Circadian oscillations play a fundamental role in many biological processes including cell metabolism and cell cycle. As such, interest in understanding these molecular oscillations has generated an increasingly large collection of circadian omic data. These studies have demonstrated the remarkable plasticity with which the set of oscillating molecular species within a cell are selected. These large shifts in oscillating species are known as circadian reprogramming events. These events have been observed across experimental condition, tissue, and species. While many of these studies have made tissue or condition specific conclusions, a consolidated framework of software tools and a central repository of data has become necessary to answer questions about the orchestration of these reprogramming events.
By combining the largest repository for circadian omic data with improved methods for the detection of circadian oscillation and regulation in omic studies, a model for the transcriptomic organization of circadian rhythms can be identified. Results are presented from a collection of specific reprogramming studies utilizing these new methods, as well as a high through-put analysis of a large collection of comparable transcriptomic datasets from mouse tissue. The identified model can be viewed as a deep hierarchical network of circadian regulation that originates from the core circadian clock to over 95% of oscillating transcripts.
