Progress Report Yeast cell cycle regulatory networkWe have completed our initial study that was funded, in part, by this award, and a manuscript (see below) iscurrently in press at Nature. The central finding is that the bulk of the periodic transcription programcontinues to be expressed on schedule in B-cyclin mutant cells that are arrested at the Gl/S border by allconventional cell cycle measures. Supported by our mathematical models, we propose that periodic geneexpression during the yeast cell cycle is primarily controlled by a network of sequentially activatedtranscription factors, and that the cyclin/CDK oscillator serves to fine tune network expression. Furthermore,our Boolean models suggest that the transcription factor network can function as a cell cycle oscillator,independent of B-cyclin/CDK activity.We have nearly completed our goal of epitope-tagging the transcription factors (TFs) in our proposed cellcycle transcription factor network (as described above). The ultimate goal for these epitope-taggedtranscription factors is to first examine protein dynamics during cell cycle progression by western blot, andthen to perform ChIP on chip experiments in synchronized cell populations in order to gain temporalinformation on TF-promoter interactions and to identify new TF-promoter interactions that may be shortlived.We have already collected protein dynamics data for 3 of the TFs in our periodic network. We haveobserved that for the TFs examined, protein levels closely mirror the mRNA levels, suggesting that these TFsare constitutively unstable. Our findings thus far validate an underlying assumption of our transcription factornetwork; specifically that TF protein abundance is controlled primarily at the level of transcription. We arepoised to perform the ChIP on chip experiments as soon as we finish our analyses on protein dynamics.We have shown previously that cell populations lose synchrony as the time series experiments progress.Thus, the data collected at any given time point represent a convolution of values from cells spread overdifferent cell cycle phases. We have developed a deconvolution algorithm that allows us to gain a moreprecise quantitative view of transcript and protein dynamics. A manuscript describing our advance is inpreparation.Orlando DA, Lin CY, Bernard A, Wang, J, Socolar, JES, Iversen ES, Hartemink AJ, HaaseSB. 2008 Global control of cell cycle transcription by coupled CDK and network oscillators.Nature. In press.
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