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

  1. Florian Mueller6,7
  1. 1 Centre for Computational Biology (CBIO), MINES ParisTech;
  2. 2 Royal Institute of Technology, Stockholm, Sweden;
  3. 3 Sorbonne Université;
  4. 4 IGH, University of Montpellier;
  5. 5 Imaging and Modeling Unit, Institut Pasteur;
  6. 6 Institut Pasteur
  1. * Corresponding author; email: fmueller{at}pasteur.fr

Abstract

Regulation of RNA abundance and localization is a key step in gene expression control. Single-molecule RNA fluorescence in-situ hybridization (smFISH) is a widely used single-cell-single-molecule imaging technique enabling quantitative studies of gene expression and its regulatory mechanisms. Today, these methods are applicable at a large scale, which in turn come with a need for adequate tools for data analysis and exploration. Here, we present FISH-quant v2, a highly modular tool accessible for both experts and non-experts. Our user-friendly package allows the user to segment nuclei and cells, detect isolated RNAs, decompose dense RNA clusters, quantify RNA localization patterns and visualize these results both at the single-cell level and variations within the cell population. This tool was validated and applied on large-scale smFISH image datasets, revealing diverse subcellular RNA localization patterns and a surprisingly high degree of cell-to-cell heterogeneity.

Keywords

  • Received December 2, 2021.
  • Accepted February 19, 2022.

This article, published in RNA, is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.

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