UC San Diego

High-throughput sequencing has given us unprecedented insight into the regulatory networks that govern enhancer selection and transcription in mammalian cells, but many open questions remain as to how the mechanics of transcriptional regulation correspond to biological outputs such as gene expression and downstream signaling. In this dissertation, I address the nature of enhancer selection and transcriptional regulation in the context of CD4+ T cell signaling in two parts. The first study describes an algorithm and database that together enable the use of Global Run-On Sequencing (GRO-Seq) data, an experimental data type that reveals the kinetics of transcription in the nucleus, for high dimensional analysis of enhancers and other transcriptional regulatory units. The tool developed allows for both the quantification of nascent RNA and the integration of other sequencing data types into analysis of GRO-Seq data, thus facilitating the use of GRO-Seq as an experimental assay of transcriptional behavior. The second study looks at enhancers and transcriptional regulation in a particular biological context: activation of CD4+ T cell by ligands of varying affinity. Using flow cytometry as well as several high-throughput sequencing methods, I found that CD4+ T cells reflect the strength of T Cell Receptor signaling both at the population level and the single-cell level, resulting in graded gene expression profiles for a subset of genes crucial for CD4+ T cell activation. Together, these studies represent an advance in our understanding of enhancer biology, particularly in the context of CD4+ T cell activation