Effects of Collective Histone State Dynamics on Epigenetic Landscape and Kinetics of Cell Reprogramming

Abstract

Cell reprogramming is a process of transitions from differentiated to pluripotent cell states via transient intermediate states. Within the epigenetic landscape framework, such a process is regarded as a sequence of transitions among basins on the landscape; therefore, theoretical construction of a model landscape which exhibits experimentally consistent dynamics can provide clues to understanding epigenetic mechanism of reprogramming. We propose a minimal gene-network model of the landscape, in which each gene is regulated by an integrated mechanism of transcription-factor binding/unbinding and the collective chemical modification of histones. We show that the slow collective variation of many histones around each gene locus alters topology of the landscape and significantly affects transition dynamics between basins. Differentiation and reprogramming follow different transition pathways on the calculated landscape, which should be verified experimentally via single-cell pursuit of the reprogramming process. Effects of modulation in collective histone state kinetics on transition dynamics and pathway are examined in search for an efficient protocol of reprogramming.

Nonequilibrium physics in biology

“…The dynamics underlying differentiation were studied by analyzing Eq. (102) for a gene regulatory network motif of two self-activating and mutually repressing genes (Ashwin and Sasai, 2015;Chickarmane and Peterson, 2008;Huang et al, 2009;Jiang et al, 2008;, 2015Sasai et al, 2013;Wang et al, 2010bXu et al, 2014b). As discussed previously, this gene motif appears often in stem cell differentiation and reprogramming (Xu et al, 2014a).…”

“…This view was shattered after the identification of the core genetic network underlying differentiation. A typical core motif for these networks involves two self activating genes mutually repressing each other (Ashwin and Sasai, 2015;Chickarmane and Peterson, 2008;Huang et al, 2009;Jiang et al, 2008;, 2015Sasai et al, 2013;Wang et al, 2010bXu et al, 2014b). Some examples include the PU.1-GATA1 gene pair, which directs the differentiation of a common myeloid progenitor (CMP) into either myeloid cell or erythroid cell in blood cell formation; Oct4 and Cdx2 gene pair for the inner cell mass/trophectoderm lineage decision; and Nanog and Gata6 gene pair for segregation of primitive endoderm and epiblast within the inner cell mass, Fig.…”

Genomic Energy Landscapes

“…To see this figure in color, go online. modulate the binding of transcription factors to the gene to regulate it (35)(36)(37)(38). The structures of the locally ordered domains seem complex.…”

Quantifying the interplay between genetic and epigenetic regulations in stem cell development

“…However, the previous landscape models usually focus on the gene regulations, and did not explicitly consider the epigenetics (such as histone modifications) [8,12].Therefore, a critical issue arises as to how to combine the gene regulations and epigenetic modifications in developmental model and get the epigenetic developmental landscape. Computational models have been developed to study the epigenetic control mechanisms [18][19][20][21][22][23][24][25][26]. For example, Berry et al proposed a mathematical model to study the interplay between histone modifications and gene regulations [21].…”