Terminal differentiation is often coupled with permanent exit from the cell cycle, yet it is unclear how cell proliferation is blocked in differentiated tissues. We examined the process of cell cycle exit in Drosophila wings and eyes and discovered that cell cycle exit can be prevented or even reversed in terminally differentiating cells by the simultaneous activation of E2F1 and either Cyclin E/Cdk2 or Cyclin D/Cdk4. Enforcing both E2F and Cyclin/Cdk activities is required to bypass exit because feedback between E2F and Cyclin E/Cdk2 is inhibited after cells differentiate, ensuring that cell cycle exit is robust. In some differentiating cell types (e.g., neurons), known inhibitors including the retinoblastoma homolog Rbf and the p27 homolog Dacapo contribute to parallel repression of E2F and Cyclin E/Cdk2. In other cell types, however (e.g., wing epithelial cells), unknown mechanisms inhibit E2F and Cyclin/Cdk activity in parallel to enforce permanent cell cycle exit upon terminal differentiation.
Heterogeneity in genetic networks across different signaling molecular contexts can suggest molecular regulatory mechanisms. Here we describe a comparative chi-square analysis (CPχ2) method, considerably more flexible and effective than other alternatives, to screen large gene expression data sets for conserved and differential interactions. CPχ2 decomposes interactions across conditions to assess homogeneity and heterogeneity. Theoretically, we prove an asymptotic chi-square null distribution for the interaction heterogeneity statistic. Empirically, on synthetic yeast cell cycle data, CPχ2 achieved much higher statistical power in detecting differential networks than alternative approaches. We applied CPχ2 to Drosophila melanogaster wing gene expression arrays collected under normal conditions, and conditions with overexpressed E2F and Cabut, two transcription factor complexes that promote ectopic cell cycling. The resulting differential networks suggest a mechanism by which E2F and Cabut regulate distinct gene interactions, while still sharing a small core network. Thus, CPχ2 is sensitive in detecting network rewiring, useful in comparing related biological systems.
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