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Predicting evolution

Nature Ecology & Evolution volume 1, Article number: 0077 (2017) Cite this article

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Abstract

The face of evolutionary biology is changing: from reconstructing and analysing the past to predicting future evolutionary processes. Recent developments include prediction of reproducible patterns in parallel evolution experiments, forecasting the future of individual populations using data from their past, and controlled manipulation of evolutionary dynamics. Here we undertake a synthesis of central concepts for evolutionary predictions, based on examples of microbial and viral systems, cancer cell populations, and immune receptor repertoires. These systems have strikingly similar evolutionary dynamics driven by the competition of clades within a population. These dynamics are the basis for models that predict the evolution of clade frequencies, as well as broad genetic and phenotypic changes. Moreover, there are strong links between prediction and control, which are important for interventions such as vaccine or therapy design. All of these are key elements of what may become a predictive theory of evolution.

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Figure 1: Clonal interference is a common mode of evolution.
Figure 2: Predictability in evolution (schematic).
Figure 3: From fitness models to evolutionary predictions.
Figure 4: Information gain and time horizon of predictions.

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Acknowledgements

We thank M. Desai, I. Gordo, M. Łuksza, T. Mora and A. Nourmohammad for comments on the manuscript. M. Desai, M. Łuksza and A. Nourmohammad also provided important input to illustrations. This work has been partially supported by Deutsche Forschungs-gemeinschaft grant SFB 680 (M.L.), Wellcome Trust grant 098051 (V.M.), and European Research Council ERCStG 306312 (A.M.W.).

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  1. Ville Mustonen

    Present address: †Present address: Department of Biosciences, University of Helsinki, PO Box 65, 00014, Finland.,

Authors and Affiliations

  1. Institute of Theoretical Physics, University of Cologne, 50937 Cologne, Germany

    Michael Lässig

  2. Wellcome Trust Sanger Institute, Cambridge, CB10 1SA, UK

    Ville Mustonen

  3. Laboratoire de Physique Théorique CNRS, Ecole Normale Supérieure, 75005 Paris, France

    Aleksandra M. Walczak

Authors
  1. Michael Lässig
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  2. Ville Mustonen
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  3. Aleksandra M. Walczak
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Contributions

All authors developed concepts and wrote the paper. Authors are listed in alphabetical order.

Corresponding authors

Correspondence to Michael Lässig, Ville Mustonen or Aleksandra M. Walczak.

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Lässig, M., Mustonen, V. & Walczak, A. Predicting evolution. Nat Ecol Evol 1, 0077 (2017). https://doi.org/10.1038/s41559-017-0077

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