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Hight-throughput technologies of functional genomics have revolutionized the dissection of gene expression regulation during development & pathology. However, most of the available genome-wide approaches have traditionally been focusing on the steady-state snapshot of gene expression, which overlooks the dynamic complexity of gene expression regulation that is achieved via different layers of post-transcriptional regulation. Through a set of overlapping processes, post-transcriptional regulation of gene expression achieves an essential spatiotemporal control of protein abundance & functionality, not only through synthesis but also through localization & decay. The structural & functional architecture of the Drosophila central & peripheral nervous systems provide a unique opportunity to model the events & processes of post-transcriptional regulation. While candidate-based studies have revealed important mechanisms of post-transcriptional regulation of gene expression via RNA processing, localization and decay, a more global genome-wide view of such events is still scarce. This is mostly due to the lack of availability of techniques that allow in vivo isolation of cell type-specific RNA for downstream analysis in combination with other approaches addressing the different aspects of post-transcriptional regulation. A method that has been employed to address some of those limitations over the past two decades is called TU-tagging. This method depends on the metabolic tagging of nascent transcripts by a uridine analogue in a cell type-specific manner by exposing UPRT-expressing-cell(s) of interest to 4-thiouracil (4TU). TU-tagging suffers from major specificity limitations due to endogenous pathways of 4-thiouracil (4TU) incorporation. We developed an alternative method, named EC-tagging, to overcome such limitations, which yielded more robust & highly specific isolation of cell type-specific RNA. The sensitivity and specificity of EC-tagging are demonstrated by obtaining cell type-specific gene expression data from intact Drosophila larvae, including transcriptome data from a small population of central brain neurons. This has led to the identification of previously uncharacterized ppk-expressing neurons in the Drosophila mushroom bodies without any need to enrich for such neurons via physical dissection. We also used EC-tagging to profile the transcriptome of the multidendritic (md) sensory neurons of the Drosophila peripheral nervous system. Traditionally, it has been a technical challenge to isolate RNA from these neurons without potentially altering gene expression due to their complex morphology and interconnected microenvironments. In addition to the fact that we further confirmed the sensitivity of EC-tagging in purifying cell type-specific RNA, we were able to identify two genes that encode RNA-binding proteins (RBPs) that play a role in regulating the arborization of dendrites in the multidendritic (md) sensory neurons. Knocking down the poly(A) polymerase Hiiragi and the translation regulator Hephaestus caused significant defects in dendrite arborization. This work provides a technical framework in which combining efficient & specific metabolic tagging of nascent transcripts with high-throughput genomic technologies can be used to profile RNA regulation & metabolism in small subpopulation of cells, including those whose structures render them not amenable to physical isolation.

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