Adaptive ratchets and the evolution of molecular complexity
Abstract
Biological systems have evolved to amazingly complex states, yet we do not understand in general how evolution operates to generate increasing genetic and functional complexity. Molecular recognition sites are short genome segments or peptides binding a cognate recognition target of sufficient sequence similarity. Such sites are simple, ubiquitous modules of sequence information, cellular function, and evolution. Here we show that recognition sites, if coupled to a time-dependent target, can rapidly evolve to complex states with larger code length and smaller coding density than sites recognising a static target. The underlying fitness model contains selection for recognition, which depends on the sequence similarity between site and target, and a uniform cost per unit of code length. Site sequences are shown to evolve in a specific adaptive ratchet, which produces selection of different strength for code extensions and compressions. Ratchet evolution increases the adaptive width of evolved sites, accelerating the adaptation to moving targets and facilitating refinement and innovation of recognition functions. We apply these results to the recognition of fast-evolving antigens by the human immune system. Our analysis shows how molecular complexity can evolve as a collateral to selection for function in a dynamic environment.
Additional Information
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license. We thank Rob Phillips for discussions. This work was supported by Deutsche Forschungsgemeinschaft grant CRC 1310 "Predictability in Evolution". Code Availability. All code used to run simulations and produce figures is available in a Github repository: https://github.com/tomroesch/adaptive_ratchets The authors have declared no competing interest.Attached Files
Submitted - 2021.11.18.469165v1.full.pdf
Supplemental Material - media-1.zip
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Additional details
- Eprint ID
- 111974
- Resolver ID
- CaltechAUTHORS:20211122-174116460
- CRC 1310
- Deutsche Forschungsgemeinschaft (DFG)
- Created
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2021-11-22Created from EPrint's datestamp field
- Updated
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2021-11-22Created from EPrint's last_modified field