Work

Epigenetic Landscapes Explain Partially Reprogrammed Cells and Identify Key Reprogramming Genes

Year: 2014

Type: article

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.

Source: PLoS Computational Biology

DOI: 10.1371/journal.pcbi.1003734

Authors: Alex H. Lang, Hu Li, James J. Collins, Pankaj Mehta

Institutions: Boston University, Harvard University, Wyss Institute for Biologically Inspired Engineering, Howard Hughes Medical Institute

Language: English

Topic: Gene Regulatory Network Analysis

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $3,043

Funder: National Science Foundation