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bioRxiv · 10.1101/2022.05.15.492007

MultiCens: Multilayer network centrality measures to uncover molecular mediators of tissue-tissue communication

Kumar, T.·Sethuraman, R.·Mitra, S.·Ravindran, B.·Narayanan, M.
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Abstract

With the evolution of multicellularity, communication among cells in different organs/tissues became pivotal to life. Molecular basis of such communication has long been studied, but genome-wide screens for biomolecules/genes mediating tissue-tissue signaling are lacking. To systematically identify inter-tissue mediators, we present a novel computational approach MultiCens (Multilayer/Multi-tissue network Centrality measures). Unlike single-layer network methods, MultiCens can distinguish within- vs. across-layer connectivity to quantify the "influence" of any gene in a tissue on a query set of genes of interest in another tissue. MultiCens enjoys theoretical guarantees on convergence and decomposability, and excels on synthetic benchmarks. On human multi-tissue datasets, MultiCens predicts known and novel genes linked to hormones. MultiCens further reveals shifts in gene network architecture among four brain regions in Alzheimers disease. MultiCens-prioritized hypotheses from these two diverse applications, and potential future ones like "Multi-tissue-expanded Gene Ontology" analysis, can enable whole-body yet molecular-level investigations in humans.

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Kumar, T., Sethuraman, R., Mitra, S., Ravindran, B., Narayanan, M.. 2022-05-16. MultiCens: Multilayer network centrality measures to uncover molecular mediators of tissue-tissue communication. https://doi.org/10.1101/2022.05.15.492007

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