Schuh, L. | Search bioRxiv

bioRxiv2019

Domain model explains propagation dynamics and stability of K27 and K36 methylation landscapes

Chromatin states must be maintained during cell proliferation to uphold cellular identity and genome integrity. Inheritance of histone modifications is central in this process. However, the histone modification landscape is challenged by incorporation of new unmodified histones during each cell cycle and the principles governing heritability remain unclear. Here, we take a quantitative computational modeling approach to describes propagation of K27 and K36 methylation states. We measure combinatorial K27 and K36 methylation patterns by quantitative mass spectrometry on subsequent generations of histones. Using model comparison, we reject active global demethylation and invoke the existence of domains defined by distinct methylation endpoints. We find that K27me3 on pre-existing histones stimulates the rate of de novo K27me3 establishment, supporting a read-write mechanism in timely chromatin restoration. Finally, we provide a detailed, quantitative picture of the mutual antagonism between K27 and K37 methylation, and propose that it stabilizes epigenetic states across cell division.

systems biology↗

bioRxiv2019

Gene networks with transcriptional bursting recapitulate rare transient coordinated expression states in cancer

SUMMARYNon-genetic transcriptional variability at the single-cell level is a potential mechanism for therapy resistance in melanoma. Specifically, rare subpopulations of melanoma cells occupy a transient pre-resistant state characterized by coordinated high expression of several genes. Importantly, these rare cells are able to survive drug treatment and develop resistance. How might these extremely rare states arise and disappear within the population? It is unclear whether the canonical stochastic models of probabilistic transcriptional pulsing can explain this behavior, or if it requires special, hitherto unidentified molecular mechanisms. Here we use mathematical modeling to show that a minimal network comprising of transcriptional bursting and interactions between genes can give rise to rare coordinated high states. We next show that although these states occur across networks of different sizes, they depend strongly on three (out of seven) model parameters and require network connectivity to be [≤] 6. Interestingly, we find that while entry into the rare coordinated high state is initiated by a long transcriptional burst that also triggers entry of other genes, the exit from it occurs through the independent inactivation of individual genes. Finally, our model predicts that increased network connectivity can lead to transcriptionally stable states, which we verify using network inference analysis of experimental data. In sum, we demonstrate that established principles of gene regulation are sufficient to describe this new class of rare cell variability and argue for its general existence in other biological contexts.

systems biology↗