Rapid construction of empirical RNA fitness landscapes.

Publication Type:

Journal Article

Source:

Science (New York, N.Y.), Volume 330, Issue 6002, p.376-9 (2010)

Keywords:

2010, Algorithms, Base Sequence, Basic Sciences Division, Biocatalysis, Center-Authored Paper, Evolution, Molecular, Genotype, Nucleic Acid Conformation, PHENOTYPE, Point Mutation, RNA, RNA, Catalytic, Selection, Genetic, Sequence Analysis, RNA

Abstract:

Evolution is an adaptive walk through a hypothetical fitness landscape, which depicts the relationship between genotypes and the fitness of each corresponding phenotype. We constructed an empirical fitness landscape for a catalytic RNA by combining next-generation sequencing, computational analysis, and "serial depletion," an in vitro selection protocol. By determining the reaction rate constant for every point mutant of a catalytic RNA, we demonstrated that abundance in serially depleted pools correlates with biochemical activity (correlation coefficient r = 0.67, standard score Z = 7.4). Therefore, enumeration of each genotype by deep sequencing yielded a fitness landscape containing ~10(7) unique sequences, without requiring measurement of the phenotypic fitness for each sequence. High-throughput mapping between genotype and phenotype may apply to artificial selections, host-pathogen interactions, and other biomedically relevant evolutionary phenomena.