Deep Learning Decodes Multi-layered Roles of Polycomb Repressor Complex 2 During Mouse CNS Development
A prominent aspect of most, if not all, central nervous systems (CNSs) is that anterior regions (brain) are larger than posterior ones (spinal cord). Studies in Drosophila and mouse have revealed that the Polycomb Repressor Complex 2 (PRC2) acts by several mechanisms to promote anterior CNS expansion. However, it is unclear if PRC2 acts directly and/or indirectly upon key downstream genes, what the full spectrum of PRC2 action is during embryonic CNS development and how PRC2 integrates with the epigenetic landscape. We removed PRC2 function from the developing mouse CNS, by mutating the key gene Eed, and generated spatio-temporal transcriptomic data. We developed a bioinformatics workflow that incorporates standard statistical analyses with machine learning to integrate the transcriptomic response to PRC2 inactivation with epigenetic information from ENCODE. This multi-variate analysis corroborates the central involvement of PRC2 in anterior CNS expansion, and reveals layered regulation via PRC2. These findings uncover a differential logic for the role of PRC2 upon functionally distinct gene categories that drive CNS anterior expansion. To support the analysis of emerging multi-modal datasets, we provide a novel bioinformatics package that can disentangle regulatory underpinnings of heterogeneous biological processes.