|M.Sc Student||Farkash Keren|
|Subject||Characterization of Gene Expression Variation in Yeast Cell|
|Department||Department of Physics||Supervisors||Professor Naama Brenner|
|Professor Erez Braun|
|Full Thesis text|
Phenotypic variation is known to exist in a population of cells having identical genomic content. Many sources generate noise creating the overall variation. In order to study this phenotypic variation, we chose to characterize the variation in the expression of a single regulated gene in a yeast population (S.cerevisiae). Cells were grown in chemostat in order to ensure control conditions over many generations, allowing measurement of gene expression distribution dynamics and steady state. We used experimental analysis and Monte-Carlo simulations in order to reveal the predominant sources that shape the gene expression variation.
In our research we found that steady state presents a broad distribution with an exponential tail. Growth under different environmental conditions, obligating different metabolisms, shows the same steady state characteristics. The observed dynamics under perturbations display an asymmetric time scale response for different initial states. The asymmetry at intermediate time scales (~2-10 generations) underlines the existence of information transfer through generations and stresses the significance in a population approach. Balance between two population forces has been offered as the main population mechanism for determining protein content. The first is the production force, the creation of protein as reflected in the exponential slope of the distribution. This force contains the biochemical noise which has long been the focus of many studies. The second is the dilution force, division of cytoplasm and protein inheritance. On the basis of this view we built a simple synchronized population simulation. Different theoretical production and dilution forces have been simulated. All simulations reached steady state, part of them show a broad exponential tail distribution at steady state similar to the observed one. On the other hand none of the simulations show the asymmetric dynamics observed in the experiments. Thus, a synchronized population having simple balance between two forces can not reflect the observed phenomenon and other population factors must be added. Both experiments and simulations indicate that the main features of the gene expression distribution are largely determined by population effects and are less sensitive to the intracellular biochemical noise.