Gene flow favours local adaptation under habitat choice in ciliate microcosms

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1 SUPPLEMENTARY Brief Communication INFORMATION DOI: /s In the format provided by the authors and unedited. Gene flow favours local adaptation under habitat choice in ciliate microcosms Staffan Jacob 1,2 *, Delphine Legrand 1, Alexis S. Chaine 1,3, Dries Bonte 4, Nicolas Schtickzelle 2, Michèle Huet 1 and Jean Clobert 1 1 Station d Ecologie Théorique et Expérimentale, CNRS UMR5321, Moulis, France. 2 Earth and Life Institute, Biodiversity Research Centre, Université Catholique de Louvain, 1348 Louvain-la-Neuve, Belgium. 3 Institute for Advanced Studies in Toulouse, Toulouse School of Economics, Toulouse, France. 4 Terrestrial Ecology Unit, Department of Biology, Ghent University, B-9000 Ghent, Belgium. * jacobstaffan@gmail.com Nature Ecology & Evolution Macmillan Publishers Limited, part of Springer Nature. All rights reserved.

2 Supplementary material Gene flow favours local adaptation under habitat choice in ciliate microcosms Staffan Jacob* 1,2, Delphine Legrand 1, Alexis S. Chaine 1,3, Dries Bonte 4, Nicolas Schtickzelle 2, Michèle Huet 1, Jean Clobert 1 Nature Ecology and Evolution * Corresponding author 1 Station d Ecologie Théorique et Expérimentale du CNRS UMR5321, Evolutionary Ecology Group, 2 route du CNRS, Moulis, France 2 Université Catholique de Louvain, Earth and Life Institute, Biodiversity Research Centre, Croix du Sud 4, L , 1348 Louvain-la-Neuve, Belgium 3 Institute for Advanced Studies in Toulouse, Toulouse School of Economics, 21 allée de Brienne, Toulouse, France 4 Ghent University, Terrestrial Ecology Unit, Department Biology, K.L. Ledeganckstraat 35, B-9000 Ghent, Belgium Staffan Jacob: jacobstaffan@gmail.com; Delphine Legrand: delphine.legrand@sete.cnrs.fr; Alexis S Chaine: alexis.chaine@sete.cnrs.fr; Dries Bonte: Dries.Bonte@UGent.be; Nicolas Schtickzelle: nicolas.schtickzelle@uclouvain.be; Michèle Huet: michele.huet@sete.cnrs.fr; Jean Clobert: jean.clobert@sete.cnrs.fr;

3 Figure S1: Thermal niche of T. thermophila. The main graph shows the thermal niche of a population initially inoculated with 10 genotypes differing in their thermal niche, maintained for 2 weeks at 23 C (~40 generations: 6-10h doubling time at 23 C leading to 33 to 56 generations) to allow populations to approach an evolutionary equilibrium. Dots correspond to the measured growth rate of independent population replicates. Inset panel shows the density distribution of thermal optimums of the 10 genotypes. Growth rate per hour was quantified at every 4 C from 11 to 39 C, while the upper limit of the niche (i.e. 43 C) was set to 0 without being properly measured since 43 C is known as a lethal temperature in this species (Hallberg et al. 1995). Genetically variable population Growth Growth rate rate Thermal optimums of genotypes (density distribution) Optimum Temperature

4 Figure S2: Experimental designs to test for a) temperature-dependent habitat choice and b) consequences of habitat choice for local adaptation. (a) Genetically variable populations initially placed in central patches (40000 cells/ml) were allowed to disperse for 24 hours. Temperature in the central patch was set at either 23 C or 35 C, connected to one 23 C patch and one 35 C patch by 6cm long corridors. Single patch systems were kept either at 23 C or 35 C for 24 hours as controls. Fitness of cells from each patch at the upper margin of the species thermal niche was quantified through growth rate in fresh media at 35 C (see Methods). (b) Genetically variable populations maintained at 35 C for 6 weeks (~250 generations: 2-5h doubling time at 35 C leading to 200 to 300 generations; 5% weekly transfer to fresh media) received dispersers once a week who i) chose a 35 C patch (habitat matching), ii) did not perform habitat choice (random dispersal by pipetting a random subset from populations kept at 23 C), or iii) chose a 23 C patch (only the two main treatments are illustrated here for clarity).

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6 Figure S3: Intra-patch variability of cell phenotype [SD of size (in µm)] after dispersal occurred in the habitat choice experiment. Controls without dispersal (grey), cells that chose a 35 C habitat (red), cells that chose a 23 C habitat (blue). Cell size was quantified using automated digital analysis of pictures taken under dark field microscopy (Pennekamp & Schtickzelle 2013) using ImageJ software (version 1.47, National Institutes of Health, USA, Shown are standard box and whisker plots.

7 Figure S4: Local versus foreign estimation of local adaptation. In addition to quantifying adaptation to local conditions as the growth rate at 35 C, we estimated local adaptation following Kawecki & Ebert (2004) and Blanquart et al as the growth rate at 35 C of individuals from experimental populations at 35 C that received immigrants minus the growth rate at 35 C of individuals originating from control populations without immigration and maintained at 23 C (i.e. local versus foreign for each population). Mean ± SE of local adaptation of 12 replicates are shown. a) Local adaptation increased through time when dispersal entailed habitat choice towards the niche margin (Table S1), and did not occur under random dispersal (Table S1). b) Local adaptation increased regardless of whether immigrants were cells that chose to disperse toward a 35 C habitat, or did not disperse but rather stayed in a 35 C habitat (Table S1). c) Local adaptation remained unchanged or even decreased when populations received immigrants consisting of cells that chose a 23 C habitat.

8 Figure S5: Home versus away estimation of local adaptation at the end of the experiment (growth rate at 35 C of individuals from experimental populations at 35 C that received immigrants minus the growth rate of these individuals transferred in a 23 C patch). Mean ± SE of local adaptation of 12 replicates at the end of the experiment are shown. Local adaptation tended to be negative under random dispersal (Student t-test compared to 0: t=- 1.92; df=23; p=0.068), while it increased under habitat choice (F 1,94 =47.85; p<0.001) and decreased when immigrants consisted of cells that chose a 23 C habitat (F 1,94 =20.81; p<0.001). Local adaptation Habitat choice (Dispersers 23 to 35 C) Random dispersal Disp 35 to 35 C Resi 35 C Resi 23 C Disp 23 to 23 C Disp 35 to 23 C

9 Figure S6: Population densities after 6 weeks under the different dispersal treatments. Random dispersal treatment in grey, choice of a 35 C patch in red, choice of a 23 C patch in blue. Shown are standard box and whisker plots. Final population density (cells/ml)

10 Table S1: Summary of changes of growth rate and local adaptation index through time in each dispersal treatment. Time effects were computed as the slope of growth rate over the six weekly time points for growth rate at 35 C, while it represents the difference between initial and final state for the local adaptation index. Main time and dispersal level effects were tested while removing the interaction from the models when not significant. Analyses were performed using linear mixed models (lme, nlme R-package) with growth rate or local adaptation index as a dependent variable, time, dispersal level and their interaction as continuous explanatory variables, and population as a random factor. Growth rate at 35 C Local adaptation Dispersal treatments F df p F df p Random dispersal Time , , Dispersal level , , Time*dispersal level , , Choice of a 35 C patch Dispersers 23 to 35 C Time ,59 < ,23 <0.001 Dispersal level , , Time*dispersal level , , Residents 35 C Time ,59 < ,23 <0.001 Dispersal level , , Time*dispersal level , , Dispersers 35 to 35 C Time ,58 < ,22 <0.001 Dispersal level , , Time*dispersal level , , Choice of a 23 C patch Dispersers 35 to 23 C Time , , Dispersal level , , Time*dispersal level , , Residents 23 C Time ,59 < , Dispersal level , , Time*dispersal level , , Dispersers 23 to 23 C Time ,59 < ,23 <0.001 Dispersal level , , Time*dispersal level , ,

11 Figure S7: Example of three-patch microcosms for temperature-dependent habitat choice in Tetrahymena thermophila. Temperature in the central and neighbouring patches were set to either 23 C (core of the thermal niche of the genetically variable populations; Fig S1) or 35 C (upper thermal niche margin) using dry bath systems (H2O3 Dry Bath Incubator; Coyote Bioscience) placed in incubators. Patches in the dry baths were set at either 23 or 35 C while temperature in patches outside the dry baths was defined by incubator temperature (3 replicates with dry bath at 35 C and incubator at 23 C, and 3 replicates with dry bath at 23 C and incubator at 35 C).

12 Figure S8: Relationship between cell density quantified through picture analysis and absorbance at 550nm. Each dot correspond to an independent population. Absorbance (550nm) Cell density (k cells/ml) Table S2: Cells from control populations maintained at 23 C showed no change in fitness at 35 C through time. Growth rate at 35 C p Random dispersal , Habitat choice (23 to 35 C) , No dipersal , F df

13 Table S3: List of the genotypes used in this study. Identities of genotypes (code) and identifying numbers at the Tetrahymena Stock Centre, Cornel (TSC ID) are shown. Code TSC ID Sampling done by City isolation date reference D1 SD01546 Doerder FP Ridgway 21/08/02 Zufall et al Mol.Ecol D2 SD01547 Doerder FP Ridgway 21/08/02 Zufall et al Mol.Ecol D3 SD01548 Doerder FP Warren 01/06/03 Zufall et al Mol.Ecol D4 SD01549 Doerder FP Warren 01/06/03 Zufall et al Mol.Ecol D6 SD01551 Doerder FP Warren 01/06/03 Zufall et al Mol.Ecol D10 SD01557 Doerder FP Alstead 22/07/09 Zufall et al Mol.Ecol D12 SD01556 Doerder FP Guys Mills 26/08/08 Zufall et al Mol.Ecol D13 SD01555 Doerder FP Guys Mills 26/08/08 Zufall et al Mol.Ecol D15 SD01560 Doerder FP Antrim 24/07/09 Zufall et al Mol.Ecol D17 SD01561 Doerder FP Antrim 24/07/09 Zufall et al Mol.Ecol

14 Discussion of candidate explanatory processes The five candidate processes to explain the effects we show in this study are drift, selection, plasticity, mutation, and spatial segregation through habitat choice: Stochasticity/drift: Effective population size and potentially associated increased genetic variability is expected to favour local adaptation. However, during the local adaptation experiment (Supplementary Figure 2b) all populations started with similar population sizes and were all connected (i.e. by receiving a fixed number of immigrants every week). Stochasticity/drift due to differences in effective population sizes, with either increased genetic variability or on the contrary random loss of genotypes, thus cannot explain the consistent effects of dispersal treatments in this experiment. During the habitat choice experiment (Supplementary Figure 2a), all systems were initially inoculated with ~ cells (40000 cells/ml; see Supplementary Figure 2), but cells initially inoculated in the central patch of the 3-patch systems can choose to disperse to an empty patch. This led to a dilution of these individuals in the 3-patch systems compared to single patch systems ( no dispersal ; Supplementary Figure 2a). Connectivity consequently did not lead to an increase of population density and associated portfolio effect in this study. Since the same initial genetically variable populations were inoculated in single and connected patches (i.e. same standing genetic variability), the likelihood for a 35 C lottery ticket is therefore higher in isolated compared to connected patches in our experiment. Higher fitness at 35 C for cells staying or joining 35 C thus cannot be explained by a stochastic process. Selection: In the habitat choice experiment (Supplementary Figure 2a), rapid selection of the better-fitted genotypes in 35 C patches is expected to lead to an increase of fitness at 35 C in those patches. However, fitness at 35 C of cells maintained for 24h in 35 C isolated patches ( no dispersal ; Supplementary Figure 2a) did not significantly differ from fitness of cells maintained at 23 C (grey points in Fig 1). This result shows that selection cannot explain the increased fitness at 35 C of cells that stay or join 35 C patches in the habitat choice experiment. Consequently, cells choosing a 35 C patch in the 3-patch choice systems rather showed increased growth rate at 35 C because they preferred to stay in or join the temperature that matched their thermal performance when they had the opportunity to disperse actively. Plasticity: Environmentally induced plasticity of thermal performance during development may lead to increased fitness at 35 C even without selection or segregation through habitat choice. However, plasticity in thermal performance should then lead to an increase of fitness

15 at 35 C also in isolated 35 C patches during the habitat choice experiment (Supplementary Figure 2a). The absence of a significant difference in fitness at 35 C between isolated 35 C and 23 C patches (grey points in Fig 1) thus strongly suggest that plasticity in thermal performance is limited in this system. Furthermore, dispersal with habitat choice is not expected to generate local adaptation (sensus local versus foreign or home versus away) if the phenotypic specialization involves only plastic, non-heritable traits (see for instance 1 ). The effects of dispersal treatments on local adaptation in this study thus cannot be explained by potential plasticity of thermal performance. Mutations: We cannot rule out the hypothesis that rare mutations occurred during long-term local adaptation experiment (~250 generations). However, the appearance of new mutations is unlikely to explain the highly consistent effects of dispersal treatments that we showed here, especially since focal populations were initially inoculated with equal cell densities and received similar levels of gene flow, ensuring that treatment effects have low probability to result from drift or differences in mutational input rates. Spatial segregation through habitat choice: Active dispersal decisions that depend on individual phenotype and the environmental context have previously been demonstrated in the ciliated protozoa Tetrahymena thermophila. For instance, using 3-patch systems similar to the ones used in the present paper, a previous study 2 demonstrated that cells of isolated genotypes are able to disperse either toward or away from kin depending on their cooperation tendency. Furthermore, this species uses social information gathered by immigrants about ecological conditions in neighbouring patches to adjust dispersal decisions 3. Here we show that individuals that either staid or joined the thermal niche margin had significantly higher growth rates at 35 C than those that either staid in or joined 23 C patches. Such differences did not occur when cells had no opportunity to disperse (grey points in Fig 1). Our results provide strong evidence for segregation of genotypes through habitat choice given the background of active dispersal decisions in this species, the higher fitness of cells in the conditions they chose and the lack of evidence for alternative hypotheses. Furthermore, variability in cell size within a patch was reduced when cells had the opportunity to disperse compared to when no dispersal was allowed (isolated patches versus connected patches: F 1,45 =82.46; p<0.001; Fig S3). Given the known cell size differences between genotypes in this species 4,5, the decrease in cell size variability within patches likely indicates phenotypedependent sorting of individuals through habitat matching during dispersal.

16 Together with the evidence against alternative explanations exposed above, our results thus provide solid evidence for spatial segregation of standing genetic variability through a habitat choice process. References 1. Jacob, S., Bestion, E., Legrand, D., Clobert, J. & Cote, J. Habitat matching and spatial heterogeneity of phenotypes: implications for metapopulation and metacommunity functioning. Evol. Ecol. 29, (2015). 2. Chaine, A. S., Schtickzelle, N., Polard, T., Huet, M. & Clobert, J. Kin-based recognition and social aggregation in a ciliate. Evolution 54, (2010). 3. Jacob, S., Chaine, A. S., Schtickzelle, N., Huet, M. & Clobert, J. Social information from immigrants: multiple immigrant-based sources of information for dispersal decisions in a ciliate. J. Anim. Ecol. 84, (2015). 4. Fjerdingstad, E. J., Schtickzelle, N., Manhes, P., Gutierrez, A. & Clobert, J. Evolution of dispersal and life history strategies Tetrahymena ciliates. BMC Evol. Biol. 7, 133 (2007). 5. Jacob, S. et al. Cooperation-mediated plasticity in dispersal and colonization. Evolution 70, (2016).

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