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 spin-glass 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 datasets. 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.

24 pages in main text with 11 pages in Supplementary Information, 6 Figures, 6 Data Files. v2 correctly attaches Data Files, no paper changes. v3 only change in Data File TF_Reprogramming_Candidates.xls so that Overexpression / Knockout were in separate lists. v4 updates file to version published in Plos Comp Bio

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