Identification of Factors Involved in 18S Nonfunctional Ribosomal RNA Decay and a Method for Detecting 8-oxoguanosine by RNA-Seq
Authors
Limoncelli, Kelly A.Faculty Advisor
Melissa J. MooreAcademic Program
NeuroscienceUMass Chan Affiliations
RNA Therapeutics InstituteDocument Type
Doctoral DissertationPublication Date
2017-12-18Keywords
biochemistrydeep-sequencing
neurodegenerative disease
quality control
ribosome
RNA biology
RNA damage
RNA-Seq
structural biology
translation
yeast
Biochemistry
Bioinformatics
Genetics
Molecular Biology
Nucleic Acids, Nucleotides, and Nucleosides
Structural Biology
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Show full item recordAbstract
The translation of mRNA into functional proteins is essential for all life. In eukaryotes, aberrant RNAs containing sequence features that stall or severely slow down ribosomes are subject to translation-dependent quality control. Targets include mRNAs encoding a strong secondary structure (No-Go Decay; NGD) or stretches of positively-charged amino acids (Peptide-dependent Translation Arrest/Ribosome Quality Control; PDTA/RQC), mRNAs lacking an in-frame stop codon (Non-Stop Decay; NSD), or defective 18S rRNAs (18S Nonfunctional rRNA Decay; 18S NRD). Previous work from our lab showed that the S. cerevisiae NGD factors DOM34 and HBS1, and PDTA/RQC factor ASC1, all participate in the kinetics of 18S NRD. Upon further investigation of 18S NRD, our research revealed the critical role of ribosomal protein S3 (RPS3), thus adding to the emerging evidence that the ribosome senses its own translational status. While aberrant mRNAs mentioned above can occur endogenously, damaging agents, such as oxidative stress or UV irradiation, can negatively affect the chemical integrity of RNA. Such lesions could lead to translation errors and ribosome stalling. However, current tools to monitor the fate of damaged RNA are quite limited and only provide a low-resolution picture. Therefore, we sought to develop a deep-sequencing method to detect damaged RNA, taking advantage of reverse transcriptase's ability to insert a mutation across a damaged site. Using oxidized RNA as a model damaged RNA, our preliminary data showed increased G>T mutations in oxidized RNA. This method provides the foundation for future work aimed at understanding how cells deal with damaged RNA.DOI
10.13028/M2MM5TPermanent Link to this Item
http://hdl.handle.net/20.500.14038/32329Rights
Licensed under a Creative Commons licenseDistribution License
http://creativecommons.org/licenses/by/4.0/ae974a485f413a2113503eed53cd6c53
10.13028/M2MM5T
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