Transcriptional synergy as an emergent property defining cell subpopulation identity enables population shift

Satoshi Okawa, Carmen Saltó, Srikanth Ravichandran, Shanzheng Yang, Enrique M. Toledo, Ernest Arenas and Antonio del Sol ()
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Satoshi Okawa: University of Luxembourg
Carmen Saltó: Biomedicum 6C
Srikanth Ravichandran: University of Luxembourg
Shanzheng Yang: Biomedicum 6C
Enrique M. Toledo: Biomedicum 6C
Ernest Arenas: Biomedicum 6C
Antonio del Sol: University of Luxembourg

Nature Communications, 2018, vol. 9, issue 1, 1-10

Abstract: Abstract Single-cell RNA sequencing allows defining molecularly distinct cell subpopulations. However, the identification of specific sets of transcription factors (TFs) that define the identity of these subpopulations remains a challenge. Here we propose that subpopulation identity emerges from the synergistic activity of multiple TFs. Based on this concept, we develop a computational platform (TransSyn) for identifying synergistic transcriptional cores that determine cell subpopulation identities. TransSyn leverages single-cell RNA-seq data, and performs a dynamic search for an optimal synergistic transcriptional core using an information theoretic measure of synergy. A large-scale TransSyn analysis identifies transcriptional cores for 186 subpopulations, and predicts identity conversion TFs between 3786 pairs of cell subpopulations. Finally, TransSyn predictions enable experimental conversion of human hindbrain neuroepithelial cells into medial floor plate midbrain progenitors, capable of rapidly differentiating into dopaminergic neurons. Thus, TransSyn can facilitate designing strategies for conversion of cell subpopulation identities with potential applications in regenerative medicine.

Date: 2018
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DOI: 10.1038/s41467-018-05016-8

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