Capturing variations in nuclear phenotypes - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Journal Articles Journal of computational science Year : 2019

Capturing variations in nuclear phenotypes


Relating genotypes with phenotypes is important to understand diseases like cancer, but extremelychallenging, given the underlying biological variability and levels of phenotypes. 3D quantitative toolsare increasingly used to provide robust inferences pertaining to variations across collections of cells.We especially focus on the changes wrought to the nucleus of specific genotypes. Fibroblasts in thetumor microenvironment of mammary epithelial tissue serve as our model system and provide the con-text, although our methods are applicable to a broader range of biological systems. Using an imagebased approach, we analyze in 3D and compare phenotypes at nuclear level using estimates of texture,morphology and spatial context based on confocal images.Our data demonstrates that deletion of TP53 in stromal fibroblasts results in reorganization of chro-matin content across the nucleus, especially the nuclear periphery, while simultaneously reducingnuclear size and making it more spindly. No such shape change was observed for PTEN-deleted genotype,although there were some differences in distribution of chromatin and an increase in the local nucleardensity.The relative changes in phenotypes are in line with the larger role that the TP53 plays in tumor initiationand progression.These findings play an important role in uncovering the relationships of those genes withthe subcellular phenotypes, as well as formulating new hypotheses, especially pertaining to the relativeimpact of genes in specific pathways. More importantly, they demonstrate the efficacy of methodologyof analyzing a large number of cellular phenotypes.
No file

Dates and versions

hal-02424723 , version 1 (28-12-2019)



Sundaresan Raman, Shantanu Singh, Thierry Pécot, Enrico Caserta, Kun Huang, et al.. Capturing variations in nuclear phenotypes. Journal of computational science, 2019, 36, pp.1-12. ⟨10.1016/j.jocs.2019.07.001⟩. ⟨hal-02424723⟩


80 View
0 Download



Gmail Facebook X LinkedIn More