Small self-cleaving ribozymes are catalytic RNAs that cleave their phosphodiester backbone rapidly and site-specifically, without the assistance of proteins. Their catalytic properties make them ideal targets for applications in RNA pharmaceuticals and bioengineering. Consequently, computational pipelines that predict or design thousands of self-cleaving ribozyme candidates have been developed. Traditional experimental techniques for verifying the activity of these putative ribozymes, however, are low-throughput and time intensive. High-throughput (HT) pipelines that employ next-generation sequencing (NGS) analyze the activity of these thousands of ribozymes simultaneously. Until recently, the application of these HT pipelines has been limited to studying all single and double mutants of a select representative ribozyme. Unfortunately, this prevents the exploration of candidates having different lengths, circular permutations, and auxiliary stem-loops. Moreover, pipelines that analyze ribozymes en masse often include transcription of non-native flanking sequences that preclude accurate assessment of the intrinsic rate of ribozyme self-cleavage. To overcome these limitations, we developed a HT pipeline, "Cleavage High-Throughput Assay (CHiTA)", which employs NGS and massively parallel oligonucleotide synthesis (MPOS) to characterize ribozyme activity for thousands of candidates in a scarless fashion. Herein, we describe detailed strategies and protocols to implement CHiTA to measure the activity of putative ribozymes from a wide range of ribozyme classes.
Keywords: CHiTA; High-throughput assay; Next-generation sequencing; Ribozyme.
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