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Quantitative Biology > Molecular Networks

Title: Epigenetic landscapes explain partially reprogrammed cells and identify key reprogramming genes

Abstract: A common metaphor for describing development is a rugged epigenetic landscape where cell fates are represented as attracting valleys resulting from a complex regulatory network. Here, we introduce a framework for explicitly constructing epigenetic landscapes that combines genomic data with techniques from physics. Each cell fate is a dynamic attractor, yet cells can change fate in response to external signals. Our model suggests that partially reprogrammed cells are a natural consequence of high-dimensional landscapes and predicts that partially reprogrammed cells should be hybrids that co-express genes from multiple cell fates. We verify this prediction by reanalyzing existing data sets. Our model reproduces known reprogramming protocols and identifies candidate transcription factors for reprogramming to novel cell fates, suggesting epigenetic landscapes are a powerful paradigm for understanding cellular identity.
Comments: 19 pages with Supplementary Information, 10 Figures, 4 Data Files. v2 correctly attaches Data Files, no paper changes
Subjects: Molecular Networks (q-bio.MN); Disordered Systems and Neural Networks (cond-mat.dis-nn); Statistical Mechanics (cond-mat.stat-mech)
Cite as: arXiv:1211.3133 [q-bio.MN]
  (or arXiv:1211.3133v2 [q-bio.MN] for this version)

Submission history

From: Alex Lang [view email]
[v1] Tue, 13 Nov 2012 21:07:27 GMT (4373kb,D)
[v2] Thu, 15 Nov 2012 01:27:46 GMT (4441kb,AD)