Data from: Mapping a systematic ribozyme fitness landscape reveals a frustrated evolutionary network for self-aminoacylating RNA

Molecular evolution can be conceptualized as a walk over a 'fitness
landscape', or the function of fitness (e.g., catalytic activity)over
the space of all possible sequences. Understanding evolution requires
knowing the structure of the fitness landscape and identifying the viable
evolutionary pathways through the landscape. However, the fitness
landscape for any catalytic biomolecule is largely unknown. The evolution
of catalytic RNA is of special interest because RNA is believed to have
been foundational to early life. In particular, an essential activity
leading to the genetic code would be the reaction of ribozymes with
activated amino acids, such as5(4H)-oxazolones, to form aminoacyl-RNA.
Here we combine in vitro selection with a massively parallel kinetic assay
to map a fitness landscape for self-aminoacylating RNA, with nearly
complete coverage of sequence space in a central 21-nucleotide region. The
method (SCAPE: sequencing to measure catalytic activity paired with in
vitro evolution) shows that the landscape contains three major ribozyme
families (landscape peaks). An analysis of evolutionary pathways shows
that, while local optimization within a ribozyme family would be possible,
optimization of activity over the entire landscape would be frustrated by
large valleys of low activity. The sequence motifs associated with each
peak represent different solutions to the problem of catalysis, so the
inability to traverse the landscape globally corresponds to an inability
to restructure the ribozyme without losing activity. The frustrated nature
of the evolutionary network suggests that chance emergence of a ribozyme
motif would be more important than optimization by natural selection.