DOI: 10.5061/dryad.j0zpc86m6
title: Data from: Rapid turnover of a pea aphid superclone mediated by thermal endurance in central Chile

description: Global change drivers are imposing novel conditions on Earth's
 ecosystems at an unprecedented rate. Among them, biological invasions and
 climate change are of critical concern. It is generally thought that
 strictly asexual populations will be more susceptible to rapid
 environmental alterations due to their lack of genetic variability and,
 thus, of adaptive responses. In this study, we evaluated the persistence
 of a widely distributed asexual lineage of the alfalfa race of the pea
 aphid, Acyrthosiphon pisum, along a latitudinal transect of approximately
 600 Km in central Chile after facing environmental change for a decade.
 Based on microsatellite markers, we found an almost total replacement of
 the original aphid superclone by a new variant. Considering the
 unprecedented warming that this region has experienced in recent years, we
 experimentally evaluated the reproductive performance of these two A.
 pisum lineages at different thermal regimes. The new variant exhibits
 higher rates of population increase at warmer temperatures, and computer
 simulations employing a representative temperature dataset suggest that it
 might competitively displace the original superclone. These results
 support the idea of a superclone turnover mediated by differential
 reproductive performance under changing temperatures.
description: <em>Sampling and laboratory rearing</em>
 In a previous study [47], <em>A. pisum</em>
 individuals were sampled from alfalfa fields in the spring and summer of
 2017-2018 in central Chile, the same region previously surveyed by Peccoud
 <em>et al.</em> [23] in 2006-2007 (latitude 35 to 40 ºS, see
 [47]). This study showed that there were only two MLGs in this area (named
 APG2 and APG3 in [47]), with 96% of the genotyped individuals belonging to
 APG3 and the remaining 4% to APG2. Clonal lineages were established in the
 laboratory from these two MLG by rearing them separately on broad bean
 plants (<em>Vicia faba</em> L.) inside 4 L transparent plastic
 buckets, kept in a climatic chamber at 20°C (± 0.5°C) with a long
 photoperiod (LD = 16:8) to ensure their sustained parthenogenetic
 reproduction [46, 50]. Five aphids from each lineage were taken before
 performing the experimental procedures on the thermal response (see
 below), and their DNA was extracted to confirm their genetic
 profile. <em>Genetic profiles and secondary
 symbionts assessment</em> Following Peccoud
 <em>et al</em>. [23], we used fifteen highly polymorphic
 genetic markers (microsatellites) to identify MLGs, including the seven
 original markers from [23] and eight additional markers from Nouhaud
 <em>et al.</em> [51] (Table 1). We extracted total genomic
 aphid DNA by the “salting-out” method, using proteinase-K digestion and
 precipitation by ethanol [52]. Then, the DNA was resuspended in ultrapure
 water and set to a concentration of 30 ng/mL. Each locus was amplified
 separately with fluorescent-labeled primers following the same methodology
 performed by Peccoud <em>et al</em>. [23]. The electrophoresis
 of amplified fragments was completed using the same capillary sequencer
 ABI PRISM 3130xl (Applied Biosystems, U.S.A.), and the same laboratory
 set-up. MLG characterization was made after the automatic allele calls
 given by the software GeneMapper (version 3.5 and 3.7, Applera Corp.,
 U.S.A.) and the visual checking of the allele sizes.
 Besides carrying the obligate endosymbiont bacteria
 <em>Buchnera aphidicola, </em>aphids can host a range of
 facultative endosymbionts that can produce diverse phenotypic effects on
 the aphid host, including heat tolerance [32, 49]. Hence, we screened five
 facultative bacterial symbionts commonly reported in <em>A.
 pisum</em> by randomly selecting pea aphid samples (n = 5) from each
 clonal lineage. Aliquots of DNA extracted from live samples of APG2 and
 APG3 lineages were used to amplify diagnostic PCR fragments for
 <em>Spiroplasma</em> (1500 bp), <em>Serratia
 symbiotica</em> (1140 bp), <em>Regiella insecticola</em>
 (840 bp), <em>Rickettsia sp.</em> (600 bp),
 <em>Hamiltonella defensa</em> (480 bp), and <em>B.
 aphidicola</em> (270 bp), the obligate aphid symbiont, used as
 control [42, 43]. The amplification steps were an initial DNA denaturation
 at 94 °C for 5 min, 30 cycles of 94 ºC for 30 sec, 58 ºC for 30 sec, and
 72 ºC for 1 min, and a final extension step at 72 ºC for 5 min. Amplicons
 were separated through electrophoresis in 1.5% agarose gels, using a
 GeneRuler 100 bp Plus DNA Ladder (Thermo Fisher Scientific, Waltham,
 Massachusetts, USA). The presence of each facultative endosymbiont was
 visually identified according to the size of the diagnostic amplicon in
 base pairs (bp) obtained from the DNA of each aphid [46].
 <em>Temperature and heat-shock effects on life-history
 traits</em> To evaluate the performance of
 individuals from APG2 and APG3 lineages following exposure to short and
 extreme heat events, we used an already-established protocol used by
 Montlor <em>et al</em>. [48] and Russell and Moran [53] on the
 pea aphid using two extreme temperatures registered in central Chile
 (<em>i.e.</em> 38 and 42 °C; [36-41]). In brief, 40 to 60
 age-synchronized aphid nymphs of each lineage were separately kept on
 <em>V. faba</em> seedlings in three separated climatized
 chambers at 20ºC (± 0.5°C, LD = 16:8). After 30 min of acclimation, trials
 started by increasing the temperature of two chambers to 38°C and 42ºC
 (heat-shock treatments, heating rate = 0.15 and 0.18 °C/min respectively)
 in the two first chambers respectively, while the third chamber was kept
 with no temperature change (20ºC constant, control). For each treatment,
 the temperature rose for 2 h until the trial temperature was reached. Once
 reached, this temperature was maintained for 4 h and then lowered to 20ºC
 in the next 2 h (total heat challenge time = 8.5 h). After the trials,
 individuals were returned to their original acclimation temperature (20°C
 ± 0.5°C, LD = 16:8) for 48 additional hours to allow for recovery and
 avoid over-manipulation. Subsequently, after checking that all the plants
 were well, surviving aphids were counted to obtain the proportion of
 alive/dead individuals and randomly transferred to new <em>V.
 faba</em> seedlings until they were reproductive adults.
 Furthermore, we replicated the control treatment at constant rearing
 temperatures of 15 and 25ºC (n = 6 individuals per temperature).
 Comparisons of reproductive performance were made by using
 intrinsic growth rates (<em>r<sub>m</sub></em>),
 calculated as a derivation from the Euler-Lotka equation, where
 <em>r<sub>m</sub> = ln
 </em>(<em>R<sub>0</sub></em>)/<em>t</em> (see Birch [54]). Fecundity (<em>R<sub>0</sub></em>) of the survivor nymphs was measured as the number of nymphs produced by each focal individual aphid in a lapse of ten days since the birth of its first nymph since this period generally comprises 95% of the total progeny of an aphid [55]. The developmental time (<em>t</em>), in turn, was measured as the number of days elapsed from the focal individual's birth to the birth of its first nymph. <em>R<sub>0</sub></em><sub> </sub>and <em>t</em> were recorded individually for the maximum number of survivors after the trials, for each MLG and heat challenge combination. To summarize, five experimental treatments were used: three constant acclimation temperatures (15, 20, and 25 °C) and two heat-shock temperatures (38 and 42 °C), totaling 154 individual measures of <em>r<sub>m</sub></em>, a consistent number given the clonal nature of these aphid lineages (see [56]).
description: <em>Data analysis</em> Since the
 MLGs used in this study came from the same region previously surveyed by
 Peccoud <em>et al. </em>[23], a Neighbor-Joining (NJ) tree of
 MLGs was built with the MLGs found in this study and those found by
 Peccoud <em>et al. </em>[23] using the seven original
 microsatellite markers to make both studies comparable. NJ tree was
 constructed based on a distance matrix of allele shared distances
 (D<sub>AS</sub>) with bootstrapping of 1000 replicates and
 computed by the software Populations v1.2.31 [57]. To
 analyze and compare the intrinsic growth rate of each lineage within their
 thermal niche, we fitted a linear model after a visual diagnostic of the
 data using constant acclimation temperature and MLG as independent
 variables and intrinsic growth rate as dependent variable. Then, predicted
 values of <em>r<sub>m</sub></em> were used to show
 how detected differences in <em>r<sub>m</sub></em>
 between genotypes could be translated into an ecologically relevant
 scenario. We assessed how daily population growth and cumulative
 population size are comparatively predicted to change as a function of
 mean diurnal temperatures (08:00 – 18:00 h). This time range was selected
 to better capture the influence of heat-temperature episodes recorded in
 the field. First, we obtained temperature data at hourly intervals for the
 Quinta Normal weather station (33°25’S, 70°42’W) in Santiago for the years
 2018, 2019, and 2020, sourced from the Chilean Agricultural Research
 Institute (https://agrometeorologia.cl/, data downloaded on 12 May 2022).
 We chose this locality because the effects of thermal change are
 representative of central Chile [44], this location shows a marked
 seasonality and it is a centered spot considering the wide latitudinal
 distribution of the pea aphid along central Chile. Temperature was
 converted into Kelvin degrees (adding 273°) and then returned to the
 Celsius scale to avoid possible confounding effects of below-zero
 temperatures. Then, predicted
 <em>r<sub>m</sub></em> based on these thermal
 conditions were separately converted into daily population growth for APG2
 and APG3, and subsequently into cumulative population size over a
 three-year period (1096 days in total, considering one leap year). For
 simplicity, calculations assume that initial population sizes were
 identical for both genotypes and negative
 <em>r<sub>m</sub></em> predicted from the linear
 regressions were set to zero (<em>i.e.,</em> aphids are
 assumed not to die due to cold, which is likely realistic during the
 growth period of aphid populations). On the other hand, to estimate how
 different MLG responded to the heat-shock treatment, we performed a
 multiple regression including rm as the dependent variable, genotype as a
 categorical factor, and heat-shock temperature as a covariable.
description: Script and data for: Martel et al. "Rapid turnover of a pea aphid
 superclone mediated by thermal endurance in central Chile"
 (submitted). Contains 6 files: (1) Martel et al_SupercloneTurnover.R - R
 script for statistical analysis and figures. (2) dataset_xSM.xlsx -
 original experimental dataset. Variables: \- n.sample: Mark of the
 experimental individual (internal use). Some individuals are marked as NA
 ("not applicable"), since they were identified and measured in a
 second experimental round. However, this is not crucial for the
 experiment. \- Temp.trial: Experimental temperature (15, 20, 25 constant
 temperature; 38, 42 heat shock) \- Gen: Genotype of each experimental
 individual (APG2 or APG3). \- Edad: Age of each experimental individual in
 days since birth. \- Tiempo.gen: Time between birth of experimental
 individual and the birth of its first nymph, in days. \- N.crias: Total
 number of alive nymphs births to the 10th day since the birth of the 1st
 nymph. (3) dataset_xSM.csv - experimental dataset in .csv format, to
 facilitate straightforward manipulation. Variables: \- n.sample: Mark of
 the experimental individual. Some individuals are marked as NA ("not
 applicable"), since they were identified and measured in a second
 experimental round. However, this is not crucial for the experiment. \-
 Temp.trial: Experimental temperature (15, 20, 25 constant temperature; 38,
 42 heat shock) \- Gen: Genotype of each experimental individual (APG2 or
 APG3). \- Edad: Age of each experimental individual in days since birth.
 \- Tiempo.gen: Time between birth of experimental individual and the birth
 of its first nymph, in days. \- N.crias: Total number of alive nymphs
 births to the 10th day since the birth of the 1st nymph. (4)
 microsatellites_A.pisum_Chile.xlsx - representative microsatellite genetic
 profiles Variables: \- SampleName: Mark of each sample (internal use). \-
 MLG: Multi-Locus Genotype. \- Columns C - AF: evaluated loci, two alleles
 each (111775; 114782; 117294; 118775, 18777, 126104; 127526, and 128001
 from. Ap1; Ap13; Ap17; Ap18; Ap4; Ap5 and Ap6 from Peccoud et al. 2008,
 Molecular Ecology). \* Columns marked as "x" represent the 2nd
 allele for each locus.\ \* Highlighted cells in yellow in locus 114782 for
 APG1 (see Martel et al. 2020, Ecology and Evolution) is the only mutation
 of this MLG with APG2 = Ap2. (5) Temp_2018_2020.csv - Air temperature data
 for several localities in Chile for 2018 - 2020, with 1 h resolution (3
 years) obtained from (data downloaded
 on 12 May 2022). File in Zenodo repository. Variables: \- Tiempo UCT-4
 (V1): Date and hour of air temperature measurement. \- Columns 2 - 9 (V2 -
 V9): Name of Chilean localities (meteorological stations) from north
 (Arica) to south (Puerto Montt). In this work only air temperature for
 Santiago (5th column - V5) was used. \* "Not available data for the
 cells containing "NA". (6) Readme.txt - this file