Modeling gene induction
National Institute Of Diabetes And Digestive And Kidney Diseases
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Abstract
In collaboration with Stoney Simons, I have developed a biophysical theory for steroid-mediated gene expression in the presence of various factors. Experiments have found that the dose-response curve for gene expression closely follows a Michaelis-Menten function and that factors can alter both the maximum value and location of half maximum of the function. We showed theoretically that this highly stringent constraint can only occur in a sequence of reactions if factors downstream of receptor-steroid binding interact weakly. The theory can then make precise predictions on the mechanisms and site of action of these cofactors. We used the theory to design a novel competition assay to predict the mechanisms and relative positions of the two cofactors and have applied it to several different factors. We have now augmented the theory to steroid-mediated gene repression and to explaining partial agonist and antagonist action. Thus far, we have validated our theory by making predictions on how cofactors should influence the amount of gene product produced. With my fellow Antoine Coulon, I have started a collaboration with NCI investigator Dan Larson to attempt to reconcile the theory with single cell imaging data. By analyzing data from experiments where two reporters are inserted into an exon and intron in the same gene, we have been able to demonstrate that splicing and termination are independent stochastic processes. I have also collaborated with Gordon Hager to analyze the dynamics of large scale chromatin interactions in response to glucocorticoid pulsing.
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