title: Quantifying gene expression variability arising from randomness in cell division times.
abstract: The level of a given mRNA or protein exhibits significant variations from cell-to-cell across a homogeneous population of living cells. Much work has focused on understanding the different sources of noise in the gene-expression process that drive this stochastic variability in gene-expression. Recent experiments tracking growth and division of individual cells reveal that cell division times have considerable inter-cellular heterogeneity. Here we investigate how randomness in the cell division times can create variability in population counts. We consider a model by which mRNA/protein levels in a given cell evolve according to a linear differential equation and cell divisions occur at times spaced by independent and identically distributed random intervals. Whenever the cell divides the levels of mRNA and protein are halved. For this model, we provide a method for computing any statistical moment (mean, variance, skewness, etcetera) of the mRNA and protein levels. The key to our approach is to establish that the time evolution of the mRNA and protein statistical moments is described by an upper triangular system of Volterra equations. Computation of the statistical moments for physiologically relevant parameter values shows that randomness in the cell division process can be a major factor in driving difference in protein levels across a population of cells.
authors.affiliation: Control Systems Technology, Department of Mechanical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands, D.Antunes@tue.nl.
authors.forename: Duarte
authors.initials: D
authors.lastname: Antunes
authors.forename: Abhyudai
authors.initials: A
authors.lastname: Singh
mesh_terms: D002455:Cell Division / Q000235:genetics / Q000502:physiology; D019295:Computational Biology; D003198:Computer Simulation; D015870:Gene Expression; D008390:Markov Chains; D055641:Mathematical Concepts; D008954:Models, Biological; D015233:Models, Statistical; D011506:Proteins / Q000235:genetics / Q000378:metabolism; D012333:RNA, Messenger / Q000235:genetics / Q000378:metabolism; D013269:Stochastic Processes
chemical_list: D011506:Proteins; D012333:RNA, Messenger