Polycomb-group (PcG) of proteins are evolutionarily conserved transcription factors necessary for the regulation of gene expression during the development and the safeguard of cell identity in adulthood. In the nucleus, they form aggregates whose positioning and dimension are fundamental for their function. We present an algorithm, and its MATLAB implementation, based on mathematical methods to detect and analyze PcG proteins in fluorescence cell image z-stacks. Our algorithm provides a method to measure the number, the size, and the relative positioning of the PcG bodies in the nucleus for a better understanding of their spatial distribution, and thus of their role for a correct genome conformation and function.
Gregoretti, F., Lucini, F., Cesarini, E., Oliva, G., Lanzuolo, C., Antonelli, L. (2023). Segmentation, 3D Reconstruction, and Analysis of PcG Proteins in Fluorescence Microscopy Images in Different Cell Culture Conditions. In C. Lanzuolo, F. Marasca (a cura di), Polycomb Group Proteins Methods and Protocols (pp. 147-169). Humana Press Inc. [10.1007/978-1-0716-3143-0_12].
Segmentation, 3D Reconstruction, and Analysis of PcG Proteins in Fluorescence Microscopy Images in Different Cell Culture Conditions
Lucini F.;
2023
Abstract
Polycomb-group (PcG) of proteins are evolutionarily conserved transcription factors necessary for the regulation of gene expression during the development and the safeguard of cell identity in adulthood. In the nucleus, they form aggregates whose positioning and dimension are fundamental for their function. We present an algorithm, and its MATLAB implementation, based on mathematical methods to detect and analyze PcG proteins in fluorescence cell image z-stacks. Our algorithm provides a method to measure the number, the size, and the relative positioning of the PcG bodies in the nucleus for a better understanding of their spatial distribution, and thus of their role for a correct genome conformation and function.
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