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A computational framework to study sub-cellular RNA localization.

Aubin Samacoits | Racha Chouaib | Adham Safieddine | Abdel-Meneem Traboulsi | Wei Ouyang | Christophe Zimmer | Marion Peter | Edouard Bertrand | Thomas Walter | Florian Mueller
Nature communications | 2018

RNA localization is a crucial process for cellular function and can be quantitatively studied by single molecule FISH (smFISH). Here, we present an integrated analysis framework to analyze sub-cellular RNA localization. Using simulated images, we design and validate a set of features describing different RNA localization patterns including polarized distribution, accumulation in cell extensions or foci, at the cell membrane or nuclear envelope. These features are largely invariant to RNA levels, work in multiple cell lines, and can measure localization strength in perturbation experiments. Most importantly, they allow classification by supervised and unsupervised learning at unprecedented accuracy. We successfully validate our approach on representative experimental data. This analysis reveals a surprisingly high degree of localization heterogeneity at the single cell level, indicating a dynamic and plastic nature of RNA localization.

Pubmed ID: 30389932

Research resources used in this publication

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MATLAB (tool)

RRID:SCR_001622

Multi paradigm numerical computing environment and fourth generation programming language developed by MathWorks. Allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages, including C, C++, Java, Fortran and Python. Used to explore and visualize ideas and collaborate across disciplines including signal and image processing, communications, control systems, and computational finance.

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RRID:SCR_001672

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Molecular Probes (tool)

RRID:SCR_013318

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RRID:CVCL_0188

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HeLa (tool)

RRID:CVCL_0030

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