Speaker
Description
The spatial organization of chromatin plays a key role in genome function, but how it is modulated by environmental perturbations such as sleep deprivation remains to be fully characterized. In this study, we employ a statistical mechanics framework to investigate chromatin architecture in pyramidal glutamatergic neurons (PGNs) from the mouse hippocampus, focusing on contact probabilities beyond pairwise interactions.
We analyse chromatin contact maps obtained via Genome Architecture Mapping (GAM), a ligation-free technique that avoids crosslinking biases and apply Statistical Inference of Co-Segregation (SLICE), a probabilistic model that infers interaction probabilities between genomic loci based on GAM observed frequencies.
SLICE enables the computation of triplet contact probabilities, providing a novel perspective on high-order interactions in chromatin architecture. Our results indicate that sleep deprivation induces substantial alterations in chromatin folding, affecting TAD boundary positioning and the clustering of triplet interactions, which may reflect an additional level of chromatin organization. These findings suggest that statistical mechanics principles can be effectively leveraged to characterize the chromatin organization underlying environmental stressors.
By integrating theoretical modelling with experimental data, this study highlights the power of statistical inference approaches in elucidating chromatin architecture and offers a probabilistic framework to characterize genome organization and its structural variations under environmental stressors.
| Role | Master/PhD student |
|---|
