Open Collections

Robustness and evolvability

Banff International Research Station for Mathematical Innovation and Discovery

Robustness and evolvability are two quintessentially systems properties for which a formal evolutionary perspective is essential. The relationship between robustness and evolvability is discussed using two quite different metaphors and hence classes of model (Trotter & Masel 2010). In recombining populations, robustness allows the accumulation of cryptic genetic variants, whose phenotypic effects may first become apparent under decanalizing stress, and later become genetically assimilated after recombination brings polygenic allele frequencies above a threshold. When recombination can be ignored, whether for single genes or whole asexual systems, then populations can instead be visualized in a high- dimensional space, where each node is a genotype and edges represent mutations between them. Evolvability always depends on the quantity and quality of available heritable phenotypic variants. In genotype space, quantity arguments focus on robustness allowing a population to “spread” across more nodes, and access more future genotypes via new mutations. Quality arguments demonstrate evolution not towards nodes of higher mutational “neighborhood richness”. For example, present errors in transcription, splicing, translation, folding and/or binding can mimic future mutations (Rajon & Masel 2011). This allows selection to preview the phenotypes of neighboring genotypes, even before those genotypes appear by mutation. We find that for polygenic traits, neighborhood richness, rather than population spread, is responsible for high evolvability (Rajon & Masel 2013).\\r\\n\\r\\nReferences\\r\\n\\r\\nMasel J, Trotter MV. (2010) Robustness and evolvability, Trends in Genetics, 26: 406–414. Rajon E, Masel J. (2013) Compensatory evolution and the origins of innovations, Genetics,\\r\\n193:1209-1220.\\r\\nRajon E, Masel J. (2011) Evolution of molecular error rates and the consequences for\\r\\nevolvability, PNAS, 108: 1082-1087.\\r\\nBrettner LM, Masel J. (2012) Protein stickiness, rather than number of functional protein- protein interactions, predicts expression noise and plasticity in yeast, BMC Systems Biology, 6:128.

Mathematics; Biology and other natural sciences; Systems theory; control; Mathematical biology

video/mp4

Author affiliation: University of Arizona

2014-08-07

Attribution-NonCommercial-NoDerivs 2.5 Canada

http://hdl.handle.net/2429/49618

Unreviewed

http://creativecommons.org/licenses/by-nc-nd/2.5/ca/