Rapid construction of empirical RNA fitness landscapes.
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.
Howard Hughes Medical Institute and Division of Basic Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, WA 98109-1024, USA.
Jason N
JN
Pitt
Adrian R
AR
Ferré-D'Amaré
D000465:Algorithms; D001483:Base Sequence; D055162:Biocatalysis; D019143:Evolution, Molecular; D005838:Genotype; D009690:Nucleic Acid Conformation; D010641:Phenotype; D017354:Point Mutation; D012313:RNA / Q000378:metabolism; D016337:RNA, Catalytic / Q000737:chemistry / Q000235:genetics* / Q000378:metabolism*; D012641:Selection, Genetic; D017423:Sequence Analysis, RNA
D016337:RNA, Catalytic; D012313:RNA