Transgenic C. elegans Overexpressing Gln 5'-tsRNA for Anti-Aging

The patent introduces an intermediary approach by using in silico prediction models and bioinformatics tools as mediators between the sequenced tsRNA fragments and their genomic origins. Instead of directly matching modified mature tRNA sequences to genomes, the system uses computational prediction to identify potential genomic sources, thereby resolving the mismatch caused by post-transcriptional modifications.

The patent creates a computational copy or model of the tRNA gene family structure and modification patterns. By building a predicted tsRNA profile based on known tRNA genes and their expected fragmentation patterns, the system can match observed tsRNAs to their genomic origins without requiring direct sequencing of modified mature tRNAs, thus overcoming the limitations of conventional sequencing methods.

The patent applies preliminary action by first identifying and characterizing tsRNA profiles at different ages in C. elegans before conducting functional experiments. The age-dependent changes in specific tsRNAs (such as Gln5'-tsRNA) are documented and predicted to have anti-aging functions, which then guides subsequent transgenic experiments to test these predictions, thereby preventing loss of critical functional information.

The patent implements feedback by using the observed age-dependent tsRNA expression patterns as feedback information to guide the design of transgenic C. elegans models. The predicted anti-aging function of specific tsRNAs is tested through lifespan experiments, and the results feed back into refining the understanding of tsRNA mechanisms, creating a continuous cycle of hypothesis testing and validation that preserves functional information.