Electronic Thesis/Dissertation


Computational Study of Gene Regulatory Networks in Immune System Open Access

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Immune system comprises of many cells and processes that together protect the host against diseases. It is equipped with unique features, including the ability of distinguishing between self and non-self entities, high sensitivity to invading antigens, response in a range of time-scales, and the capability of learning and memory. Underlying these sophisticated functions are genes that regulate each other forming networks. To decipher the gene regulatory networks in the immune system, we employed both top-down and bottom-up approaches. Using the top-down approaches, we studied the global regulation of immune cells by leveraging advanced data mining and machine learning methods. We investigated how intron retention (IR), a novel post-transcriptional regulatory mechanism, mediates global gene regulation in the immune system and its activation process. We demonstrated that the global IR regulation is specific only to adaptive immune cells, but not to innate immune cells. IR, a hallmark of deficiency in splicing, is associated with transcriptional read-through, a deficiency in the polyadenylation step of RNA processing. IR regulation in immune activation is coordinated with the dynamic changes of splicing and polyadenylation effectors. Collectively, our results suggested that adaptive and innate immune systems adopt different strategies in global gene regulation. In the bottom-up approaches, using targeted perturbations, we examined the role of specific genes in cell identity, where the cell’s own lineage is promoted and alternative lineages are suppressed. We identified transcription factors Tcf1 and Runx3 as critical regulators of CD8+ T cell identity.This work contributes to unraveling novel mechanisms of gene regulation in the immune system, deepening our understandings of immune response and immune cell identity, and potentially enhancing our ability to diagnosis and treat diseases in the future.

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