The predictability of molecular evolution during functional innovation
| Autor: | Martin Ackermann, Diana Blank, Olin K. Silander, Luise Wolf |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Population
Molecular Sequence Data Adaptation Biological Computational biology Biology Evolution Molecular 03 medical and health sciences 0302 clinical medicine Molecular evolution Escherichia coli Predictability education skin and connective tissue diseases Gene 030304 developmental biology Genetics Population Density 0303 health sciences Experimental evolution education.field_of_study Multidisciplinary Base Sequence Models Genetic Population size Sequence Analysis DNA Biological Sciences Phenotype Genetics Population Mutation DNA Intergenic sense organs Directed Molecular Evolution 030217 neurology & neurosurgery Metabolic Networks and Pathways |
| Zdroj: | Proceedings of the National Academy of Sciences of the United States of America PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|