Decoding RNA metabolism by RNA-linked CRISPR screening in human cells

dc.contributor.advisorSubramaniam, Arvind
dc.contributor.authorNugent, Patrick Joseph
dc.date.accessioned2024-09-09T23:13:27Z
dc.date.issued2024-09-09
dc.date.submitted2024
dc.descriptionThesis (Ph.D.)--University of Washington, 2024
dc.description.abstractRNAs undergo a complex choreography of metabolic processes in human cells that are regulated by thousands of RNA-associated proteins. While individual RNA-associated proteins and their effects on specific RNA metabolic events have been extensively characterized, the full complement of regulators for most RNA metabolic events remain unknown. Here we present a massively parallel RNA-linked CRISPR (ReLiC) screening approach to measure the response of diverse RNA metabolic events to knockout of 2,092 human genes encoding all known RNA-associated proteins. ReLiC screens highlight widespread yet modular interactions between cellular networks regulating splicing, nuclear export, translation, and decay of mRNAs. Isoform-specific ReLiC screens reveal differential regulation of intron retention and exon skipping by SF3b complex subunits. Combining ReLiC with polysome fractionation uncovers translation repression by the trimeric eIF2 initiation complex during nonsense-mediated mRNA decay. ReLiC identifies an unexpected role for GCN1 in suppressing ribosome collisions during treatment with the anti-leukemic drug homoharringtonine. Our work demonstrates ReLiC as a versatile platform for discovering and dissecting regulators of human RNA metabolism.
dc.embargo.lift2029-08-14T23:13:27Z
dc.embargo.termsRestrict to UW for 5 years -- then make Open Access
dc.format.mimetypeapplication/pdf
dc.identifier.otherNugent_washington_0250E_26656.pdf
dc.identifier.urihttps://hdl.handle.net/1773/52126
dc.language.isoen_US
dc.rightsnone
dc.subjectMolecular biology
dc.subjectGenetics
dc.subjectBiochemistry
dc.subject.otherMolecular and cellular biology
dc.titleDecoding RNA metabolism by RNA-linked CRISPR screening in human cells
dc.typeThesis

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