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. 2023 Nov 13;132(7):1259–1270. doi: 10.1093/aob/mcad171

Non-stressful temperature changes affect transgenerational phenotypic plasticity across the life cycle of Arabidopsis thaliana plants

Ailén Authier 1,2,a, Pablo Cerdán 3,4, Gabriela Auge 5,6,a,✉
PMCID: PMC10902895  PMID: 37956109

Abstract

Background and Aims

Plants respond in a plastic manner to seasonal changes, often resulting in adaptation to environmental variation. Although much is known about how seasonality regulates developmental transitions within generations, transgenerational effects of non-stressful environmental changes are only beginning to be unveiled. This study aimed to evaluate the effects of ambient temperature changes on the expression of transgenerational plasticity in key developmental traits of Arabidopsis thaliana plants.

Methods

We grew Columbia-0 plants in two contrasting temperature environments (18 and 24 °C) during their whole life cycles, or the combination of those temperatures before and after bolting (18–24 and 24–18 °C) across two generations. We recorded seed germination, flowering time and reproductive biomass production for the second generation, and seed size of the third generation.

Key Results

The environment during the whole life cycle of the first generation of plants, even that experienced before flowering, influenced the germination response and flowering time of the second generation. These effects showed opposing directions in a pattern dependent on the life stage experiencing the cue in the first generation. In contrast, the production of reproductive biomass depended on the immediate environment of the progeny generation. Finally, the seed area of the third generation was influenced positively by correlated environments across generations.

Conclusions

Our results suggest that non-stressful environmental changes affect the expression of key developmental traits across generations, although those changes can have contrasting effects depending on the parental and grandparental life stage that perceives the cue. Thus, transgenerational effects in response to non-stressful cues might influence the expression of life-history traits and potential adaptation of future generations.

Keywords: Plasticity, germination, flowering, Arabidopsis thaliana, reproductive biomass, seeds

INTRODUCTION

Plants have evolved in seasonal environments, adjusting their phenology to optimal environmental conditions throughout the year. Plants achieve this by integrating environmental information through the perception of cue changes, initiating a signalling cascade and adjusting developmental programmes, altogether resulting in a concerted response to the environment. This response is maintained until conditions are changed, when this cycle starts again (Anderson et al., 2011). Phenotypic plasticity, in which a certain genotype displays a range of phenotypic responses to face daily and seasonal changes, is essential for the survival, growth and reproduction of individuals (Liancourt et al., 2013). The informational value of environmental changes that can induce phenotypic plasticity depends on the selective pressure exerted by that environmental cue (Karban et al., 1999). If the phenotypic plasticity displayed by plants is consistent with the environment and not detrimental to fitness, then it acquires adaptive value (Dudley and Schmitt, 1996).

Plants can respond to changes in the environment that occurred during their life cycle and those of previous generations (Gutterman, 1982; Sultan, 1996, 2000; Donohue and Schmitt, 1998; Donohue, 2009; Willis et al., 2014). Much of the work done on effects across generations has been focused on the study of establishment or maintenance of responses to stressful conditions, such as presence of pathogens, extreme temperatures (high or low) or drought (reviewed by Bonduriansky, 2021; Auge et al., 2023). However, the effects of environmental factors associated with non-stressful seasonal changes and their correspondence to plant responses across generations remain to be revealed.

Adequate developmental transition control requires the perception of seasonal cues in order for them to be coordinated properly throughout the life cycle (Auge et al., 2017b). For annual plants (which germinate, flower and reproduce over the course of a year), there are two key developmental transitions: the transition from vegetative to reproductive stages (flowering) and the seed to seedling stages (germination) (Donohue et al., 2010; Ehrlén, 2015; Auge et al., 2017b). The timing of these transitions is under strong natural selection and is finely regulated by environmental conditions, with both responding to temperature, light quality and photoperiod, among other cues (Simpson and Dean, 2002; Amasino, 2004; Michaels et al., 2005; Holdsworth et al., 2008; Donohue et al., 2010; Munguía-Rosas et al., 2011; Ehrlén, 2015). Plants integrate this information in such a way that the environmental conditions experienced by mother plants influence the behaviour of the progeny (Marshall and Uller, 2007; English et al., 2015). The correct integration of environmental information within and across generations would allow future generations to respond adaptively to their own environments. Arabidopsis thaliana plants show transgenerational plasticity in multiple traits in response to changes of the parental environment (Groot et al., 2017; Lampei, 2019; Alvarez et al., 2020). Arabidopsis thaliana mostly displays an annual winter life history in its native range, experiencing fluctuating temperatures during its life cycle: seeds germinate in autumn when temperature drops and humidity increases, and plants overwinter as a rosette. The spring, with longer days and warmer temperatures, induces flowering, and the seeds are produced and dispersed at the end of this season, finishing the cycle. The hot and dry summer induces seed dormancy, but the arrival of the autumn with cooler and more humid days breaks this dormancy and induces germination, starting the cycle again (Rubio de Casas et al., 2012). A disturbance in the environment in any of the seasons could induce a change in the adjustment of the life cycle. For example, if the autumn is too dry, seeds might not germinate until the arrival of spring, thus shifting the entire life cycle into a completely different season, with part of it likely to happen during the summer, which can markedly reduce survival (Zacchello et al., 2020; Postma and Ågren, 2022). However, some A. thaliana populations have also evolved a spring/summer annual phenology, which allows them to complete a whole life cycle after dispersion of seeds in the spring when environmental conditions are met (a compromise between environments before and after seed dispersal) (Penfield and Springthorpe, 2012; Huang et al., 2014). Nonetheless, given that different life stages have different tolerances to environmental conditions, plants must adjust their developmental transitions such that each stage matches the optimal environment that allows for their development and survival. Even mild changes can affect the timing of those transitions, shifting development to suboptimal growing conditions (Gray and Brady, 2016).

Changing temperatures, in particular when experienced by the A. thaliana parental generation, result in phenotypic plasticity in the progeny (Whittle et al., 2009; Suter and Widmer, 2013a, b; He et al., 2014; Burghardt et al., 2016; Groot et al., 2017; Auge et al., 2017a; Alvarez et al., 2020). In addition, hot temperatures have negative effects in all stages of the life cycle of this species (Zinn et al., 2010; Groot et al., 2017), creating a potential selective agent in their natural habitat (Wolfe and Tonsor, 2014). The parental environment also influences the quantity, viability and vigour of progeny seeds (Valencia-Díaz and Montaña, 2005; Wang et al., 2015; Li et al., 2017; Awan et al., 2018; Huang et al., 2018). Altogether, these traits, which are under selection, could affect fitness of the next generation (Larios et al., 2014; Lu et al., 2016).

The objective of this study was to investigate whether non-stressful changes in ambient temperature would influence plasticity across generations in A. thaliana plant traits (germination, flowering time, reproductive biomass production and seed size) and to evaluate the impact of timing of those environmental effects and their persistence in the life cycle. Given that environmental changes do not necessarily have to be stressful in nature to promote plasticity, we hypothesize that transgenerational plasticity can also occur in response to non-stressful changes, leading to adaptive transgenerational effects throughout the life cycle of plants. The environmental conditions experienced during the entire life cycle of the parental generation, even before flowering, will influence the germination response, flowering time, seed yield and size of subsequent generations. These findings would imply that non-stressful stimuli might influence the expression of life traits and, potentially, contribute to the adaptive ability of future plant generations.

MATERIALS AND METHODS

Plant material and temperature treatments

In this study, we used the A. thaliana Columbia-0 (Col-0) ecotype. This accession is a highly inbred line typically used in plant biology laboratories and displays early flowering and intermediate dormancy, which allow us properly to assess the phenotypes of interest of this study (Somssich, 2019).

A first generation of plants (G0) were initially grown to homogenize the environment in which seeds of the first generation (G1) were produced, with the goal of removing any undesired transgenerational effects. The G0 seeds were imbibed in a plate with agar-agar 0.6% w/v (Plant Agar; Duchefa Biochemie) for 4 days at 4 °C in darkness. Seeds were then transferred using a micropipette to soaked 180 mL pots with a mix of 2:1 soil:perlite (Grow Mix Multipro; Agroquímica Larrocca SRL). Pots were immediately placed in a growth chamber (white light sources were Neutral LED tubes 4100K, PAR ~130 μmol m−2 s−1), where seeds were allowed to germinate at 24 °C in a long-day photoperiod (LD; 16 h light–8 h darkness). One week after germination, excess seedlings were thinned, leaving one focal plant per pot. Plants were grown at 24 °C and LD until harvest. Plants were watered regularly (two or three times a week) and fertilized once with Hakaphos 0.1 % w/v (Compo Agricultura) immediately after bolting. Seeds were harvested when two-thirds of the fruits were dry and placed in a hermetic container with silica gel for 3 days. Seeds from three different individual plants were pooled and stored in 1.5 mL tubes to generate the G1 seed stock, then kept in a fridge until being used for experiments.

To explore the effects of temperature on the expression of plasticity across generations, we designed a multigenerational experiment, in which we grew plants at two temperatures that are known to have contrasting effects on A. thaliana growth: 18 and 24 °C (Sánchez-Lamas et al., 2016). We either grew the plants during their whole life cycles at those temperatures (18–18 and 24–24), or they were moved to the contrasting temperature after bolting (18–24 and 24–18), obtaining a combination of four possible thermal environments (Table 1).

Table 1.

Experimental design of the multigenerational experiment

Treatment Temperature before flowering (BF) Temperature after flowering (AF)
1 18 18
2 24 18
3 18 24
4 24 24
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Treatment 3 would emulate what Col-0 plants (a spring/summer annual ecotype) encounters in natural conditions: progression of cooler to warmer temperatures during the life cycle would indicate the passage through spring into the summer. Comparing responses between treatments 1 vs. 3 and 2 vs. 4 would provide information about the effect of the environment after flowering (reproductive growth) on the development of the next generation, and comparing responses between treatments 1 vs. 2 and 3 vs. 4 would inform us on the effects of the environment during early development of the previous generation (vegetative growth, before flowering).

Growth of G1 plants

The G1 seeds were incubated in the conditions described above, then transferred to pots with a mix of soil and perlite (2:1) and randomly placed in LD at 24 °C for pots of treatments 1 and 3, or at 18 °C for pots of treatments 2 and 4 (for growth condition specifications, see Table 1 and previous section). Seeds were allowed to germinate, and after 1 week the excess seedlings were thinned to leave a focal plant per pot, with a total of 12 pots (plants) per treatment. Plants growing at both temperatures were watered regularly (three times a week for the ones growing at 24 °C, and one or two times a week for those growing at 18 °C) and fertilized once with Hakaphos 0.1% w/v (Compo Agricultura, Argentina) after bolting. Plants of treatments 1 and 4 were kept in the same conditions during their whole life cycle; those of treatments 2 and 3 were moved to the contrasting temperature (moved between chambers) after bolting was observed. All plants were randomized weekly within the chambers and containing trays to avoid positional effects. For this, plants were checked every other day for floral bud emergence. Given that growth at both temperatures might result in differences in flowering time and plant development, planting was staggered to synchronize seed harvest across all treatments. Seeds from 12 individual plants per treatment (independent biological replicates) were harvested on the same date and kept in separate tubes in dry storage until used for germination testing.

Germination assay for G2 seeds

To evaluate the maternal effects on germination and their interaction with the environment of the seeds, freshly harvested seeds (3 days after harvest) were imbibed in agar-agar plates (0.6% w/v, Plant Agar; Duchefa Biochemie) and immediately incubated in LD at 18 or 24 °C. Twenty seeds were sown per plate, one plate per replicate (12 maternal plants), G1 treatment (four treatments) and seed incubation condition (two temperatures), giving a total of 96 plates. Plates were considered as our unit of analysis. Germination was counted daily during the first week of incubation, then every other day until seeds reached a germination plateau (no new germinants on two consecutive counting days). A seed was considered germinated when radicle protrusion was observed. The final germination proportion was calculated as the number of germinated seeds divided by the total number of viable seeds per plate. A seed was considered viable if it kept firmness to touch at the end of the assay.

Flowering time, reproductive biomass production and seed area of G2 plants

To explore the effects of the first-generation environments on the flowering time and reproductive biomass production of the second generation, in addition to the interaction between environments of both generations, G2 plants were grown in the same treatments as G1 plants using a fully factorial experimental design (Fig. 1). For this, we used a single seed descent procedure: G2 seeds descendant from each G1 biological replicate plants (n = 12) grown in different conditions were sown in individual agar-agar plates, stratified at 4 °C in darkness for 4 days, transferred to pots and grown in the temperature treatment combinations as described above (treatments 1–4; Table 1). Plants were moved randomly within the chambers and containing trays on a weekly basis to avoid positional effects. In this way, we grew plants in one of each 16 possible combinations of first- and second-generation environments (192 plants total; Fig. 1).

Fig. 1.

Fig. 1.

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Experimental design of the multigenerational experiment to test for effects of ambient temperature on the expression of transgenerational plasticity. A single seed descent method (represented as black lines) was used to run a fully factorial experiment, in which we evaluated the interaction between parental and progeny environments on developmental traits of the progeny (germination, flowering time, reproductive biomass production and seed area, indicated to the right). Grey-outlined boxes represent generations of plants (G0–G3). Black circles represent life cycle endpoints of plants grown in standard conditions (G0). Coloured circles represent life-cycle endpoints of plants (G2 and G3) grown in the different treatments: treatment 1, 18–18 (dark blue); treatment 2, 24–18 (light blue); treatment 3, 18–24 (light orange); and treatment 4, 24–24 (dark orange). The full combination of treatments after growing two generations is indicated in the boxes at the bottom of the figure (treatment of first generation–treatment of second generation; coloured boxes follow the treatment of the first generation).

Flowering time

Flowering time was recorded as the number of rosette leaves developed from germination to bolting (floral bud emergence).

Reproductive biomass production

The G2 plants were kept until they reproduced. The G3 seeds were harvested after plants senesced and stored in separate 1.5 mL tubes by individual (12 biological replicates per treatment). Reproductive biomass production was recorded by weighting total seed yield per tube using a precision scale.

Seed size

The seed size measurement was carried out by taking pictures with a NIKON D3300 camera (ISO 1600, 1/160 s, f/8, 55 mm) of 20–40 seeds from each biological replicate with a millimetre ruler as a reference to the scale (and an identifier). Photographs were processed with the software ImageJ (Schneider et al., 2012). Initially, the image scale was established (in millimetres). Then, the seeds in the picture were selected and transformed to a binary image, selecting those objects inside the HSB coloration space with brightness between 0 and 203, saturation between 159 and 255 and hue between 0 and 57. The selected values that did not correspond to seeds were eliminated manually, and a pixel line was added between overlapped seeds to consider unique values and reduce overestimation of area values. Final seed area measurements and the total number of seeds were obtained using the tool ‘Analyze Particles’.

Statistical analysis

All statistical analyses were conducted using R v.4.2.2 (R Core Team, 2022). To test for effects of the different temperature environments on G2 seed germination with plates as the unit of analysis (independent biological replicates), we fitted generalized linear models using ‘glm’, then performed type III likelihood ratio tests (χ2 test for goodness of fit) using the ‘Anova’ function in the ‘car’ package (Fox and Weisberg, 2019). Given that germination is a binomial trait expressed in the form of proportions, we used a logit link function to run the tests. Initially, we analysed the effects of the whole life-cycle environment of the G1 plants (‘G1 Env’ with four levels: treatments 1–4 and 18–18 as reference), the seed environment (‘Incubation’ with two levels: 18 and 24 °C), and their interaction (‘G1 Env’ × ‘Incubation’). Then, we analysed the environmental effects before (BF) and after flowering (AF), and their interaction (BF × AF) (two levels, 18 and 24 °C), to evaluate whether the timing of those changes had an influence on the germination response. All the independent variables were considered as fixed.

To test for effects of G1 and G2 environments (independent variables ‘G1 Env’ and ‘G2 Env’, with four levels each: treatments 1–4) and their interactions on the response variables flowering time, reproductive biomass production and seed size, which are normally distributed, we used the ‘aov’ function in the ‘stats’ package (R Core Team, 2022) to perform a factorial ANOVA. To interpret the interactions, we next analysed the effect of the environment of each generation on the response variables. We tested the effects of the G2 environment for the group of descendants within each G1 treatment, and the effects of the G1 environment within each G2 treatment.

To estimate the magnitude and direction of the transgenerational effects on the response variables germination and flowering time, we fitted generalized linear models with the ‘brglm’ (biased reduced generalized linear models; Kosmidis and Firth, 2021) and ‘glm’ packages (Fox and Weisberg, 2019) to obtain the ‘Estimate’ representing the change in log odds with associated 95% confidence intervals. Positive values indicate that 24 °C induced germination (increased germination proportion) or delayed flowering (higher number of leaves) when compared with 18 °C; and confidence intervals not overlapping zero indicate that the effects are significant.

For all instances, when testing for multiple comparisons, a correction was conducted using the Holm method of ‘p.adjust’ in the ‘stats’ package (R Core Team, 2022).

RESULTS

Germination responses of a second generation are influenced by the environment of the first generation before and after flowering

To explore the effects of temperature throughout the whole life cycle on early life responses of the next generation, we analysed the germination response of the G2 seeds from G1 plants grown in different thermal environmental combinations (Table 1; Fig. 1). The first generation and seed incubation environments had a significant effect on germination proportion separately (G1 Env χ2 = 422.7, d.f. = 3, P < 2.2 × 10−16; Incubation χ2 = 54.5, d.f. = 1, P = 1.6 × 10−13; Fig. 2A), which follows previous reports on progeny germination and confirms that our treatments are properly establishing maternal temperature effects. However, the incubation temperature did not modify the expression of responses to the environment of the first generation (non-significant G1 Env × Incubation interaction, χ2 = 5.6, d.f. = 3, P = 0.13).

Fig. 2.

Fig. 2.

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Effect of the environment of the first generation on germination proportion of Arabidopsis thaliana Columbia-0 seeds. Graphs show final germination proportion (A) or germination speed (B) of seeds from mother plants grown in a combination of non-stressful ambient temperature environments (18 and 24 °C) before and after flowering (BF-AF, x-axis): treatment 1, 18–18 (dark blue); treatment 2, 24–18 (light blue); treatment 3, 18–24 (light orange); and treatment 4, 24–24 (dark orange). Responses of seeds incubated at 18 °C (left panel) and 24 °C (right panel) are shown as boxplots.

To explore the influence of timing of those environmental changes, we analysed the effect of temperatures before (BF) and after flowering (AF) separately on the final germination proportion (for this analysis, the non-significant three-way interaction, AF × BF × Incubation, was dropped because it did not improve the model). Temperature before and after flowering interacted significantly to regulate seed germination proportion (significant BF × AF; Table 2). As expected, temperature after flowering affected germination strongly: for both incubation conditions, seeds developed and matured at warmer temperatures germinated more than those seeds produced at cooler temperatures (comparisons 18–18 vs. 18–24, and 24–18 vs. 24–24; Table 2; Fig. 2A; Supplementary Data Fig. S1). In addition, the environment experienced by the G1 plants before flowering significantly affected seed germination at both incubation temperatures: at equal environments after flowering, warmer temperatures before flowering reduced progeny germination (comparisons 18–18 vs. 24–18, and 18–24 vs. 24–24; Table 2; Fig. 2A; Supplementary Data Fig. S1).

Table 2.

Effects of temperature before flowering (BF) and after flowering (AF) and during seed incubation (IT) on progeny germination proportion. The table shows effects of temperature BF, AF and IT and their two-way interactions (full model); and of temperature BF and AF and their two-way interaction by incubation temperature (IT = 18 °C and IT = 24 °C). Tests were based on type III analyses of likelihood ratios from a generalized linear model with a logit link function (for the full model, the three-way interaction was dropped because preliminary analyses showed that it did not improve the model). The χ2 values, degrees of freedom (d.f.) and P-values are shown in the table

Variable Full model IT = 18 °C IT = 24 °C
χ2 d.f. P-value χ2 d.f. P-value χ2 d.f. P-value
BF 24.6 1 1.69 × 10−6 22.9 1 1.69 × 10−6 33.5 1 6.98 × 10−9
AF 163.8 1 <2.2 × 10−16 139.2 1 <2.2 × 10−16 227.1 1 <2.2 × 10−16
IT 58.1 1 2.54 × 10−14 – –
BF × AF 20.5 1 6.07 × 10−6 3.6 1 0.057 16.9 1 0.057
BF × IT 4.9 1 0.027 – –
AF × IT 0.3 1 0.551 – –
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In addition, germination proportion was highly correlated with germination speed (number of seeds germinated per day), i.e. the environments across generations that promoted germination also induced faster germination and vice versa (Pearson’s correlation = 0.967, P < 0.001; Fig. 2B).

Persistence of transgenerational effects in flowering time is dependent on the environment of the progeny

When evaluating the persistence of the G1 environment effects further down in the life cycle of the progeny, our results showed a significant interaction between the environments of both generations on flowering time (significant G1 Env × G2 Env interaction; Table 3; Supplementary Data Figs S2 and S3).

Table 3.

Effects of maternal environment on rosette leaf number of progeny plants. The table shows the results of an ANOVA, indicating F-values, degrees of freedom (d.f.) and P-values for the effects of the first- (G1 Env) and second-generation environments (G2 Env) and their interactions (full model), or the effects of the first-generation environment on plants grown at 18 or 24 °C

Variable Full model G2 = 18 °C G2 = 24 °C
F d.f. P-value F d.f. P-value F d.f. P-value
G1 Env 14.23 2 2.55 × 10-6 19.27 2 2.56 × 10−7 0.87 2 0.417
G2 Env 87.66 1 2.9 × 10−16 -- --
G1 Env × G2 Env 18.63 2 7.57 × 10−8 -- --
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When G2 plants were grown at 18 °C, we observed a significant effect of the environment of G1 plants before and after flowering (Fig. 3). We observed contrasting effects on flowering time of G2 plants that were dependent on the life stage experiencing the environmental cue in the previous generation. Warm temperatures before flowering accelerated bolting, whereas when experienced after flowering, flowering was delayed (Supplementary Data Fig. S3), strikingly similar to what was observed for the germination response (Supplementary Data Fig. S1).

Fig. 3.

Fig. 3.

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Effects of environment changes experienced by the first generation on flowering time of Arabidopsis thaliana Columbia-0 progeny plants. The graph shows the number of leaves at bolting (y-axis) for each progeny treatment, 18 °C (left) and 24 °C (right; x-axis). Colours indicate the environment of G1 plants: treatment 1, 18–18 (dark blue); treatment 2, 24–18 (light blue); treatment 3, 18–24 (light orange); and treatment 4, 24–24 (dark orange).

Warmer temperatures experienced by the second generation accelerated flowering time, regardless of the environment of G1 plants (Table 3; Fig. 3; Supplementary Data Fig. S2). However, this effect was larger when G1 plants were grown in the combination 18–24 °C (Supplementary Data Fig. S2). This might be because the warmer temperature provided a strongly inductive flowering environment, which, combined with a long-day photoperiod, masked the expression of the transgenerational effects.

Effects of environments of consecutive generations on reproductive biomass production

To analyse whether the transgenerational effects on traits related to fitness further down in the second-generation life cycle are persistent, we quantified the environmental effects of both generations on production of reproductive biomass by G2 plants. We observed that in our experimental conditions, the environment of the first generation did not affect seed production of G2 plants (Fig. 4). Production of reproductive biomass depended strongly on the immediate environment: G2 plants grown at 18–18 (dark blue) and 24–18 (light blue) produced the maximum and minimum total seed weight, respectively, regardless of the treatment of the first generation (Fig. 4). These results are reflected in the non-significant interaction of the statistical analysis (non-significant G1 Env × G2 Env).

Fig. 4.

Fig. 4.

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Effects of environments across generations on reproductive biomass production of Arabidopsis thaliana Columbia-0 G2 plants. The graph shows total seed weight (in milligrams) from G2 plants (colours) grown in a combination of G1 environments before and after flowering (BF-AF, x-axis): treatment 1, 18–18 (dark blue); treatment 2, 24–18 (light blue); treatment 3, (18–24 (light orange); and treatment 4, 24–24 (dark orange). Top right: results of the ANOVA testing for environmental effects and their interactions (G1 Env and G2 Env).

Seed size is influenced by the interaction of environments across generations

To analyse the persistence of transgenerational effects further, we measured the area of G2 and G3 seeds, a trait strongly related to fitness. The G2 seed size was not affected by the environment of the previous generation (Supplementary Data Fig. S4). However, the results showed that, in our experimental conditions, the environments of both generations interacted to influence G3 seed size (Fig. 5). In addition, the most favourable environment of G2 plants (the one that produced seeds with larger size) was 18–18 (dark blue) for all G1 treatments, indicating that the most immediate generation is still a large determinant of fitness, as observed for seed weight. Interestingly, we observed that there was an effect on seed size when environments were matched across generations. The seeds from G2 plants that grew in the same environmental conditions as those of the previous generation were larger compared with those where there was no correlation of environments.

Fig. 5.

Fig. 5.

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Environmental effects of progeny and maternal environments on the area of Arabidopsis thaliana Columbia-0 G3 seeds. The graph shows seed area (in millimetres squared) for seeds from G2 plants (colours) descending from G1 plants grown in a combination of environments before and after flowering (BF-AF, x-axis): treatment 1, 18–18 (dark blue); treatment 2, 24–18 (light blue); treatment 3, 18–24 (light orange); and treatment 4, 24–24 (dark orange). Bottom right: results of the ANOVA testing for environmental effects and their interactions.

DISCUSSION

The environment that the first generation of plants encountered throughout their entire life cycle had a strong influence on the expression of many developmental traits in the subsequent generation. We found that the environment of the first generation exerts short-term effects on the germination response of the next generation and long-term effects on plant phenotypes during another critical developmental transition, flowering. These effects of temperature can be contrasting (change direction) and are dependent on the life stage of the previous generation that experienced those changing temperatures. However, these effects are weakened and disappear later in the life cycle, because we did not find a significant contribution on seed production across generations, implying that within-generation effects are favoured. But in the third generation, we observed that seed size, a proxy for propagule investment, was positively influenced when environments across generations matched.

We found that seeds developed and matured at warmer temperatures germinated more than those of mother plants experiencing cooler temperatures. This behaviour was expected and consistent with multiple reports showing that increasing temperatures after flowering reduce dormancy levels (Penfield and Springthorpe, 2012; Footitt et al., 2013; Burghardt et al., 2016). Maternal effects can contribute to a bet-hedging strategy to spread germination across the year and help seeds face unpredictable environmental conditions. Warming temperatures during seed maturation might accelerate germination to fit a whole new generation before summer strikes (Burghardt et al., 2016) or it might reduce the ability of seeds to cycle back into a deep secondary dormant state (Auge et al., 2015). In a natural environment, dispersal closer to summer would indicate that the dormant period should be shorter for seeds to ensure germination in the autumn. In turn, the environment experienced by the mother plant before flowering significantly affected progeny germination, but in an opposite manner to the effect of the same environment experienced after flowering: for equal environments after flowering, warmer temperatures experienced early in the life cycle influenced the behaviour of the next generation of seeds, even before the plants committed the developmental programme from vegetative to reproductive growth. This could have the same effect as cooler temperatures during seed maturation on the response of progeny germination, allowing seeds to explore a wider range of environments to ensure that germination occurs in optimal conditions. Early life temperature changes have been shown to have a strong effect on progeny germination (Chen et al., 2014; Auge et al., 2017a; Penfield and MacGregor, 2017). Progeny seeds of the Landsberg erecta ecotype had a high level of primary dormancy when mother plants were grown at 16 °C before flowering, showing a similar effect of that environment when experienced after flowering (Chen et al., 2014). Our results showed the opposite trend (cooler temperatures before flowering promoted germination), and this might be attributable to different environmental sensitivities across populations of the same species and local adaptation (Burghardt et al., 2016; Colicchio, 2017. However, it strongly reinforces the fact that the environment during the whole life cycle of the mother plant influences early trait responses in the progeny generation.

The response to environments that have been experienced by previous generations could restrict the expression of adaptive phenotypes and affect fitness. Nevertheless, this response could also add information that helps to synchronize life cycles in correlated environments among generations (Auge et al., 2017b). We observed that the environment of the first generation affected the flowering time of the second generation, i.e. the flowering time of the progeny was influenced by the maternal environment. We also observed that the flowering response to the environment of the previous generation depended on the environment of the present generation. In this case, warmer temperatures (24 °C) masked the expression of the maternal effects on flowering time. Plants would be expected to favour within-generational over transgenerational plasticity if they are challenged by increasingly stressful environments, in this way allowing them to adjust their phenotypes to match the current conditions more optimally (Lampei, 2019; Dury and Wade, 2020). It would be interesting to find out whether shortening days would permit effects attributable to the interaction of the environments of both generations at the warmer temperature tested in this study. However, this approach would need to account for potential transgenerational effects of the photoperiod, as has been shown previously (Imaizumi et al., 2017). In contrast, when the environment of the progeny allowed for maternal effects to be expressed (18 °C), the environment of the mother plant before flowering regulated the response of the second generation to its own environment, regardless of the maternal environment after flowering. Cooler temperatures experienced within generation delay flowering in Arabidopsis plants (Blázquez et al., 2003; Lorenzo et al., 2016), and this effect is also true across generations. We found that offspring of mothers grown in cooler temperatures flowered later than those from mothers grown in warmer temperatures. Maternal environments have been shown to affect progeny flowering responses in different conditions: salinity and heat stress experienced by mother plants could advance flowering (Suter and Widmer, 2013a; Moriuchi et al., 2016). Our results are consistent with those reported by Groot et al. (2017), in which the third generation of plants grown in warmer temperatures showed earlier flowering in cases where their lineage was grown in the same conditions. The phenotypic plasticity of the progeny associated with the response to warming experienced by several generations could be understood as an adaptive strategy to the seasonal variation of temperature through generations, because high temperatures have negative effects on the life cycle of A. thaliana (Zinn et al., 2010), becoming a potential selection agent in its natural habitat (Wolfe and Tonsor, 2014). Thus, the parental effects we observed are likely to be adaptive, because the maternal environment is more accurately predicting the environment of the progeny, owing to matching environmental changes (Leverett et al., 2016; Auge et al., 2017a, b; Alvarez et al., 2021).

After flowering, the accumulation of reproductive biomass and seed size are measurements related to the resources invested in producing the next generation and are a strong indicator of fitness. These can be measured as total seed weight or seed area for a fitness proxy. We have not observed a maternal or two-generation effect (interaction of first- and second-generation environments) on the seed yield, but a strong within-generation effect instead. In line with this, the largest seeds were produced when G2 plants were grown in the cooler environment during their whole life cycles (regardless of the G1 plant treatments), indicating that the environment of the present generation is strongly determining fitness, matching the observed effect on seed weight. In addition, the observed detrimental effect of the warmer temperature suggests that for the summer annual Col-0, and probably also for other A. thaliana ecotypes, the coolest environment is the most favourable. Given that the daily temperature range for Col-0 in its defined natural range is between 15–16 and 21–22 °C (TAIR, 2023), it is highly likely that 24 °C has a mild stress effect on the production of reproductive biomass and allocation of nutrient supply (Groot et al., 2017). Additionally, seed size showed a strong response to the interaction between first- and second-generation environments, indicating that transgenerational effects are present in at least one trait related to propagule investment (Wang et al., 2015). Furthermore, we observed that a correlation between environments of both generations (i.e. when maternal and progeny environments matched) increased seed size, indicating that fitness enhances when previous environments are repeated (Marshall and Uller, 2007; Auge et al., 2023). In consequence, when comparing total seed weight and individual seed size, there is a trade-off between traits (number of seeds determined by weight and size). These results suggest that the adaptive strategy would be to produce seeds with more resources (larger seeds) to the detriment of the number of seeds. This strategy has been theorized to favour the evolution of parental effects when selection on viability (i.e. survival) is acting (Kuijper and Johnstone, 2021). Altogether, the results suggest that when experiencing environments that either favour or impair reproduction, within-generation effects are likely to constrain the expression of plasticity and the evolution of parental effects.

Our study demonstrates that adaptive transgenerational plasticity arises when environmental changes across generations are minimized and temporally correlated, favouring phenotypes related to fitness advantages (Hoyle and Ezard, 2012; Ezard et al., 2014). We did find that maternal effects could be concealed and that within-generation plasticity was favoured when maintaining transgenerational effects could lead to less desirable phenotypes, such as a delay in flowering at higher temperatures. To determine how the balance between within- and across-generation effects would contribute to plasticity, providing adaptive local variation and the best expression of life cycles, we would need to explore these response patterns and fitness costs and benefits in additional ecotypes. Although environmental effects are strong across generations, as demonstrated in this and other studies (Groot et al., 2017; Auge et al., 2017a; Latzel et al., 2023), their direction and strength show significant genetic variation (Auge et al., 2017a; Groot et al., 2017; Matesanz et al., 2022; Latzel et al., 2023), and our findings should be confirmed in other A. thaliana populations with different life histories. Nevertheless, our study shows that even non-stressful environmental changes, such as ambient temperatures that fall within the range of what A. thaliana plants typically experience in nature, can have significant consequences for plant development and fitness over generations and might enable the process of adaptation to broader environmental changes.

SUPPLEMENTARY DATA

Supplementary data are available at Annals of Botany online and consist of the following.

Figure S1: effect size and direction of G2 seed germination responses in both incubation conditions. Figure S2: direction and size of the effect of the environment of G2 plants on their flowering time for descendants of each environment of the first generation (y-axis). Figure S3: direction and size of the effect of the environment of G1 plants on the flowering time of the progeny. Figure S4: effect of the maternal environment on the area of Arabidopsis thaliana Columbia-0 G2 seeds.

mcad171_suppl_Supplementary_Figures_S1-S4
mcad171_suppl_supplementary_figures_s1-s4.docx (77.4KB, docx)

ACKNOWLEDGEMENTS

We thank Dr Mariana Barber, Tomas Deguer, Maria Clara Fontana and Virginia Ibarra for their technical help, and Dr Nora Madanes for valuable comments on the manuscript.

Contributor Information

Ailén Authier, Consejo Nacional de Investigaciones Científicas y Tecnológicas (CONICET), Buenos Aires, Argentina; Instituto de Biociencias, Biotecnología y Biología Traslacional (iB3), Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina.

Pablo Cerdán, Consejo Nacional de Investigaciones Científicas y Tecnológicas (CONICET), Buenos Aires, Argentina; Fundación Instituto Leloir, Instituto de Investigaciones Bioquímicas Buenos Aires – Consejo Nacional de Investigaciones Científicas y Tecnológicas (IIBBA – CONICET), Buenos Aires, Argentina.

Gabriela Auge, Consejo Nacional de Investigaciones Científicas y Tecnológicas (CONICET), Buenos Aires, Argentina; Instituto de Biociencias, Biotecnología y Biología Traslacional (iB3), Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina.

FUNDING

This work was supported by Agencia Nacional de Promoción de la Investigación, el Desarrollo Tecnológico y la Innovación (Agencia I+D+i), Argentina [grants no. PICT2016-0386 and PICT2020-A-00072 awarded to G.A., and PICT2016-0944 awarded to P.C.].

CONFLICT OF INTERESTS

The authors declare no competing interests, financial or otherwise.

DATA AVAILABILITY STATEMENT

Data can be accessed by following this link: https://osf.io/7uyqa

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

mcad171_suppl_Supplementary_Figures_S1-S4
mcad171_suppl_supplementary_figures_s1-s4.docx (77.4KB, docx)

Data Availability Statement

Data can be accessed by following this link: https://osf.io/7uyqa

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