All multicellular organisms embed endogenous circadian oscillators or clocks that rhythmically regulate a wide variety of processes in response to daily environmental cycles. Previous molecular studies using rhythmic mutants for several model systems have identified a set of genes responsible for rhythmic activities and illustrated the molecular mechanisms underlying how disruptions in circadian rhythms are associated with the sort of aberrant cell cycling. However, the wide use of these forward genetic studies is impaired by a limited number of mutations that can be identified or induced only in a single genome, limiting the identification of many other conserved or non-conserved clock genes. Genetic linkage or association mapping provides an unprecedented glimpse into the genome-wide scanning and characterization of genes underlying circadian rhythms. The implementation of sophisticated statistical models into genetic mapping studies can not only identify key clock genes or clock quantitative trait loci (cQTL) but also, more importantly, reveal a complete atlas of the genetic control mechanisms constituted by gene interactomes. Here, we introduce and review an advanced statistical mechanics framework for coalescing all possible clock genes into intricate but well-organized interaction networks that regulate rhythmic cycles. The application of this framework to widely available mapping populations will reshape and further our understanding of the genetic signatures behind circadian rhythms for an enlarged range of species including microbes, plants, and humans.
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