The spatial organization in the cell nucleus is tightly linked to genome functions such as gene regulation. Similarly, specific spatial arrangements of biological components such as macromolecular complexes, organelles and cells are involved in many biological functions. Spatial interactions among elementary components of biological systems define their relative positioning and are key determinants of spatial patterns. However, biological variability and the lack of appropriate spatial statistical methods and models limit our current ability to analyze these interactions. Here, we developed a framework to dissect spatial interactions and organization principles by combining unbiased statistical tests, multiple spatial descriptors and new spatial models. We used plant constitutive heterochromatin as a model system to demonstrate the potential of our framework. Our results challenge the common view of a peripheral organization of chromocenters, showing that chromocenters are arranged along both radial and lateral directions in the nuclear space and obey a multiscale organization with scale-dependent antagonistic effects. The proposed generic framework will be useful to identify determinants of spatial organizations and to question their interplay with biological functions.

The interphase cell nucleus is extraordinarily complex, ordered, and dynamic. In the last decade, remarkable progress has been made in deciphering the functional organisation of the cell nucleus, and intricate relationships between genome functions (transcription, DNA repair, or replication) and various nuclear compartments have been revealed. In this review, we describe the architecture of the Arabidopsis thaliana interphase cell nucleus and discuss the dynamic nature of its organisation. We underline the need for further developments in quantitative and modelling approaches to nuclear organization.

The cell nucleus is a structurally complex and dynamic organelle ensuring key biological functions. Complex relationships between nuclear structure and functions require a better understanding of the three-dimensional organization of the genome and of the subnuclear compartments. Quantitative image analysis coupled with spatial statistics and modeling is a relevant approach to address these questions. In this chapter, we describe a step-by-step procedure to process images and to test a spatial random model for the distribution of nuclear objects using chromocenters as an example. More elaborate models can be designed on the basis of the random model by introducing additional and more complex constraints to better fit observations and to question determinants of these spatial organizations.

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