A fitness landscape of a gene defines the molecular potential of evolution. This can help us understand the current state of evolution as well as predict unrealized potential. Using deep sequencing to examine mutations in nonessential genes that affect the growth of yeast strains, two studies have generated fitness landscapes and measured the effect of epistatic interactions (see the Perspective by He and Liu). Li et al. generated a library of mutants in a transfer RNA gene, including all single and many double and multiple mutants. The RNA secondary structure was generally predictive of bases under selection. Similarly, Puchta et al. assessed a small nucleolar RNA gene for the fitness effects of individual mutations, which correlated with evolutionary conservation and structural stability. Both studies suggest that epistasis—the combined functional effect—for double substitutions is more often negative than positive. Science , this issue pp. 837 and 840 ; see also p. 769 Between-site epistasis is pervasive in a transfer RNA gene with patterns explained by the structure of the molecule. Fitness landscapes describe the genotype-fitness relationship and represent major determinants of evolutionary trajectories. However, the vast genotype space, coupled with the difficulty of measuring fitness, has hindered the empirical determination of fitness landscapes. Combining precise gene replacement and next-generation sequencing, we quantified Darwinian fitness under a high-temperature challenge for more than 65,000 yeast strains, each carrying a unique variant of the single-copy tRNA CCU Arg gene at its native genomic location. Approximately 1% of single point mutations in the gene were beneficial and 42% were deleterious. Almost half of all mutation pairs exhibited statistically significant epistasis, which had a strong negative bias, except when the mutations occurred at Watson-Crick paired sites. Fitness was broadly correlated with the predicted fraction of correctly folded transfer RNA (tRNA) molecules, thereby revealing a biophysical basis of the fitness landscape.
CITATION STYLE
Li, C., Qian, W., Maclean, C. J., & Zhang, J. (2016). The fitness landscape of a tRNA gene. Science, 352(6287), 837–840. https://doi.org/10.1126/science.aae0568
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