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Large programs of dynamic gene expression, like cell cyles and circadian rhythms, are controlled by a relatively small “core” network of transcription factors and post-translational modifiers, working in concerted mutual regulation. Recent work suggests that system-independent, quantitative features of the dynamics of gene expression can be used to identify core regulators. We introduce an approach of iterative network hypothesis reduction from time-series data in which increasingly complex features of the dynamic expression of individual, pairs, and entire collections of genes are used to infer functional network models that can produce the observed transcriptional program. The culmination of our work is a computational pipeline, I terative N etwork H ypoth e sis Re ductio n from T emporal Dynamics (Inherent dynamics pipeline), that provides a priority listing of targets for genetic perturbation to experimentally infer network structure. We demonstrate the capability of this integrated computational pipeline on synthetic and yeast cell-cycle data. 

During infections with the malaria parasitesPlasmodium vivax, patients exhibit rhythmic fevers every 48 h. These fever cycles correspond with the time the parasites take to traverse the intraerythrocytic cycle (IEC). In otherPlasmodiumspecies that infect either humans or mice, the IEC is likely guided by a parasite-intrinsic clock [Rijo-Ferreiraet al.,Science368, 746–753 (2020); Smithet al.,Science368, 754–759 (2020)], suggesting that intrinsic clock mechanisms may be a fundamental feature of malaria parasites. Moreover, becausePlasmodiumcycle times are multiples of 24 h, the IECs may be coordinated with the host circadian clock(s). Such coordination could explain the synchronization of the parasite population in the host and enable alignment of IEC and circadian cycle phases. We utilized an ex vivo culture of whole blood from patients infected withP. vivaxto examine the dynamics of the host circadian transcriptome and the parasite IEC transcriptome. Transcriptome dynamics revealed that the phases of the host circadian cycle and the parasite IEC are correlated across multiple patients, showing that the cycles are phase coupled. In mouse model systems, host–parasite cycle coupling appears to provide a selective advantage for the parasite. Thus, understanding how host and parasite cycles are coupled in humans could enable antimalarial therapies that disrupt this coupling.