2014
DOI: 10.1101/003897
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Intermediate Migration Yields Optimal Adaptation in Structured, Asexual Populations

Abstract: Most evolving populations are subdivided into multiple subpopulations connected to each other by varying levels of gene flow. However, how population structure and gene flow (i.e., migration) affect adaptive evolution is not well understood. Here, we studied the impact of migration on asexually reproducing evolving computer programs (digital organisms). We found that digital organisms evolve the highest fitness values at intermediate migration rates, and we tested three hypotheses that could potentially explai… Show more

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Cited by 4 publications
(3 citation statements)
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“…This situation occurs because the slower fixation of these intermediates might allow for better competitors (from domains of nearer peaks) to arise. In contrast, these more distant peaks become accessible in a structured population due to reduced competitive displacement (16). If some of these distant peaks are also higher, then structured populations are predicted to achieve better fitness and to accumulate more mutations.…”
Section: Resultsmentioning
confidence: 98%
“…This situation occurs because the slower fixation of these intermediates might allow for better competitors (from domains of nearer peaks) to arise. In contrast, these more distant peaks become accessible in a structured population due to reduced competitive displacement (16). If some of these distant peaks are also higher, then structured populations are predicted to achieve better fitness and to accumulate more mutations.…”
Section: Resultsmentioning
confidence: 98%
“…Constant population sizes facilitate analytical calculations, and allowed us to fully quantify the impact of a periodic presence of antimicrobial on resistance evolution, but it will be very interesting to extend our work to variable population sizes [51,52,16,53,54]. Another interesting extension would be to incorporate spatial structure [32,55,56,57] and environment heterogeneity, in particular drug concentration gradients. Indeed, static gradients can strongly accelerate resistance evolution [58,59,60,61], and one may ask how this effect combines with the temporal alternation-driven one investigated here.…”
Section: Context and Perspectivesmentioning
confidence: 99%
“…On rugged fitness landscapes, in contrast, populations must find the best combinations of mutations to adapt, and these combinations may not involve the most individually beneficial mutations. It has long been suggested that spatial structure may facilitate adaptation in this case [Wright, 1932, Kryazhimskiy et al, 2012, Nahum et al, 2015, Van Cleve and Weissman, 2015, Bitbol and Schwab, 2014, Covert III and Wilke, 2014, Cooper and Kerr, 2016, Crona, 2018, although it is controversial whether it actually does so in nature [Coyne et al, 1997].…”
Section: Introductionmentioning
confidence: 99%