@article{d5380af06e2e40c690a1f8a9ac97c87c,
title = "Statistically derived geometrical landscapes capture principles of decision-making dynamics during cell fate transitions",
abstract = "Fate decisions in developing tissues involve cells transitioning between discrete cell states, each defined by distinct gene expression profiles. The Waddington landscape, in which the development of a cell is viewed as a ball rolling through a valley filled terrain, is an appealing way to describe differentiation. To construct and validate accurate landscapes, quantitative methods based on experimental data are necessary. We combined principled statistical methods with a framework based on catastrophe theory and approximate Bayesian computation to formulate a quantitative dynamical landscape that accurately predicts cell fate outcomes of pluripotent stem cells exposed to different combinations of signaling factors. Analysis of the landscape revealed two distinct ways in which cells make a binary choice between one of two fates. We suggest that these represent archetypal designs for developmental decisions. The approach is broadly applicable for the quantitative analysis of differentiation and for determining the logic of developmental decisions.",
keywords = "Waddington landscape, catastrophe theory, cell fate decisions, dynamical systems, geometric models, pluripotent stem cell differentiation",
author = "Meritxell S{\'a}ez and Robert Blassberg and Elena Camacho-Aguilar and Siggia, {Eric D.} and Rand, {David A.} and James Briscoe",
note = "Funding Information: Funding: this work was funded by the EPSRC (grant EP/P019811/1 to D.A.R.) and an EPSRC scholarship to E.C.-A (1499350); the University of Warwick ; the Francis Crick Institute , which receives its core funding from Cancer Research UK ; the UK Medical Research Council and Wellcome Trust (all under FC001051 ); and by the European Research Council under European Union (EU) Horizon 2020 research and innovation program grant 742138 . E.D.S. was supported by the National Science Foundation (US) by grant Phy 2013131 . Some of this work was performed at the KITP Santa Barbara and, therefore, this research was supported in part by the National Science Foundation under grant no. NSF PHY-1748958 , NIH grant no. R25GM067110 , and the Gordon and Betty Moore Foundation grant no. 2919.01 . This research was funded in whole, or in part, by the Wellcome Trust ( FC001051 ). For the purpose of Open Access, the author has applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission. Funding Information: We thank Despina Stamataki for experimental support and Francis Corson, Joaquina Delas, Ashley Libby, Rory Maizels, and Archishman Raju for critical feedback on the manuscript. We thank Paul Brown for technical support and Yashin Dicente Cid for critical discussions. We are grateful to the Crick Science Technology Platforms, in particular, to Flow Cytometry Facility and High-Performance Computing. Funding: this work was funded by the EPSRC (grant EP/P019811/1 to D.A.R.) and an EPSRC scholarship to E.C.-A (1499350); the University of Warwick; the Francis Crick Institute, which receives its core funding from Cancer Research UK; the UK Medical Research Council and Wellcome Trust (all under FC001051); and by the European Research Council under European Union (EU) Horizon 2020 research and innovation program grant 742138. E.D.S. was supported by the National Science Foundation (US) by grant Phy 2013131. Some of this work was performed at the KITP Santa Barbara and, therefore, this research was supported in part by the National Science Foundation under grant no. NSF PHY-1748958, NIH grant no. R25GM067110, and the Gordon and Betty Moore Foundation grant no. 2919.01. This research was funded in whole, or in part, by the Wellcome Trust (FC001051). For the purpose of Open Access, the author has applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission. R.B. J.B. E.C.-A. and D.A.R. conceived the project. R.B. established the in vitro differentiation system and flow-cytometry workflow, performed all experiments, and pre-processed data. M.S. and E.C.-A. analyzed data. M.S. designed and performed the clustering procedure with input from E.C.-A. and R.B. All authors interpreted data and designed experiments. M.S. D.A.R. and E.D.S. designed the mathematical model with contributions from E.C.-A. E.C.-A. designed and implemented the software to simulate and fit the mathematical model with input from M.S. M.S. performed the fitting with input from E.C.A. M.S. D.A.R. and J.B. wrote the manuscript with contributions from R.B. and E.C.-A. E.D.S. reviewed and edited the manuscript. The authors declare no competing interests. Publisher Copyright: {\textcopyright} 2021 The Author(s)",
year = "2022",
month = jan,
day = "19",
doi = "10.1016/j.cels.2021.08.013",
language = "English",
volume = "13",
pages = "12--28.e3",
journal = "Cell Systems",
issn = "2405-4712",
publisher = "Cell Press",
number = "1",
}