Speaker: Alex Lang

When: October 3, 2012 (Wed), 02:00PM to 03:00PM (add to my calendar)

Location: SCI 328

Examining Committee:  Pankaj Mehta, Ahmad Khalil, Claudio Chamon, Martin Schmaltz

 

Abstract:

A common metaphor for describing development is a rugged “epigenetic landscape” where cell types are represented as attracting valleys resulting from a complex regulatory network. Here, we introduce a correlation-based framework for explicitly constructing epigenetic landscapes that combines large scale genomic data with techniques from spin glass physics. Each cell type is a dynamic attractor, yet individual cells can still change cell fate in response to external signals. Our model suggests that partially-reprogrammed cells (i.e spurious cell types that do not occur in vivo) are a natural consequence of the high-dimensional landscape and predicts that partially-reprogrammed cells are linear combinations of existing cell types. We verify this prediction by reanalyzing existing data sets. Finally, we show that our landscape can be used to identify candidate transcription factors for reprogramming and reproduces known protocols. This suggests a general method for rationally designing reprogramming protocols to new cell types.