ADAPTATION TO DIFFERENT RATES OF ENVIRONMENTAL CHANGE INCHLAMYDOMONAS

Abstract

We investigate how different rates of environmental change affect adaptive outcomes and dynamics by selecting Chlamydomonas populations for over 200 generations in environments where the rate of change varies. We find that slower rates of environmental change result in end populations that grow faster and pay a lower cost of adaptation than populations that adapt to a sudden change of the same magnitude. We detected partial selective sweeps in adapting populations by monitoring changes in marker frequency in each population. Although populations adapting to a sudden environmental change showed evidence of mutations of large effect segregating early on, populations adapting to slow rates of change showed patterns that were consistent with mutations of relatively small effect occurring at less predictable times. This work suggests that rates of environmental change may fundamentally alter adaptive dynamics and outcomes of adaptation by changing the size and timing of fitness increases. We suggest that using mutations of smaller effect during adaptation may result in lower levels of pleiotropy and historical constraints, which could in turn result in higher fitness by the end of the experiment.K E Y W O R D S : Adaptation, adaptive walks, Chlamydomonas, epistasis, experimental evolution, pleiotropy.

Rate of novel host invasion affects adaptability of evolving RNA virus lineages

“…Previous experimental work on adaptation in directionally changing environments has focused on continuous abiotic environmental variables, such as phosphate or antibiotic concentration. These experiments have demonstrated that more gradual environmental change tends to result in populations that are better adapted to their final environment or less likely to go extinct [8,9,12]. Chlamydomonas populations evolved in environments with increasing phosphate concentrations reached fitter endpoints when the environment changed more gradually [12], and bacterial populations evolved in response to increasing antibiotic concentrations more consistently avoided extinction and reached high endpoint fitness when adapting to gradual change [9].…”

“…These experiments have demonstrated that more gradual environmental change tends to result in populations that are better adapted to their final environment or less likely to go extinct [8,9,12]. Chlamydomonas populations evolved in environments with increasing phosphate concentrations reached fitter endpoints when the environment changed more gradually [12], and bacterial populations evolved in response to increasing antibiotic concentrations more consistently avoided extinction and reached high endpoint fitness when adapting to gradual change [9]. Our results reaffirm the finding that more gradual rates of change tend to result in better-adapted populations, and we demonstrate that this effect holds true for populations responding to change in a patchy biotic environmental variable.…”

“…In a gradually changing environment, the population experiences a series of smaller drops in fitness and may fix a series of smaller effect mutations in response [4][5][6]. The rate of environmental change may affect the likelihood of extinction [7][8][9][10][11], fitness in the final environment [9,12] and which mutations go to fixation [4 -6,9,12,13].…”

The Genetic Basis of Phenotypic Adaptation II: The Distribution of Adaptive Substitutions in the Moving Optimum Model

“…In particular, experimental evolution studies with microbes have almost exclusively employed constant selection regimes. Notable exceptions are provided by Collins and Bell (2004) and Perron et al (2008), but a recent study by Collins and De Meaux (2009) is the first to (partly) resolve the evolutionary dynamics at the genetic level. For the future, we hope that more experiments will include gradual variation in environmental factors.…”

Comment on ''Effects of long-term high CO<sub>2</sub> exposure on two species of coccolithophore'' by Müller et al. (2010)

“…After we do this successfully, we then have to contextualise our results by scaling up, slowing down and adding complications. Here, insights from ecological evolution studies can explain the systematic effects of some simplifications used in laboratory work, such as speeding up environmental change (Collins and de Meaux, 2009), using a stable environment even though we know that most natural environments fluctuate (Lande, 2007), using homogenous environments instead of patchy ones (Rainey and Travisano, 1998), looking at responses to changes in single instead of multiple environmental variables (Barrett et al, 2005), and using single strains rather than communities where groups interact (Rueffler et al, 2006;Collins, 2010).…”