ReviewAdvances in experimental medicine and biology2026
Evolution of the Cell-Cycle Clock Models: Biochemical or Transcriptional?
Review in Advances in experimental medicine and biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Models of the central oscillating mechanism of the cell-division cycle have evolved over more than 40 years of investigation across multiple model systems. The initial oscillator models were based on observations from early embryonic systems and suggested that oscillations were driven by a small biochemical feedback loop comprised of mitotic cyclin, cyclin-dependent kinase (CDK) and the ubiquitin ligase complex, anaphase promoting complex/cyclosome (APC/C). The model was expanded to include kinase and phosphatase regulators of CDK (Wee1 and Cdc25) with experiments in Xenopus extracts. Biochemical models were supported by genetic studies in both S. cerevisiae and S. pombe systems where cell-cycle arrests were associated with mutations in the kinases, phosphatases, and ubiquitin ligases of the cell-cycle clock. Mathematical models also supported these biochemical oscillator models and were able to accurately predict the outcome of genetic experiments. Thus, there was no apparent need for new models until work showed that autonomous cell-cycle oscillations continued when mitotic cyclins were deleted in S. cerevisiae. The advent of transcriptomics technologies in the late 1990s revealed the existence of large programs of oscillating gene expression associated with cell-cycle progression. It was further shown that these programs of oscillating gene expression could function autonomously in S. cerevisiae mutants where mitotic cyclins were disrupted and cell-cycle progression was halted. Taken together, these new findings suggested that a gene regulatory network (GRN) may function as the underlying cell-cycle oscillator with CDKs serving primarily as the effectors of these oscillations. Here, we explore the evolution of these models from early biochemical to more contemporary GRN models.
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