DOI: 10.5061/dryad.tdz08kq2s
title: Evolutionary consequences of pesticide exposure include transgenerational plasticity and potential terminal investment transgenerational effects

description: Transgenerational plasticity, the influence of the environment experienced
 by parents on the phenotype and fitness of subsequent generations, is
 being increasingly recognised. Human-altered environments, such as those
 resulting from the increasing use of pesticides, may be major drivers of
 such cross-generational influences, which in turn may have profound
 evolutionary and ecological repercussions. Most of these consequences are,
 however, unknown. Whether transgenerational plasticity elicited by
 pesticide exposure is common, and the consequences of its potential
 carry-over effects on fitness and population dynamics remains to be
 determined. Here we investigate whether exposure of parents to a common
 pesticide elicits intra-, inter- and transgenerational responses (in F0,
 F1 and F2 generations) in life-history (fecundity, longevity, and lifetime
 reproductive success-LRS-), in an insect model system, the seed beetle
 Callosobruchus maculatus. We also assessed sex-specificity of the effects.
 We found sex-specific and hormetic intergenerational and transgenerational
 effects on longevity and lifetime reproductive success, manifested both in
 the form of maternal and paternal effects. In addition, the
 transgenerational effects via mothers detected in this study are
 consistent with a new concept: terminal investment transgenerational
 effects. Such effects could underlie cross-generational responses to
 environmental perturbation. Our results indicate that pesticide exposure
 leads to unanticipated effects on population dynamics and have
 far-reaching ecological and evolutionary implications.
description: <strong>Experimental
 setup</strong> We individually exposed male and female beetles
 from the stock to either water (controls) or sub-lethal concentrations of
 pesticide. We applied the experimental treatments only to the parental
 generation, and recorded longevity, fecundity, lifetime reproductive
 success and body size (assessed as dry body weight; see below) of
 individuals up to the second generation (F2), after mating the focal
 parent to standardized mates (see below). Sample size doubled with each
 subsequent generation as we randomly selected one son and one daughter
 from each pair of parents to start each subsequent generation to test for
 sex-related differences in transgenerational effects (Fig. 1). The total
 number of individuals scored was expected to be 1050 (75 F0 mothers, 75 F0
 fathers, 150 F1 daughters, 150 F1 sons, 300 F2 granddaughters, 300 F2
 grandsons), but due to some individuals escaping and accidental mishaps,
 the final sample sizes were slightly lower and varied for the different
 traits (sample size for each analysis is indicated in the tables in the
 Results section). We placed inoculated beans individually in
 Eppendorf tubes to ensure virginity of the emerging adult beetles and to
 keep track of individual age. Bean isolation was done 11 days after female
 oviposition, to minimize potential effects of mechanical manipulation on
 freshly laid eggs or early instar larvae inside the beans. The age of
 individuals at the time of exposure to the experimental treatments
 (toxicant/control) ranged between 1 and 4 days. We exposed each individual
 beetle to either one of two non-lethal concentrations of the pesticide (1
 g/L and 2 g/L COMBO Deltamethrin, 2.5% w/v, Sarabia) or to carbon-filtered
 dechlorinated tap water (control group) inside a flow cabinet at room
 temperature for 24 h. We previously conducted pilot tests to identify
 non-lethal concentrations of the pesticide for this species (see Figure
 S1). We aimed to expose parental beetles to sub-lethal concentrations so
 as not to confound potential transgenerational effects (influences on
 offspring's phenotype via non-genetic inheritance) with genetic
 changes due to differential survival, i.e. selection. Each beetle was
 randomly allocated to a single treatment (control, low pesticide, high
 pesticide). We exposed 25 F0 individuals from each sex to each treatment,
 for a total of 150 initial individuals (25 individuals x 2 sexes x 3
 treatments; Fig. 1). To expose each parental beetle to its
 corresponding treatment, we impregnated the ends of cotton swabs with 30
 µL of either pesticide or water and placed these in 2 mL Eppendorf tubes
 that we kept open. We then introduced the target beetle in another tube
 with the bottom cut out and fit this tube into the one containing the
 impregnated swab, placing a mesh in between both tubes. This setup allowed
 exposure of beetles to airborne pesticide but prevented direct contact
 with it. After the exposure phase, focal beetles were individually placed
 into 26 mL plastic vials with pinholes in the cap to allow airflow, and ad
 libitum beans to be used as oviposition substrate. Each individual shared
 the vial with a tester non-exposed mate (male or female). These tester
 individuals were sourced from a standardized heterozygote tester line that
 was generated by crossing two near-isogenic lines generated after 17
 generations following a brother-sister mating protocol. The use of these
 genetically homogeneous tester individuals minimizes sampling variance
 arising from random sampling of mates (see for rationale and application
 Garcia-Gonzalez and Evans
 2011; Garcia-Gonzalez and Dowling 2015; Travers et al.
 2015), and also ensures
 that transgenerational effects would be only minimally obscured by genetic
 or non-genetic variation introduced by individuals used as mates
 (Garcia-Gonzalez and Dowling 2015). We allowed beetles to mate and lay
 eggs in the vial for 48 h. Afterwards, we extracted males from the vials
 and individually kept them in Eppendorf tubes, to track their longevity.
 We then transferred mated females (focal females mated to tester males, or
 tester females mated to focal males) to a second 26 mL container with ad
 libitum beans where they laid eggs for the remainder of their lifespan. We
 counted the lifetime number of eggs (fecundity) and number of adult
 offspring (Lifetime Reproductive Success-LRS) produced by each female. LRS
 is a good estimate of fitness, as it measures the lifetime production of
 sexually mature progeny. We did not expose the two subsequent generations
 (F1 and F2) to the pesticide, but kept housing and mating conditions
 identical to those of the parental generation. To obtain virgin F1
 individuals we waited until day 11 after oviposition by parental females
 (see above) and individually isolated beans from the mating vials in
 Eppendorf tubes, as described above. We followed the same procedure in the
 F2 generation. We tracked longevity by checking the survival of
 isolated individuals daily. We determined fecundity by carefully
 inspecting all beans and counting the total number of eggs laid by each
 female, both in the mating vial and the subsequent oviposition vial (only
 for F0 and F1 generations). We measured LRS as number of adults produced by each female
 during her lifetime. To obtain these data, we froze vials on day 28 since
 the last possible day of oviposition (in the second oviposition vial, the
 day the female was found dead), and later counted the number of adult
 individuals present in the vial. This procedure ensures that our LRS
 measurement excludes individuals from a subsequent generation (i.e.,
 produced by crossings between siblings), because we take into account
 female egg-laying span and the timing of egg-to-adult transition.
 Reproducing females only live a few days (15 days maximum; mean longevity
 ± SE = 8.38 ± 0.069; 99% of females lived less than 13 days) and their
 fecundity is maximal the first few days after mating (Zajitschek et al. 2018), hardly laying any eggs after the first week
 post-mating (unless they are housed with males and remate during this
 period). Moreover, new adults take ca. 23 days to emerge from newly laid
 eggs under our experimental conditions and virtually all adults emerge
 from the beans within 28 days (Rodriguez-Exposito 2018; Rodriguez-Exposito and
 Garcia-Gonzalez, unpublished). We therefore preserved the vials after all
 adults have emerged, but before any of their subsequent offspring could
 have emerged. Lifetime reproductive success has two components. First, an
 intragenerational component, because a female’s total number of adult
 offspring produced over its lifespan is largely determined by fecundity
 and effects of mothers on egg-to-adult viability (including maternal
 effects such as egg provisioning). Second, an intergenerational component,
 because egg-to-adult viability is expected to be largely dependent on
 properties of the individual offspring. This consideration also affects
 the interpretation of changes in LRS in the F1 and F2 generations
 discussed below, and generally, it implies that our conclusions on the
 extent of cross-generational influences of pesticide exposure are
 conservative. We measured the dry weight of focal beetles with
 a Sartorius Cubis MSA6.6S microbalance (readability 0.001 mg, Sartorius,
 Goettingen, Germany). Beetles were previously frozen at -20 ºC (after
 death, in order to be able to track longevity), and afterwards thawed and
 dried to constant weight on an oven at 40 ºC for ~1 week, hence removing
 variation in body weight due to variation in time elapsed between death
 and freezing. <strong>Statistical
 analyses</strong> We used linear models (LMs; F0 and F1
 generations) and general linear mixed models (GLMMs; F2 generation) to
 test whether experimental treatments applied to parental individuals
 affected not only their phenotype and life-history traits, but also those
 of subsequent generations. Our response variables were longevity,
 fecundity and LRS, all of which were normally or approximately normally
 distributed. Models included the experimental treatment as a fixed factor.
 Longevity was included as covariate in models testing effects on fecundity
 and LRS. Body size of the focal individual was included as covariate for
 longevity of those focal individuals, whereas body size of the female
 (focal or tester) was included as covariate for fecundity and LRS.
 Individuals' age at mating (1-4 days old) was also entered as a
 covariate. Longevity was also analysed by means of survival analysis using
 Cox models, and Cox mixed models for the F2 generation. Results from these
 proportional hazards models are consistent with those from the LMs and the
 GLMMs (Table S4). To ease the interpretation of results and also
 because in this species males and females have distinct life-histories
 (Hallsson and Björklund
 2012), we conducted the
 analyses separately according to sex of the focal individuals and by the
 sex of the parent/grandparent (for F1 and F2, respectively) initially
 exposed to treatment. We fitted LMs to the data from the F0 and F1
 generations using the function “lm” in R (R Core Team, 2016). Since we only took one male and one female per
 cross in each generation, and because we conducted the analyses separately
 by sex, F1 data analyses did not require inclusion of a random effect to
 correct for parental ID. For the F2 generation, we fitted GLMMs using the
 “lmer” function in the “lme4” package (Bates et al. 2014) including grandparent ID as a random factor.
 P-values were calculated on maximum likelihood models, while REML models
 were run to obtain parameter estimates. The package pbkrtest
 (Halekoh and Højsgaard
 2014) was used to
 calculate the degrees of freedom for the estimates in the case of GLMMs. A
 few instances of F0 LRS data &lt;10 were excluded from the analyses a
 priori because such low fertility data are likely outliers due to
 intrinsic individual health problems or to infertility problems
 (Rodriguez-Exposito
 2018). The few cases of
 LRS &lt; 10 were distributed across groups, including the controls,
 which supports the notion that these cases are unrelated to the treatment
 (number of cases in the female-treated dataset: 2 in the control group, 1
 in the low group, 1 in the high group; number of cases in the male-treated
 dataset: 1 in the control group, 2 in the low group). Due to the large
 number of P-values estimated throughout our study, we controlled the false
 discovery rate using the p.adjust function in R applying the
 Benjamini-Hochberg method (Benjamini and Hochberg
 1995). We corrected P
 values within each generation and show adjusted P values in the
 Results' section and the tables.
 We also calculated
 cross-generational multiplicative fitness for females and males exposed to
 treatment and we did so both via daughters and via sons (Fig. S2). In
 these calculations, a 1:1 sex ratio was assumed. Multiplicative fitness
 via daughters for each F0 individual was calculated by multiplying its LRS
 (halved, as half of the number of adults produced would be daughters,
 assuming equal sex ratio) by the LRS of his/her daughters (F1), and by the
 LRS of his/her grandoffspring (F2) produced via daughters. We followed a
 similar procedure to calculate multiplicative fitness via sons. Due to the
 multiplicative nature of these calculations, sample sizes in these
 analyses are reduced compared to the analyses above because missing values
 for any family in any given generation implies a missing value for the net
 fitness of a particular lineage across the three generations (see final
 sample sizes for the lineages in the Results section). As before, F0 LRS
 data &lt; 10 were excluded a priori from the analyses. Effect sizes
 (Cohen's d, that is, the mean difference divided by the pooled
 standard deviation) and their associated 95% CIs for the difference in
 multiplicative fitness between groups were calculated using the package
 compute.es (Re
 2013). Cohen's d for
 intragenerational effects of the pesticide on female fitness (see below)
 was calculated from raw data using compute.es, but also using marginal
 means from the model, with the package emmeans (Lenth et al. 2018). For simplicity, we do not state or discuss
 specific influences of covariables on the response variables. Their
 effects are nonetheless reflected on the tables. Notably,
 transgenerational effects were detected even after controlling for these
 influences. Graphical representation of data for response variables that
 were not affected by treatment can be found in Figures S3-S7 in the
 Supplementary Information (SI). Tukey post-hoc tests for all models can be
 found in Table S1 in the SI.
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