Spatial modeling of biological patterns shows multiscale organization of Arabidopsis thaliana heterochromatin

Abstract

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.

NODeJ: an ImageJ plugin for 3D segmentation of nuclear objects

“…75.5% of detected chromocenters were under 0.6 µm of the nuclear periphery (Fig. 2D) compared to 80% in the original study [16]. All together, the results obtained with NODeJ are in agreement with previously published results.…”

“…We observed a similar nuclei volume distribution compared to the published results (centered ≈ 100 µm 3 ) (Fig. 2A) [16]. We then used NODeJ to detect the size and the number of individual chromocenters for each nucleus.…”

“…2B), and we obtained a distribution centered ≈ 8 chromocenters per nucleus (Fig. 2C), the same values found in Arpòn et al (2021). We also analyzed the radial distance from the chromocenter boundary to the nearest border of the nuclear envelope.…”

“…To demonstrate the ability of NODeJ to segment objects from grayscale images, we reanalyzed several datasets of nuclei stained with DNA dyes. Arpòn et al (2021) published images of isolated nuclei from various tissues from wild type plants 18 days after germination (dag) (n=212 nuclei) showing different levels of endoreduplication (i.e. ploidy level) and therefore different numbers of chromocenters.…”

Spatial Statistical Models: An Overview under the Bayesian Approach

“…Spatial statistical models play a key role in determining the spatial pattern or quantifying the relative positions of biological components, such as DNA, involved in some biological functions. Some examples include the study of the relative positioning of primordial and growing follicles in mice to identify the likely source of some regulatory muscles [44]; determine the spatial patterns, relative position, and interaction of Arabidopsis thaliana heterochromatin [45]; for molecular profiling using the Bayesian hierarchical negative binomial distribution for diagnoses and treatment procedures [46]. Moreover, it is useful for disease mapping to determine the onset of an epidemic disease.…”