Branching and oscillations in the epigenetic landscape of cell-fate determination
| Autor: | Ariel L. Babierra, Jomar F. Rabajante |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Regulation of gene expression
State variable Bistability Models Genetic Ecology Systems biology Cellular differentiation Transdifferentiation Biophysics Gene regulatory network Gene Expression Regulation Developmental Cell Differentiation Biology Cell fate determination Evolutionary biology Biological Clocks Animals Humans Computer Simulation Epigenetics Molecular Biology Reprogramming Transcription Factors |
| Zdroj: | Progress in biophysics and molecular biology. 117(2-3) |
| ISSN: | 1873-1732 |
| Popis: | The well-known Waddington?s epigenetic landscape of cell-fate determination is not static but varies because of the dynamic gene regulation during development. However, existing mathematical models with few state variables and fixed parameters are inadequate in characterizing the temporal transformation of the landscape. Here we simulate a decision-switch model of gene regulation with more than two state variables and with time-varying repression among regulatory factors. We are able to demonstrate multi-lineage differentiation at different timescales that portrays the branching canals in Waddington?s illustration. We also present a repressilator-type system that activates suppressed genes via sustained oscillations in a flattened landscape, hence providing an alternative scheme for cellular reprogramming. The time-dependent parameters governed by gradient-based dynamics regulate cell differentiation, dedifferentiation and transdifferentiation. Our prediction integrates the theories of branching and structural oscillations in cell-fate determination, which reveals key temporal patterns of cell differentiation and associated diseases, such as cancer. Keywords: gene regulatory network, stem cells, pluripotency, synthetic biology, multistability, attractor Note: This paper has been accepted for publication in Progress in Biophysics and Molecular Biology (Elsevier). DOI of the peer-reviewed manuscript: 10.1016/j.pbiomolbio.2015.01.006 |
| Databáze: | OpenAIRE |
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