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The predictability of molecular evolution during functional innovation
Author(s) -
Diana Blank,
Luise Wolf,
Martin Ackermann,
Olin Silander
Publication year - 2014
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.1318797111
Subject(s) - predictability , evolutionary biology , biology , affect (linguistics) , phenotype , protein expression , expression (computer science) , computational biology , molecular evolution , gene , genetics , phylogenetics , computer science , psychology , communication , physics , quantum mechanics , programming language
Determining the molecular changes that give rise to functional innovations is a major unresolved problem in biology. The paucity of examples has served as a significant hindrance in furthering our understanding of this process. Here we used experimental evolution with the bacterium Escherichia coli to quantify the molecular changes underlying functional innovation in 68 independent instances ranging over 22 different metabolic functions. Using whole-genome sequencing, we show that the relative contribution of regulatory and structural mutations depends on the cellular context of the metabolic function. In addition, we find that regulatory mutations affect genes that act in pathways relevant to the novel function, whereas structural mutations affect genes that act in unrelated pathways. Finally, we use population genetic modeling to show that the relative contributions of regulatory and structural mutations during functional innovation may be affected by population size. These results provide a predictive framework for the molecular basis of evolutionary innovation, which is essential for anticipating future evolutionary trajectories in the face of rapid environmental change.

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