The circadian clock is an endogenous molecular oscillator with a period of approximately 24 hours that is present nearly ubiquitously in bacterial fungal, plant, and animal species. External stimuli, such as light or temperature, are entrainment cues that ensure that the circadian oscillator is in precise resonance with the local environment. Self-sustained rhythms are maintained by clock network architecture through multiple, interlocked transcriptional feedback loops and extensive post-translational regulation. The robust circadian network coordinates biochemical, physiological, and behavioral responses with environmental rhythms to optimize resource allocation and increase fitness. We propose to deploy a combination of genetics, biochemistry, functional genomics, and computational approaches to identify the components and molecular mechanisms that underlie the multilayered clock network. Areas that we will gain direct insight into through the work proposed in this grant include the fundamental sensory pathways for environmental input into the clock, circadian network dynamics, and mechanistic control of outputs. By screening a comprehensive transcription factor library with core clock promoters, we have identified putative elements that mediate the perception and transcriptional responses to temperature inputs into the clock. We will explore their roles in temperature- associated phenomenon (entrainment, gating, and compensation) in relation to the circadian oscillator. Also, recent work in the laboratory has identified biochemical properties of key transcription factors, TOC1 and LUX, which provide important advances in our understanding of their roles within the clock. We propose to further characterize the mechanistic underpinnings of their activities through biochemical and molecular approaches, as well as explore their function on a genomic level to understand their role in the control of clock outputs. Finally, while robustness in networks is partially built on redundancy of components, this redundancy hinders our ability to identify new factors and understand their function through genetic perturbations. To circumvent this obstacle, we have developed a new computational approach for identifying functional specificity in multi-gene families by mining microarray data. We propose to expand this approach on all Arabidopsis transcription factor families and validate the approach on preliminary candidates affecting the circadian network. This new tool can be broadly applied to any organism with microarray expression data to identify perturbations that can separate the function of closely related homologs or members of a multi-gene family. Continued efforts such as the work proposed here and the on-going research in our laboratory to elucidate the molecular mechanisms of the plant circadian clock will complement similar analyses in other systems, ultimately translating our understanding of circadian biology to impact the treatment of human circadian disorders.