Single-Cell Expression Analyses during Cellular Reprogramming Reveal an Early Stochastic and a Late Hierarchic Phase
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Buganim-2012-Single-Cell Expressi.pdf
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Author(s)
Buganim, Yosef
Faddah, Dina A.
Itskovich, Elena
Markoulaki, Styliani
Ganz, Kibibi
van Oudenaarden, Alexander
Jaenisch, Rudolf
Klemm, Sandy Lee
van Oudenaarden, Alexander
Cheng, Albert Wu
Date Issued
September 2012
Journal
Cell
Publisher
Elsevier
Citation
Buganim, Yosef, Dina A. Faddah, Albert W. Cheng, Elena Itskovich, Styliani Markoulaki, Kibibi Ganz, Sandy L. Klemm, Alexander van Oudenaarden, and Rudolf Jaenisch. “Single-Cell Expression Analyses During Cellular Reprogramming Reveal an Early Stochastic and a Late Hierarchic Phase.” Cell 150, no. 6 (September 2012): 1209–1222. © 2012 Elsevier Inc.
Version
Final published version
Abstract
During cellular reprogramming, only a small fraction of cells become induced pluripotent stem cells (iPSCs). Previous analyses of gene expression during reprogramming were based on populations of cells, impeding single-cell level identification of reprogramming events. We utilized two gene expression technologies to profile 48 genes in single cells at various stages during the reprogramming process. Analysis of early stages revealed considerable variation in gene expression between cells in contrast to late stages. Expression of Esrrb, Utf1, Lin28, and Dppa2 is a better predictor for cells to progress into iPSCs than expression of the previously suggested reprogramming markers Fbxo15, Fgf4, and Oct4. Stochastic gene expression early in reprogramming is followed by a late hierarchical phase with Sox2 being the upstream factor in a gene expression hierarchy. Finally, downstream factors derived from the late phase, which do not include Oct4, Sox2, Klf4, c-Myc, and Nanog, can activate the pluripotency circuitry.
MIT Department
Massachusetts Institute of Technology. Computational and Systems Biology Program
Massachusetts Institute of Technology. Department of Biology
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Department of Physics
Whitehead Institute for Biomedical Research
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1016/j.cell.2012.08.023
