Project Summary/Abstract Genetically identical cells in the same environment can have large individual differences in gene expression. This “single-cell variability” in gene expression diversifies cell types during development, contributes to chemotherapeutic resistance in cancer cells, and hinders the production of pure cell types in reprogramming protocols. Although single-cell variability is an important property of gene expression in development and disease, the sequence features of promoters and the epigenetic features of chromosomes that predict a gene’s single-cell variability are unknown. To address this gap, we propose to develop a high-throughput technology that measures the single-cell variability of different classes of promoters in diverse chromosomal environments. We propose to integrate transgenes into thousands of locations across the genome and measure the resulting single-cell variability of transgene expression from all locations in parallel. These data will allow us to leverage existing epigenomic maps to identify the features of chromosomal environments that amplify or dampen single-cell variability in gene expression. We propose to apply this technology to multiple cell types and with transgenes carrying diverse promoters. The resulting data will be analyzed with a framework separates the independent contributions of promoters and chromosomal environments to single-cell variability, and also quantifies any interactions between specific promoters and chromosomal environments that impact single-cell variability. Our goal in developing this technology is to understand the properties of the genome that control the single-cell variability of mRNA expression.