High-Throughput Mutational Analysis of Six Self-Cleaving Ribozymes
Faculty Mentor Information
Eric Hayden
Abstract
Ribozymes are RNA molecules that have the ability to form complex structures and perform catalytic biochemical functions. Using a recently developed high-throughput sequencing based biochemical assay to detect self-cleavage, we will conduct comprehensive a mutational analysis of six ribozymes (HDV, CPEB3, hatchet, hammerhead III, twister, hairpin). These ribozymes all exhibit 5’ self-cleavage and range from 45-78nt. DNA libraries have been designed to synthesize all of the single and double mutants for each ribozyme. Quality control has been conducted for the transcription, reverse transcription/template switching and the Illumina adapter PCR. Specifically, the proposed research will assess the biochemical function of all of the wildtype, single and double mutants for each of the ribozymes resulting in ~106,000 unique sequences. This data will then be analyzed using custom Python scripts that determine the effect of each mutation on the ribozyme cleavage activity. Using the data collected from the single and double mutants we will be able to infer the mutational interactions (pair-wise epistasis) exhibited in all six ribozymes. This data will be used toward the development of models that predict fitness effects needed for evolutionary forecasting.
High-Throughput Mutational Analysis of Six Self-Cleaving Ribozymes
Ribozymes are RNA molecules that have the ability to form complex structures and perform catalytic biochemical functions. Using a recently developed high-throughput sequencing based biochemical assay to detect self-cleavage, we will conduct comprehensive a mutational analysis of six ribozymes (HDV, CPEB3, hatchet, hammerhead III, twister, hairpin). These ribozymes all exhibit 5’ self-cleavage and range from 45-78nt. DNA libraries have been designed to synthesize all of the single and double mutants for each ribozyme. Quality control has been conducted for the transcription, reverse transcription/template switching and the Illumina adapter PCR. Specifically, the proposed research will assess the biochemical function of all of the wildtype, single and double mutants for each of the ribozymes resulting in ~106,000 unique sequences. This data will then be analyzed using custom Python scripts that determine the effect of each mutation on the ribozyme cleavage activity. Using the data collected from the single and double mutants we will be able to infer the mutational interactions (pair-wise epistasis) exhibited in all six ribozymes. This data will be used toward the development of models that predict fitness effects needed for evolutionary forecasting.