Systems Biology of the Circadian Clock Output Network
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The circadian clock is an evolutionarily conserved time-keeping mechanism that, through the regulation of rhythmic gene expression, coordinates the physiology of an organism with daily environmental cycles. Because virtually all aspects of human physiology and behavior are linked to the clock, abnormalities in the circadian system are associated with a wide range of diseases, including metabolic syndrome that affects up to 40% of adults over the age of 50. Thus, knowing what genes are regulated by the clock, and the mechanisms of this regulation, are necessary to understand clock-associated diseases. Furthermore, clock-controlled transcripts peak at all possible phases of the circadian cycle; however, we lack a basic understanding of what controls phase. To begin to understand the circadian output gene network, we identified the direct targets of the core clock component and transcription factor (TF) WCC in Neurospora crassa, and found an overrepresentation of TFs in the roughly 200 direct targets. Among these first tier TFs, ADV-1 was shown to be robustly rhythmic, defective in clock-controlled development, and closely linked to the downstream metabolic network. We also discovered that in addition to WCC, several first tier TFs bind to the adv-1 promoter, and that ADV-1 feeds back to bind to the promoters of these same TFs. These same TFs also bind and potentially co- regulate each other, and the direct targets of ADV-1. In addition, our analysis of the direct targets of ADV-1 revealed enrichment for genes involved in development, metabolism, and transcription control. Together, these data suggest a complex regulatory network linking WCC to ADV-1 and to downstream developmental and metabolic genes. Our data also suggest that one function of this network is to generate distinct temporal dynamics of gene expression critical to robust rhythms in biological functions. By combining computational and experimental biology, we will directly test this idea in our specific aims. We will determine how the upstream network sculpts the rhythms in ADV-1 (Aim1), and how the ADV-1 downstream network generates distinct temporal patterns of gene expression (Aim 2). We will combine the upstream and downstream network models to predict and validate which genetic changes will selectively alter the phase of expression of specific metabolic pathways that are rhythmically controlled by ADV-1 (Aim 3). As such, one major outcome of this work is the exciting potential to develop interventions to diminish the serious effects of disruption of the clock on human disease, such as metabolic syndrome associated with shift work.