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Published July 17, 2014 | Supplemental Material + Published
Journal Article Open

Dynamic Heterogeneity and DNA Methylation in Embryonic Stem Cells


Cell populations can be strikingly heterogeneous, composed of multiple cellular states, each exhibiting stochastic noise in its gene expression. A major challenge is to disentangle these two types of variability and to understand the dynamic processes and mechanisms that control them. Embryonic stem cells (ESCs) provide an ideal model system to address this issue because they exhibit heterogeneous and dynamic expression of functionally important regulatory factors. We analyzed gene expression in individual ESCs using single-molecule RNA-FISH and quantitative time-lapse movies. These data discriminated stochastic switching between two coherent (correlated) gene expression states and burst-like transcriptional noise. We further showed that the "2i" signaling pathway inhibitors modulate both types of variation. Finally, we found that DNA methylation plays a key role in maintaining these metastable states. Together, these results show how ESC gene expression states and dynamics arise from a combination of intrinsic noise, coherent cellular states, and epigenetic regulation.

Additional Information

© 2014 Elsevier Inc. Copyright © 2014 The Authors. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/3.0/). Received 18 October 2013, Revised 4 April 2014, Accepted 18 June 2014, Available online 18 July 2014. We thank Jordi Garcia-Ojalvo, Xiling Shen, Georg Seelig, Arjun Raj, and David Sprinzak for helpful comments on the manuscript; the Kathrin Plath Lab, the Austin Smith Lab, and RIKEN for kindly providing reporter and knockout cell lines; and the Caltech FACS Facility for assistance with cell sorting. This work was supported by the National Institutes of Health grants R01HD075605A, R01GM086793A, and P50GM068763; the Weston Havens Foundation; Human Frontiers Science Program; the Packard Foundation; a Wellcome Trust Investigators Grant to M.A.S.; and a KAUST, APART, and CIRM Fellowship to J.T. This work is funded by the Gordon and Betty Moore Foundation through Grant GBMF2809 to the Caltech Programmable Molecular Technology Initiative. Open Access funded by Wellcome Trust. Sequencing data have been deposted in NCBI's GEO under accession number GSE58396. Author Contributions: Z.S.S. and J.Y. contributed equally and are listed alphabetically. Z.S.S., J.Y., J.T., L.C., M.A.S., and M.B.E. conceived experiments. Z.S.S., J.Y., J.T., and J.A.H. performed experiments and analyzed data, with Z.S.S. leading smFISH and methylation experiments and J.Y. leading the movie experiments and modeling. A.A. contributed computational algorithms. M.A.S. and M.B.E. supervised research. Z.S.S., J.T., J.Y., and M.B.E. wrote the manuscript with substantial input from all authors.

Attached Files

Published - 1-s2.0-S1097276514005632-main.pdf

Supplemental Material - mmc1.pdf

Supplemental Material - mmc2.xlsx

Supplemental Material - mmc3.mp4

Supplemental Material - mmc4.mp4

Supplemental Material - mmc5.mp4

Supplemental Material - mmc6.mp4


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August 20, 2023
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