

Background:

High-throughput spatial transcriptomics enables mRNA expression analysis within cellular contexts.
A lack of standardized analysis tools hinders reproducibility and accessibility in spatial transcriptomics.
In-house tools are often poorly documented and lack generalizability.

Purpose of the Study:

To develop a standardized, semi-automated, and generalizable pipeline for spatial transcriptomics data analysis.
To improve transcript annotation for fluorescence in situ hybridization (FISH)-based spatial transcriptomics.
To provide a publicly available and open-source tool for the research community.

Main Methods:

Expansion and improvement of the existing starfish library.

Keywords:

FISH computational methods genomics spatial transcriptomics transcriptomics

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Last Updated: Jul 16, 2025

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Published on: May 16, 2025

Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish

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Development of PIPEFISH, a pipeline for transcript annotation in FISH-based spatial transcriptomics.

Application of PIPEFISH to MERFISH, seqFISH, and targeted in situ sequencing (ISS) datasets.

Main Results:

Successful annotation of transcript locations across three diverse FISH-based spatial transcriptomics datasets.
High-quality results validated by internal quality metrics and orthogonal RNA expression measurements.
Demonstrated generalizability and robustness of the PIPEFISH pipeline.

Conclusions:

PIPEFISH offers a standardized and robust solution for analyzing FISH-based spatial transcriptomics data.
The pipeline enhances the accessibility and reproducibility of spatial transcriptomics research.
PIPEFISH is a valuable, open-source resource for investigating spatial gene expression patterns.