Transcriptional synergy as an emergent property defining cell subpopulation identity enables population shift
| Autor: | Srikanth Ravichandran, Antonio del Sol, Enrique M. Toledo, Satoshi Okawa, Carmen Saltó, Shanzheng Yang, Ernest Arenas |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Transcription Genetic Science genetic processes General Physics and Astronomy Hindbrain Computational biology Biology General Biochemistry Genetics and Molecular Biology Article 03 medical and health sciences Single-cell analysis Transcription (biology) Animals Humans natural sciences Cell Lineage Progenitor cell lcsh:Science Transcription factor Floor plate Multidisciplinary Models Genetic Sequence Analysis RNA fungi Computational Biology General Chemistry Neuroepithelial cell 030104 developmental biology Identity (object-oriented programming) lcsh:Q Single-Cell Analysis Algorithms Transcription Factors |
| Zdroj: | Nature Communications Nature Communications, Vol 9, Iss 1, Pp 1-10 (2018) |
| ISSN: | 2041-1723 |
| Popis: | 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. Gaining insight into cell identities from single cell RNA-seq data remains a challenge. Here, the authors introduce an approach to identify transcription factors (TFs) that synergistically determine cellular identities, and demonstrate its ability to identify TFs that can induce cellular conversion. |
| Databáze: | OpenAIRE |
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