Epigenetics and Gene Regulation
A dynamical systems model for predicting gene expression from the epigenome
Gene regulation is an important fundamental biological process involving a number of complex sub-processes that are essential for development and adaptation to the environment. Understanding gene expression patterns has broad scientific and clinical potential, including providing insight into mechanisms of regulatory control and a patient's response to disease or treatment. The regulation of gene expression is managed through a variety of methods, including transcription, post-transcriptional modifications, and epigenetic processes.
In an upcoming paper (arxiv link), we introduce a piece-wise deterministic Markov process to model gene regulation due to epigenetic modification. This model assumes fundamentally that transcription of DNA is (relatively) fast and done at a deterministic rate according to the bound or unbound state of transcription factor binding sites. We assume that binding and unbinding of transcription factors is a (relatively) slow and stochastic process, with propensity proportional to the availability of transcription factor and mediated by epigenetic modification. The result is a dynamic model of protein production which accounts for the epigenetic mechanism of gene regulation.
In addition to predicting gene expression, our model provides a detailed look at the regulatory activity that leads to its prediction. We can therefore provide details about the differential regulatory activity that results from differential epigenetic modification.
This work is in collaboration with Prof. Kord Kober at the University of California, San Francisco, Prof. Timothy Downing at the University of California, Irvine, and Prof. Eric Mjolsness at the University of California, Irvine.