Publications

DypFISH

Macha Nikolski

• 2 min read
DypFISH approach overview
DypFISH is an approach for measuring quantitatively the spatial distribution of slow-scale dynamics of mRNA and protein distributions

Dynamic Patterned FISH to Interrogate RNA and Protein Spatial and Temporal Subcellular Distribution

Anca F. Savulescu, Robyn Brackin, Emmanuel Bouilhol, Benjamin Dartigues, Jonathan H. Warrell, Mafalda R. Pimentel, Nicolas Beaume, Isabela C. Fortunato, Stephane Dallongeville, Mikaël Boulle, Hayssam Soueidan, Fabrice Agou, Jan Schmoranzer, Jean-Christophe Olivo-Marin, Claudio A. Franco, Edgar R. Gomes, Macha Nikolski and Musa M. Mhlanga


Interrogating RNA and protein spatial subcellular distribution in smFISH data with DypFISH
Savulescu et al. present DypFISH, a method to quantitatively investigate the subcellularspatial localization of RNA and proteins. DypFISH introduces a range of analyticaltechniques and statistics to interrogate single-molecule RNA FISH data in combinationwith protein immunolabeling.
Cell Reports MethodsSearch for articles by this author
Read the full article on Cell Reports Methods 

Overview

DypFISH is a spatially resolved high throughput approach for measuring quantitatively the spatial distribution of slow-scale dynamics of mRNA and protein distributions at fine-grained spatial resolution in single cells. DypFISH introduces analytical techniques that allow joint analysis of discrete point-based single molecule Fluorescence In Situ Hybridization (FISH) mRNA data and continuous intensity immunofluorescence (IF) protein data. The analytical techniques include a generalized approach to identifying clustering dynamics, an approach to identifying dependencies of mRNA and protein spatial distributions on organelle positioning and an approach to identifying interdependent dynamics between mRNA transcripts and their corresponding protein products globally and at specific subcellular locations.

Code

The source code of the downstream analysis pipeline can be downloaded from our GitHub

GitHub - cbib/dypfish
Contribute to cbib/dypfish development by creating an account on GitHub.
GitHubcbib

Data

Dataset Link
H5 files for Micropatterned Arhgdia, Gapdh, B-actin, Pard3, Rab13, Pkp4. Config file Download
H5 file for CHX data, config file Download
H5 file for CytoD data, config file Download
H5 file for Nocodazole data, config file Download
H5 file for PRRC2C data, config file Download
H5 file for Muscle data, config file Download

Datasets to run the unit tests, as well as sample config : Download

Citation

DypFISH: Dynamic Patterned FISH to Interrogate RNA and Protein Spatial and Temporal Subcellular Distribution Anca F. Savulescu, Robyn Brackin, Emmanuel Bouilhol, Benjamin Dartigues, Jonathan H. Warrell, Mafalda R. Pimentel, Stephane Dallongeville, Jan Schmoranzer, Jean-Christophe Olivo-Marin, Edgar R. Gomes, Macha Nikolski, Musa M. Mhlanga bioRxiv 536383; doi: https://doi.org/10.1101/536383

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