SUMMARY¶

Integrated gene landscapes uncover multi-layered roles of repressive histone marks during mouse CNS development¶

Ariane Mora1, Jonathan Rakar3, Ignacio Monedero Cobeta3*, Behzad Yaghmaeian Salmani3#, Annika Starkenberg3, Stefan Thor2,3$, Mikael Bodén1

1) School of Chemistry and Molecular Biosciences 2), and School of Biomedical Sciences, University of Queensland, St Lucia QLD 4072, Australia. 3) Department of Clinical and Experimental Medicine, Linkoping University, SE-58185, Linkoping, Sweden.

Current addresses: #) Department of Cell and Molecular Biology, Karolinska Institute, SE-171 65, Stockholm, Sweden. *Department of Physiology, Universidad Autonoma de Madrid, Madrid, Spain. $) School of Biomedical Sciences, University of Queensland, St Lucia QLD 4072, Australia

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. Code for our scivae package is available at sci-vae). Use our interactive website to look at genes of interest!