Degree
Doctor of Philosophy (PhD)
Department
Biological Sciences
Document Type
Dissertation
Abstract
tRFs, a diverse and abundant class of small non-coding RNAs, are increasingly recognized for their regulatory roles in gene expression. Although tRFs are known to bind RNA-binding proteins and influence processes such as translation, stress responses, and RNA silencing, the biological significance and mechanisms of tRF:mRNA interactions remain only partially understood, especially compared to well-studied regulatory RNAs like microRNAs. It is still unclear how much tRFs modulate gene expression through direct RNA–RNA interactions and whether these interactions follow traditional microRNA-like pathways or other mechanisms. This thesis presents an integrated bioinformatics approach to systematically identify and analyze candidate tRF:mRNA interactions across the human transcriptome. We analyzed CLIP-seq libraries, focusing on chimeric reads to reveal physical interactions between tRFs and mRNAs. These results were combined with novel tRF prediction tools and analysis of 5′ phosphate sequencing (5′ P-seq) data to connect tRF binding to specific mRNA cleavage sites, supporting the discovery of potential functional interactions. A core hypothesis of this work is that some tRFs can hybridize with target mRNAs to form tRNA-like secondary structures that may be recognized and processed by the tRNA endonuclease RNase P. To test this, we assessed how well predicted tRF:mRNA hybrids match known tRNA features and whether they correspond to transcriptome-wide RNA cleavage patterns. Our analyses identify many candidate tRF:mRNA pairs with properties suggestive of guided RNA cleavage, potentially linked to cellular stress. Overall, the findings support a model in which tRFs serve as adaptable post-transcriptional regulators through RNA–RNA interactions that extend beyond traditional microRNA pathways. This research deepens understanding of tRF biology by introducing a novel paradigm for tRF function and lays the foundation for future experimental studies of tRF-driven gene regulation.
Date
9-9-2026
Recommended Citation
Eldondeti, Mahmoud F., "From RNA Processing to Gene Regulation: Bioinformatic Identification of RNase P-mediated mRNA Control" (2026). LSU Doctoral Dissertations. 7203.
https://repository.lsu.edu/gradschool_dissertations/7203
Committee Chair
Anastasios Vourekas
LSU Acknowledgement
1
LSU Accessibility Acknowledgment
1
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