measured the cytoplasmic mRNA level of in yeast and also found an approximate 2-fold increase from late phases to phase
 measured the cytoplasmic mRNA level of in yeast and also found an approximate 2-fold increase from late phases to phase. Next, we characterize the dependance of (43) 0 , 2 . delineate how they are combined to regulate transcription output and noise. In view of gene dosage, a cell cycle is divided into an early stage and a late stage to measured in a mouse embryonic stem cell line. When transcription follows similar kinetics in both stages, and are responsible for mitotic progression, whose transcripts are stable during the interphase, but exhibit a 30-fold increase in degradation in the mitosis phase . In budding yeast, acetylation of histone 3 suppresses transcription activity to buffer changes in DNA dose for expression homeostasis of other genes during DNA replication . During cell division processes, genome duplication involves DNA dosage increase at discrete times in phase, and introduces considerable variations in gene copies [13C15]. Moreover, the time spent between two successive cell-division events , the DNA replication catalyzed by DNA polymerases [16, 17], the variation in transcription kinetics between different cell cycle stages [9, 15, 18], and the partition of molecules between two daughter cells , are all observed to be stochastic and may contribute to cell-to-cell variability in transcript counts. It remains largely unexplored how these random events govern mRNA outputs and their fluctuation among individual cells . In this work, we initiate a mathematical approach by coupling the classical two-state model with cell division cycles to delineate the combined contribution of transcription activities and cell divisions in the variability of transcript counts [4, 6, 20]. In view of gene dosage, a cell cycle is divided into and stages. In each stage, the target gene transits randomly between active and inactive states with constant rates. As usual, we use the mean, the noise, and the noise strength to characterize stochastic gene transcription. For a given random variable ? E[to by and are the mean transcription levels at the two stages. Although > 0. 21-Deacetoxy Deflazacort The transcripts are produced only when the gene is active with a synthesis rate > 0, and are turned over with a degradation rate > 0. Apparently, as the four rates are all assumed to be constants, the transcription described by the model is independent of many important cellular processes such as cell growth and cell division. Actively dividing eukaryote cells go through several stages known collectively as the cell division cycle, including Gap 1 phase (phase, each gene is duplicated into two copies that are transcribed independently in the same cell . During phase, a cell is divided into two daughter cells and residual mRNA molecules are randomly partitioned. Cell division cycle has global effects on mRNA and protein synthesis, and is also an important source of gene expression noise [10C13]. In recent years, many real-time monitoring methods, such as single molecule fluorescent in situ hybridization (smFISH), have been developed to estimate mRNA copy numbers in different cell cycle stages. In mouse embryonic stem cells, nascent Oct4 and Nanog mRNAs were measured in different phases using smFISH method . It was found that the ratio of the average number of mRNA copies in phase and are degraded almost completely before cytokinesis . From the measurements of , we estimated that the median of 21-Deacetoxy Deflazacort cytoplasmic CLB2 mRNA copy numbers is 10 in phase, and 5 in phase. It remains an essential and widely open question to quantify how the transition of cell cycle phases, the variation of DNA content and transcription kinetics in different phases, and the random partition of mRNAs in daughter cells affect the dynamics and noise of gene transcription. Open in a separate window Fig FASLG 1 Coupling gene 21-Deacetoxy Deflazacort transcription with cell cycle.Actively dividing eukaryote cells go through phases in one cell.