EASI-ORC: A pipeline for the efficient analysis and segmentation of smFISH images for organelle-RNA colocalization measurements in yeast

Analysis of single-molecule fluorescent in situ hybridization (smFISH) images is important to translate cellular image data into a quantifiable format. Although smFISH is the gold standard for RNA localization measurements, there are no freely available, user-friendly applications for assaying messenger RNA (mRNA) localization to organelles. EASI-ORC (Efficient Analysis and Segmentation of smFISH Images for Organelle-RNA Colocalization) is a novel pipeline for the automated analysis of multiple smFISH images of yeast cells. EASI-ORC automates the segmentation of cells and organelles, identifies bona fide smFISH signals, and measures mRNA-organelle colocalization. EASI-ORC is efficient, unbiased, and plots the colocalization data and statistical analyses. EASI-ORC utilizes existing ImageJ plugins and original scripts, thus allowing for free access and ease-of-use. To circumvent technical literacy issues, a step-by-step user guide is provided. EASI-ORC offers a robust solution to smFISH image analysis - one that saves time, effort and provides consistent measurements of mRNA-organelle colocalization in yeast.

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Publication Details

Journal
Communications Biology
Published
2025-02-15
DOI
https://doi.org/10.1038/s42003-025-07682-z
Citations
2
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
3.27

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article

EASI-ORC: A pipeline for the efficient analysis and segmentation of smFISH images for organelle-RNA colocalization measurements in yeast

Shahar Garin, Jeffrey E. Gerst, Liav Levavi
2 citations
Communications Biology
Cell Image Analysis Techniques
3.27
article

EASI-ORC: A pipeline for the efficient analysis and segmentation of smFISH images for organelle-RNA colocalization measurements in yeast

Shahar Garin, Jeffrey E. Gerst, Liav Levavi
article en
2 citations

Abstract

Analysis of single-molecule fluorescent in situ hybridization (smFISH) images is important to translate cellular image data into a quantifiable format. Although smFISH is the gold standard for RNA localization measurements, there are no freely available, user-friendly applications for assaying messenger RNA (mRNA) localization to organelles. EASI-ORC (Efficient Analysis and Segmentation of smFISH Images for Organelle-RNA Colocalization) is a novel pipeline for the automated analysis of multiple smFISH images of yeast cells. EASI-ORC automates the segmentation of cells and organelles, identifies bona fide smFISH signals, and measures mRNA-organelle colocalization. EASI-ORC is efficient, unbiased, and plots the colocalization data and statistical analyses. EASI-ORC utilizes existing ImageJ plugins and original scripts, thus allowing for free access and ease-of-use. To circumvent technical literacy issues, a step-by-step user guide is provided. EASI-ORC offers a robust solution to smFISH image analysis - one that saves time, effort and provides consistent measurements of mRNA-organelle colocalization in yeast.

Communications BiologyVol. 8(1)
Weizmann Institute of Science (IL)
Weizmann Institute of Science
Openalex Percentile: Top 9%
Cell Image Analysis Techniques
3.27
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EASI-ORC: A pipeline for the efficient analysis and segmentation of smFISH images for organelle-RNA colocalization measurements in yeast — Shahar Garin, Jeffrey E. Gerst, et al. · Communications Biology (2025) | TGRS Research Map | TGRS