The central question of this proposal is: how are changes in cell state regulated at the transcriptomic and epigenetic level? I will tackle this question using an integrated computational and experimental approach with the T helper cell system as my model. The Th system consists of a naïve precursor cell type, and four main differentiated cell types that have some capacity to interconvert, known as plasticity. The experiments will be designed to measure both entire transcriptomes and single mRNAs by single molecule RNA-FISH.(i) Quantifying genetic switches. On a genome-wide scale, what is the distribution of gene expression levels in the Th cell types? Do genes have two discrete expression levels (on and off) in terms of mRNAs per cell or a continuous distribution of expression levels? How do epigenetic marks correlate with expression levels? We will use genome-wide RNA-seq and epigenetic ChIP-seq experiments on homogeneous populations of cells coupled with new computational methods.(ii) The molecular nature of the genetic switch. What is the hierarchy and kinetics of molecular events that drive gene expression changes during differentiation and plasticity? Using highly resolved timecourse experiments to profile individual cell generations, we will unravel the temporal order of regulation by transcription factors, microRNAs and epigenetic factors using RNA-seq and ChIP-seq experiments. We will integrate the data computationally to infer new regulatory interactions.(iii) How genetic switches drive cell type switches. Which transcription factors directly regulate cytokines, the phenotypic readout of Th cells? Are the kinetics of these interactions graded or switch-like? What is the extent of stochastic cell-to-cell variation? We will validate predicted transcription factor-cytokine interactions and quantify levels of proteins and mRNA in single cells with fluorescence microscopy experiments, modelling this data probabilistically.