Abstract : 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.
https://hal-mines-paristech.archives-ouvertes.fr/hal-01984014
Contributeur : Thomas Walter
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Soumis le : mercredi 16 janvier 2019 - 17:57:07
Dernière modification le : mardi 14 janvier 2020 - 01:16:13
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Distributed under a Creative Commons Paternité 4.0 International License
