High-throughput assay and engineering of self-cleaving ribozymes by sequencing
Author(s) -
Shungo Kobori,
Yoko Nomura,
Anh Miu,
Yohei Yokobayashi
Publication year - 2015
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gkv265
Subject(s) - ribozyme , biology , ligase ribozyme , computational biology , synthetic biology , dna sequencing , hairpin ribozyme , genetics , selection (genetic algorithm) , dna , rna , gene , computer science , machine learning
Self-cleaving ribozymes are found in all domains of life and are believed to play important roles in biology. Additionally, self-cleaving ribozymes have been the subject of extensive engineering efforts for applications in synthetic biology. These studies often involve laborious assays of multiple individual variants that are either designed rationally or discovered through selection or screening. However, these assays provide only a limited view of the large sequence space relevant to the ribozyme function. Here, we report a strategy that allows quantitative characterization of greater than 1000 ribozyme variants in a single experiment. We generated a library of predefined ribozyme variants that were converted to DNA and analyzed by high-throughput sequencing. By counting the number of cleaved and uncleaved reads of every variant in the library, we obtained a complete activity profile of the ribozyme pool which was used to both analyze and engineer allosteric ribozymes.
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