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.

Resilience Theory and Research on Children and Families: Past, Present, and Promise

“…Diverse pathways arise in human or family life because of the many interactions involved in shaping the adaptive function and development of systems. This diversity of pathways has been noted for decades in developmental embryology, epigenetics, and behavior genetics (Gottesman, 1974;Gottlieb, 2007;Waddington 1957Waddington /2014, developmental psychopathology (Bowlby, 1988;Cicchetti, 2006;Cicchetti & Rogosch, 1996;Cummings & Valentino, 2015;Masten & Kalstabakken, in press;Sroufe 1979), and the literature on individual resilience (Bonanno, 2004(Bonanno, , 2015Masten et al, 1990;Masten & Reed, 2002;Masten & Cicchetti, 2016) as well as family resilience (Boss et al, 2017;Hawley & DeHaan, 1996;Henry et al, 2015). Individual resilience investigators were keenly interested in the diversity of pathways that emerged over the life course, particularly in regard to positive changes that occurred on pathways, when they observed dramatic turnarounds and turning points in the lives of individuals who had suffered adversity (Masten, 2014b;Masten et al, 1988;Masten & Cicchetti, 2016, Rutter, 1987.…”

Cellular reprogramming for understanding and treating human disease

“…This model has verified that partially reprogrammed cells co-express TFs associated with multiple cell fates, has reproduced known reprogramming protocols, and has the potential to generate new reprogramming protocols to create novel cell types (Lang et al, 2014). Defining epigenetic landscapes can not only help to gain better insights into reprogramming processes, but also to design highly efficient protocols.…”

Reverse-engineering biological networks from large data sets

“…Alternatively, attractors of the dynamics of biological networks may be a more laconic descriptions of the networks than the interactions among the nodes themselves [14,336]. This possibility may be motivated via a historical analogy: renormalization group theory in physics [337] offers a systematic way .…”