ABSTRACT (as submitted in the original application) Many of the molecular mechanisms underlying well-characterized robust and rapidly inducible transcriptional responses are shared among other systems, so we use hormone-induced transcriptional responses to study gene regulation. We use rapid kinetic regulation and perturbation of transcription cascades, transcription factors, and cofactors to identify key mechanisms, genes, and regulatory elements that are critical for hormone signaling. Transcription factors act as activators or repressors and interface with a constellation of accessory cofactors to regulate distinct steps in the transcription to coordinate gene expression, but the molecular functions of the vast majority of transcription factors remain uncharacterized. We use molecular genomics assays and computational methods to classify transcription factors by their molecular function, as opposed to broad activator and repressor classes, in order to understand the context specificity of gene regulation. We found that the estrogen receptor transcription factor may compete with other transcription factors for limiting cofactors to mediate estrogen-induced repression. We will develop genetic tools to uncouple activation and repression to test various models of repression, such as squelching cofactors from repressed genes. The genes and regulatory elements that are downstream of the first wave of transcriptional response are critical for propagating regulatory cascades. We generate high resolution, genome-wide time course data of regulatory element activity and nascent transcription upon stimulation of differentiation processes. We construct mechanistically interpretable networks to identify effector genes and regulatory elements that are critical for signaling in regulatory cascades. Our research reveals basic principles and rules that govern transcription factor specificity in order to understand how genetics, nutrition, and environmental factors contribute to variation in transcriptional programs that can lead to disease states or ineffective therapies.