Next-generation sequencing reveals how RNA catalysts evolve from random space

Catalytic RNAs are attractive objects for studying molecular evolution. To understand how RNA libraries can evolve from randomness toward highly active catalysts, we analyze the original samples that led to the discovery of Diels–Alderase ribozymes by next-generation sequencing. Known structure-activity relationships are used to correlate abundance with catalytic performance. We find that efficient catalysts arose not just from selection for reactivity among the members of the starting library, but from improvement of less potent precursors by mutations. We observe changes in the ribozyme population in response to increasing selection pressure. Surprisingly, even after many rounds of enrichment, the libraries are highly diverse, sug-gesting that potential catalysts are more abundant in random space than generally thought. To high-light the use of next-generation sequencing as a tool for in vitro selections, we also apply this tech-nique to a recent, less characterized ribozyme selection. Making use of the correlation between sequence evolution and catalytic activity, we predict mutations that improve ribozyme activity and validate them biochemically. Our study reveals principles underlying ribozyme in vitro selections and provides guidelines to render future selections more efficient, as well as to predict the conservation of key structural elements, allowing the rational improvement of catalysts