Trade-offs constrain the improvement of performance of multiple traits simultaneously. Such trade-offs define Pareto fronts, which represent a set of optimal individuals that cannot be improved in any one trait without reducing performance in another. Surprisingly, experimental evolution often yields genotypes with improved performance in all measured traits, perhaps indicating an absence of trade-offs at least in the short term. Here we densely sample adaptive mutations in Saccharomyces cerevisiae to ask whether first-step adaptive mutations result in trade-offs during the growth cycle. We isolated thousands of adaptive clones evolved under carefully chosen conditions and quantified their performances in each part of the growth cycle. We too find that some first-step adaptive mutations can improve all traits to a modest extent. However, our dense sampling allowed us to identify trade-offs and establish the existence of Pareto fronts between fermentation and respiration, and between respiration and stationary phases. Moreover, we establish that no single mutation in the ancestral genome can circumvent the detected trade-offs. Finally, we sequenced hundreds of these adaptive clones, revealing new targets of adaptation and defining the genetic basis of the identified trade-offs.
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All code used in this manuscript is deposited in GitHub. The source code for computing these fitness estimates can be found at https://github.com/barcoding-bfa/fitness-assay-python. The source code for variant calling and annotation can be found at https://github.com/liyuping927/DNAscope-variants-calling.
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We thank A. Agarwala, G. Kinsler, C. McFarland and D. Fisher for discussions. We thank J. Blundell, K. Geiler-Samerotte, O. Kolodny, S. Kryazhimskiy, C. Li, F. Rosenzweig and S. Venkataram for comments on the manuscript. We thank all members in the Sherlock and Petrov labs for helpful suggestions. Y.L. is supported by the Stanford Center for Computational, Human and Evolutionary Genomics Predoctoral Fellowship. The work was supported by NIH grants (nos. R01 GM110275 and R35 GM131824), a NASA grant (no. NNX17AG79G to G.S.) and a NIH grant (no. R35GM118165 to D.A.P.).
The authors declare no competing interests.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Figs. 1–5.
Barcode counts of all lineages during the course of evolution.
Fitness measurements of isolated clones.
Genetic basis of genome-wide sequenced clones.
Viability measurement of FPK1 mutants and wild-type strains.
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Li, Y., Petrov, D.A. & Sherlock, G. Single nucleotide mapping of trait space reveals Pareto fronts that constrain adaptation. Nat Ecol Evol 3, 1539–1551 (2019). https://doi.org/10.1038/s41559-019-0993-0
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