A model-driven discovery process, Computing Life, is used to identify an ensemble of genetic networks that describe the biological clock. A clock mechanism involving the genes white-collar-1 and white-collar-2 (wc-1 and wc-2) that encode a transcriptional activator (as well as a blue-light receptor) and an oscillator frequency (frq) that encodes a cyclin that deactivates the activator is used to guide this discovery process through three cycles of microarray experiments. Central to this discovery process is a new methodology for the rational design of a Maximally Informative Next Experiment (MINE), based on the genetic network ensemble. In each experimentation cycle, the MINE approach is used to select the most informative new experiment in order to mine for clock-controlled genes, the outputs of the clock. As much as 25% of the N. crassa transcriptome appears to be under clock-control. Clock outputs include genes with products in DNA metabolism, ribosome biogenesis in RNA metabolism, cell cycle, protein metabolism, transport, carbon metabolism, isoprenoid (including carotenoid) biosynthesis, development, and varied signaling processes. Genes under the transcription factor complex WCC ( = WC-1/WC-2) control were resolved into four classes, circadian only (612 genes), light-responsive only (396), both circadian and light-responsive (328), and neither circadian nor light-responsive (987). In each of three cycles of microarray experiments data support that wc-1 and wc-2 are auto-regulated by WCC. Among 11,000 N. crassa genes a total of 295 genes, including a large fraction of phosphatases/kinases, appear to be under the immediate control of the FRQ oscillator as validated by 4 independent microarray experiments. Ribosomal RNA processing and assembly rather than its transcription appears to be under clock control, suggesting a new mechanism for the post-transcriptional control of clock-controlled genes.

A diverse array of organisms from bacteria to humans may have evolved the ability to tell time in the presence or absence of external environmental cues. In the lowly bread mould, Neurospora crassa, biomolecular reactions involving the white-collar-1 (wc-1), white-collar-2 (wc-2), and frequency (frq) genes and their products constitute building blocks of a biological clock. Here we use genetic network models to explain quantitatively, from a systems perspective, how these building blocks interact, and how a complex trait like clock oscillation emerges from these interactions. We use a recently developed method of genetic network identification to find an ensemble of oscillating network models quantitatively consistent with available RNA and protein profiling data on the N. crassa clock. Predicted key features of the N. crassa clock system are a dynamically frustrated closed feedback loop, cooperativity in frq gene activation, and/or WC-1/WC-2 protein complex deactivation and substantial posttranscriptional enhancement of wc-1 RNA lifetime. Measuring the wc-1 mRNA lifetime provides a critical test of the genetic networks. (1) and are at the heart of a new systems approach to biology (2). The biological clock (3) provides a prototypical and biologically ubiquitous example of how a complex trait can emerge from the interaction of even a small number of gene regulatory elements. In an experimentally well studied example, the filamentous fungus, Neurospora crassa, and the biomolecular reactions involving the white-collar-1, white-collar-2, and frequency genes and their products constitute building blocks of a biological clock (4). A central open question of systems biology is whether these building blocks are necessary and sufficient to define a circuit or genetic network that oscillates, and how, in quantitative detail, such oscillations emerge from the interactions among these building blocks. Here we use a recently developed method of genetic network identification (5) to find an ensemble of oscillating network models, constituted from wc-1, wc-2, and frq and their products, which is quantitatively consistent with available RNA and protein profiling data on the N. crassa biological clock. The use of genetic networks to integrate diverse experimental information and to predict the behavior of a complex trait, such as the biological clock, provides a new paradigm for quantitative genetics at the molecular level (6).Key features of the genetic network that permit oscillations are: (i) the presence of functional wc-1, wc-2, and frq genes, generating protein products WC-1, WC-2, and FRQ, and the white collar complex (WCC) formed by WC-1 and WC-2; (ii) a closed-feedback loop of the biomolecular reactions in the genetic network, with WCC activating the frq gene 3 the activated frq gene producing frq mRNA 3 frq mRNA producing FRQ protein and 3 FRQ protein deactivating WCC; (iii) dynamical frustration arising in the feedback loop because of WCC's stimulation of the production of FRQ, whereas FRQ induces the deactivation o...

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