Stochastic epigenome systems with different TF binding locations as a predictor of in vivo parameters for nucleosome accessibility

Jinsu Kim (May 6, 2020)

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In cellular immune responses, inflammatory ligands activate signal-dependent transcription factors (SDTFs), which can display complex temporal profiles. SDTFs are central effectors for inflammatory gene expression. However, the information contained in SDTF signals must also be decoded by the epigenome in a stimulus-specific manner, to allow controlled plasticity in cellular epigenetic states in response to environmental encounters. The mechanisms and biophysical principles that generate distinct epigenomes in response to different SDTF signaling remain unclear. Here, we develop and analyze stochastic models of nucleosome accessibility to study how SDTF signals alter the epigenome dynamics. Interestingly the response of our epigenome model to SDTF signals helps us to predict the cooperativity of genome-scale nucleosome in vivo. Two alternative but reasonable hypotheses on the cooperativity of parameters in nucleosome unwrapping steps were experimentally tested by ATAC sequencing. On the genome-scale, the location of SDTF binding is a predictor of nucleosome accessibility since the epigenome dynamics depends on SDTF binding sites differently under cooperative and non-cooperative parameters. We could compare our numerical results to experimental measurements to test our prediction. Our work proposes a framework that allows a predictive understanding of how nucleosomes respond to SDTF signaling at specific genomic locations to produce chromatin alterations in health and disease conditions.