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Evolutionary Systems Biology pp 195–224Cite as

Toward a Theory of Multilevel Evolution: Long-Term Information Integration Shapes the Mutational Landscape and Enhances Evolvability

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Part of the book series: Advances in Experimental Medicine and Biology ((volume 751))

Abstract

Most of evolutionary theory has abstracted away from how information is coded in the genome and how this information is transformed into traits on which selection takes place. While in the earliest stages of biological evolution, in the RNA world, the mapping from the genotype into function was largely predefined by the physical–chemical properties of the evolving entities (RNA replicators, e.g. from sequence to folded structure and catalytic sites), in present-day organisms, the mapping itself is the result of evolution. I will review results of several in silico evolutionary studies which examine the consequences of evolving the genetic coding, and the ways this information is transformed, while adapting to prevailing environments. Such multilevel evolution leads to long-term information integration. Through genome, network, and dynamical structuring, the occurrence and/or effect of random mutations becomes nonrandom, and facilitates rapid adaptation. This is what does happen in the in silico experiments. Is it also what did happen in biological evolution? I will discuss some data that suggest that it did. In any case, these results provide us with novel search images to tackle the wealth of biological data.

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Notes

  1. 1.

    This dictum is often attributed to Einstein (e.g., [42]), although he has never said it in this form. Nevertheless, it remains a nice pointer to emphasize that on the one hand, models should not incorporate unnecessary detail, but on the other hand should not overlook (and therewith obscure) essential features of the process modeled.

  2. 2.

    DNA can, in fact, be a catalyst as well, but in the model, we define it as noncatalytic as it is in present-day systems.

  3. 3.

    In this model, we do not distinguish + strands and − strands.

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Acknowledgements

I thank my (former) students, in particular Nobuto Takeuchi, Anton Crombach, Otto Corderro, and Thomas Cuypers. I reviewed their work in this chapter, and I thoroughly enjoyed working with them! I also thank my longtime collaborator Ben Hesper for his strong conceptual support.

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Authors and Affiliations

  1. Theoretical Biology and Bioinformatics Group, Utrecht University, Padualaan 8, 3584CH, Utrecht, The Netherlands

    Paulien Hogeweg

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  1. Paulien Hogeweg
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Correspondence to Paulien Hogeweg .

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  1. University of Exeter, Prince of Wales Road, Exeter, EX4 4SB, Devon, United Kingdom

    Orkun S. Soyer

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Hogeweg, P. (2012). Toward a Theory of Multilevel Evolution: Long-Term Information Integration Shapes the Mutational Landscape and Enhances Evolvability. In: Soyer, O. (eds) Evolutionary Systems Biology. Advances in Experimental Medicine and Biology, vol 751. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3567-9_10

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