Low concordance of short-term and long-term selection responses in experimental Drosophila populations
| Autor: | Anna Maria Langmüller, Christian Schlötterer |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0106 biological sciences
0301 basic medicine early adaptation Concordance Biology Population and Conservation Genetics 010603 evolutionary biology 01 natural sciences 03 medical and health sciences Genetics Animals Computer Simulation experimental evolution Time point Selection Genetic replicated time series data Set (psychology) Ecology Evolution Behavior and Systematics Selection (genetic algorithm) Experimental evolution Evolve & Resequence Haplotype Term (time) 030104 developmental biology Drosophila melanogaster Haplotypes Evolutionary biology concordance of adaptation Drosophila Drosophila simulans Original Article ORIGINAL ARTICLES Genomic selection |
| Zdroj: | Molecular Ecology |
| ISSN: | 1365-294X |
| Popis: | Experimental evolution is becoming a popular approach to study the genomic selection response of evolving populations. Computer simulation studies suggest that the accuracy of the signature increases with the duration of the experiment. Since some assumptions of the computer simulations may be violated, it is important to scrutinize the influence of the experimental duration with real data. Here, we use a highly replicated Evolve and Resequence study in Drosophila simulans to compare the selection targets inferred at different time points. At each time point, approximately the same number of SNPs deviates from neutral expectations, but only 10% of the selected haplotype blocks identified from the full data set can be detected after 20 generations. Those haplotype blocks that emerge already after 20 generations differ from the others by being strongly selected at the beginning of the experiment and display a more parallel selection response. Consistent with previous computer simulations, our results demonstrate that only Evolve and Resequence experiments with a sufficient number of generations can characterize complex adaptive architectures. |
| Databáze: | OpenAIRE |
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