  Standing genetic variation provides a rich reservoir of potentially useful
mutations facilitating the adaptation to novel environments. Experimental
evolution studies have demonstrated that rapid and strong phenotypic responses
to selection can also be obtained in the laboratory. When combined with the
Next Generation Sequencing technology, these experiments promise to identify
the individual loci contributing to adaption. Nevertheless, until now, very
little is known about the design of such evolve and resequencing (E&R) studies.
Here, we use forward simulations of entire genomes to evaluate different
experimental designs that aim to maximize the power to detect selected
variants. We show that low linkage disequilibrium in the starting population,
population size, duration of the experiment and the number of replicates are
the key factors in determining the power and accuracy of E&R studies.
Furthermore, replication of E&R is more important for detecting the targets of
selection than increasing the population size. Using an optimized design
beneficial loci with a selective advantage as low as s=0.005 can be identified
at the nucleotide level. Even when a large number of loci are selected
simultaneously, up to 56% can be reliably detected without incurring large
numbers of false positives. Our computer simulations suggest that, with an
adequate experimental design, E&R studies are a powerful tool to identify
adaptive mutations from standing genetic variation and thereby provide an
excellent means to analyze the trajectories of selected alleles in evolving
populations.
