Natural genetic variation underlying the negative effect of elevated CO2 on ionome composition in Arabidopsis thaliana

Océane Cassan; Léa-Lou Pimparé; Timothy Mozzanino; Cécile Fizames; Sébastien Devidal; Fabrice Roux; Alexandru Milcu; Sophie Lèbre; Alain Gojon; Antoine Martin

doi:10.7554/eLife.90170.2

eLife assessment

This paper provides useful information about how the ionome of Arabidopsis thaliana adapts to very high CO2-levels, backed up by solid evidence and carefully designed studies. The work will be of interest to anyone studying natural genetic variation as well as the response of plants to altered CO2 levels in the atmosphere.

https://doi.org/10.7554/eLife.90170.2.sa2

Significance of findings

useful: Findings that have focused importance and scope

landmark
fundamental
important
valuable
useful

Strength of evidence

solid: Methods, data and analyses broadly support the claims with only minor weaknesses

exceptional
compelling
convincing
solid
incomplete
inadequate

During the peer-review process the editor and reviewers write an eLife assessment that summarises the significance of the findings reported in the article (on a scale ranging from landmark to useful) and the strength of the evidence (on a scale ranging from exceptional to inadequate). Learn more about eLife assessments

Abstract

The elevation of atmospheric CO₂ leads to a decline in the plant mineral content, which might pose a significant threat to food security in the coming decades. To date, very few genes have been identified as having a role in the negative effect of elevated CO₂ on plant mineral composition. Yet, several studies have shown a certain degree of diversity in the ionome’s response to elevated CO₂, associated with genotypic variation. This suggests the existence of genetic factors controlling the effect of CO₂ on ionome composition. However, no large-scale studies have been carried out to date to explore the genetic diversity of the ionome responses to elevated CO₂. Here, we used six hundred Arabidopsis thaliana accessions, representing geographical distributions ranging from worldwide to regional and local environments, to analyze the natural genetic variation underlying the negative effect of elevated CO₂ on the ionome composition in plants. We show that the growth under elevated CO₂ leads to a global and important decrease of the ionome content whatever the geographic distribution of the population. We also observed a high range of genetic diversity in the response of the ionome composition to elevated CO₂, and we identified sub-populations, showing effects on their ionome ranging from the most pronounced to resilience or even to a benefit in response to elevated CO₂. Using genome-wide association mapping on the response of each mineral element to elevated CO₂ or on integrative traits, we identified a large set of QTLs and genes associated with the ionome response to elevated CO₂. Finally, we demonstrate that the function of one of these genes is associated to the negative effect of elevated CO₂ on the plant mineral composition. This resource will contribute to understand the genetic mechanisms underlying the negative effect of elevated CO₂ on plant mineral nutrition, and could help towards the development of crops adapted to a high-CO₂ world.

Introduction

The elevation of atmospheric CO₂ concentration leads to a decline in the mineral composition of C3 plants (Gojon et al., 2023). The negative effect of elevated CO₂ on plant mineral composition has been observed worldwide, and alters the content of nutrients that are essential for human nutrition, such as nitrogen (N) and proteins, iron (Fe) or zinc (Zn) (Loladze, 2014). Therefore, the rise in atmospheric CO₂ poses a significant threat to food security in the coming decades. Indeed, several modeling approaches predict a decrease in plant-based nutrient availability due to the negative effect of elevated CO₂ on the mineral status of plants, leading to an additional risk of nutritional deficiency for hundreds of millions of people (Medek et al., 2017; Ebi and Loladze, 2019). However, the reasons why elevated CO₂ leads to the degradation of plant mineral composition are far from being well understood. To date, only a few genes with a potential regulatory role on this effect have been identified (Gao et al., 2019; Umnajkitikorn et al., 2020; Yang et al., 2020; Bouain et al., 2022; Sun et al., 2022; Cassan et al., 2023). Despite their limited number, these studies show that the detrimental effect of high CO₂ on the plant mineral status has genetic bases. In addition to this, several reports suggest that exploring the natural genetic variability of plants represents a major opportunity to understand the mechanisms by which high CO₂ leads to a decline in plant mineral composition (Myers et al., 2014; Zhu et al., 2018; Marcos-Barbero et al., 2021). Indeed, a significant diversity in the response of mineral composition to high CO₂ has been observed in several plant species. For protein and therefore N content, as well as for Fe or Zn content, substantial variations have been observed between small panels of genotypes from different species (Myers et al., 2014; Zhu et al., 2018; Marcos-Barbero et al., 2021). This implies the presence of a genetic diversity reservoir, which can facilitate the understanding of the ionome’s response to high CO₂ and subsequently provide an opportunity to alleviate this negative impact. However, in order to identify the genetic determinants of this negative response of the ionome to high CO₂, large-scale approaches are necessary, but are still lacking for the moment. The objective of this work was to fill the aforementioned knowledge gap by using a large collection of natural genotypes of the model plant Arabidopsis thaliana. This allowed to explore in depth the natural variation of the ionome response to elevated CO₂, and to generate a resource of phenotypic data that can be used in association genetics approaches. To this end, we used several hundreds of accessions from different geographic scales of A. thaliana, and analyzed their leaf mineral composition under contrasted conditions of CO₂ concentration. This allowed us to extract the general trends in the leaf ionome response to high CO₂, and to identify a large set of genes associated with the variation in the mineral composition of plants in response to high CO₂. By combining this information with genome expression data under elevated CO₂, we end up by functionally validating one of these genes for its importance in the reduction of Zn content under elevated CO₂. Our results open the way for a better understanding of the genetic and molecular mechanisms involved in the regulation of plant mineral nutrition by the elevation of atmospheric CO₂.

Results

In order to explore the natural variation and identify its underlying genetic basis associated with the negative effect of elevated CO₂ on plant ionome, we used three populations of A. thaliana representing different geographic scales (i.e., the worldwide REGMAP population, the LANGUEDOC regional population and the local TOU-A population from east of France) and displaying different levels of genetic diversity (Fig. 1A). These populations were grown under ambient or elevated CO₂, and we measured in each accession the composition of their ionome in rosettes, including C, N, Na, Fe, Mg, Mn, Zn and Cu content.

Elevated CO₂ negatively impacts the ionome content at the population-scale level in *Arabidopsis thaliana*.
A. Representation of the experimental design used in this study. The content of eight mineral elements was assessed for around 600 *Arabidopsis thaliana* accessions coming from the REGMAP (B), LANGUEDOC (C) and TOU-A (D) populations. Each dot represents the value of the content of a mineral element for one accession (yellow: ambient CO₂ (aCO₂, ∼420 ppm), blue: elevated CO₂ (eCO₂, 900 ppm). N (% of dry weight), Fe (µg.g^-1 dry weight), Zn (µg.g^-1 dry weight), Cu (µg.g^-1 dry weight), Mg (µg.g^-1 dry weight), Mn (µg.g^-1 dry weight), Na (µg.g^-1 dry weight), C (% of dry weight). Asterisks indicate significant differences (Paired Wilcoxson test; *, P < 0.05; **, P < 0.005; ***, P < 0.0005). ns; not significant.

Elevated CO₂ globally decreases ionome content at the population level, whatever the geographic scale

In the three A. thaliana populations, we observed a global and important decrease of the ionome content when plants were grown under elevated CO₂ as compared to ambient CO₂. This was particularly the case for N and Fe, for which the decrease in content was very robust and important in each of the population analyzed (Fig. 1B-D). Zn, Cu and Mg content were also negatively affected to a significant extent by the growth under elevated CO₂ in the REGMAP and in the TOU-A populations (Fig. 1B, C), although not significantly in the LANGUEDOC population (Fig. 1D). More variability for the effect of elevated CO₂ was observed on Mn and Na content, which were decreased in the REGMAP population, but not significantly changed in the TOU-A and LANGUEDOC populations, respectively. In parallel, the C content of these populations increased under elevated CO₂, by very significant factors for the REGMAP and the LANGUEDOC populations. Altogether, these observations demonstrate that elevated CO₂ has on average a negative impact on the mineral content of natural genotypes of A. thaliana at the population-scale, whatever their geographic distribution.

The ionome of Arabidopsis thaliana natural accessions displays a high range of phenotypic diversity in response to elevated CO₂

To explore the effect of elevated CO₂ in each accession, we calculated the relative change in nutrient composition of A. thaliana accessions from the three populations in response to elevated CO₂. In agreement with the results previously mentioned, we observed that the median relative change of most nutrient content at the population-level was negatively affected by elevated CO₂ (Fig. 2). But the most striking observation was the genetic diversity of ionome response observed in these populations. Indeed, while most the natural accessions were negatively affected by elevated CO₂ (with a negative relative ratio of their nutrient content between ambient and elevated CO₂), a considerable number of accessions were rather not affected by elevated CO₂, or even positively affected, therefore showing an improved nutrient composition under elevated CO₂. For macronutrients like N, the relative change of concentration between ambient and elevated CO₂ varied from 20% to -50%, and for micronutrients like Cu, Fe or Zn, the relative change of concentration between ambient and elevated CO₂ varied from 100% to -60% (Fig. 2). In addition, some differences among nutrients were observed between populations. For instance, a smaller dispersion of Fe relative change in the LANGUEDOC population, against a higher distribution of Mn relative change.

Elevated CO₂ leads to high phenotypic diversity of ionome response in *Arabidopsis thaliana.*
Distributions of the relative change (%) of the content of 8 mineral elements between elevated CO₂ and ambient CO₂, in each population (A: REGMAP, B: LANGUEDOC, C: TOU-A). Each dot represents the value of the relative change of the content a mineral element for one accession. The name of the element appears in bold if the mean of the element in elevated CO₂ is significantly different from the mean of the element in ambient CO₂ (Paired wilcoxon test, significance threshold of 0.05).

In order to explore the behavior of the different elements in response to elevated CO₂ and to observe the structure of phenotypic variation, we performed a principal component analysis (PCA) of the relative change in the 8 elements for the accessions from the three populations. The accessions from all populations seem to have globally similar responses to elevated CO₂, as suggested by the overlap of the three populations in the two first principal components (Fig. 3A). The first component of the PCA described a clear antagonistic trend between C content and the change of other mineral elements (Fig. 3B), suggesting that most of the variation between accessions in term of mineral response (almost 40%) could be driven by one or a few mechanisms resulting in an inverse variation between the whole ionome and C change (Fig. 3B). Interestingly, the second component, explaining almost 15% of the variation among accessions in term of mineral response, was mainly driven jointly by change in N and C concentration. Altogether, these results show that there is a marked and large variability among accessions in their mineral concentration in response to elevated CO₂, illustrated by accessions negatively affected by elevated CO₂ and others positively affected by elevated CO₂.

Elevated CO₂ results in a general pattern of ionome variation common to most accessions constituting natural populations of *Arabidopsis thaliana.*
Principal Component Analysis (PCA) was performed using the variation of each element in response to elevated CO₂. A. Natural accessions were positioned on the PCA and colored based on population. B. Contribution of each element to the PCA axis.

In order to explore specific behavior of sub-populations, we clustered the accessions from the REGMAP panel via a k-means approach. This multivariate clustering resulted in the partitioning of accessions in three groups (Fig.4 – Suppl. Table 1). Cluster 1 displayed the most negative pattern of ionome response to elevated CO₂. Inversely, accessions included in Cluster 2 displayed a globally positive response, with the highest relative change for almost all mineral elements, except for C content. These accessions did not appear to be clustered geographically with respect to their collection origin in the REGMAP panel (Suppl. Fig. 1), which is in line with the high genetic diversity of response to elevated CO₂ observed at smaller geographical scales (Fig.2). Finally, Cluster 3 displayed a resilient pattern, with accessions showing a globally attenuated response to elevated CO₂. Interestingly, the large phenotypic diversity of the ionome observed in the three populations in response to high CO₂, as well as the presence of contrasted subpopulations in the REGMAP panel, suggests the presence of genetic determinants associated with this response.

Variation in the response of the ionome to elevated CO₂ identifies contrasting subpopulations inside the REGMAP panel.
K-means clustering was performed in the REGMAP accessions to identify different subpopulations. Each accession is represented by a dot, connected by a line between each element. Cluster 1:65 accessions. Cluster 2: 25 accessions. Cluster 3: 69 accessions.

Genetic architecture of the ionome response to elevated CO₂, and identification of genetic determinants

We ran Genome-Wide Association (GWA) mapping to describe the genetic architecture of the ionome response to elevated CO₂, and to fine-map candidate genes underlying the detected quantitative trait loci (QTLs). We focused here on the phenotypic data collected on the REGMAP population, and used the sequencing data available for this population (Arouisse et al., 2020). We included in this analysis the level of each mineral under ambient and under elevated CO₂, as well as the relative change between ambient and elevated CO₂ for each element. We also included a trait corresponding for each accession to the coordinate on the first and on the second PCA axes (PCA1 and PCA2) explaining collectively more than 50% of ionomic variation (Fig. 3). Therefore, these values correspond to traits driving and summarizing a large part of the ionome variation under elevated CO₂. This resulted as a whole in running GWA mapping on 30 different single-trait GWAS. The overall approach was first validated by observing expected results for traits phenotyped under ambient CO₂. For instance, we observed a very strong peak for the Na content at the locus of the HKT1 gene (Suppl. Fig. 2A), which is known to be involved in the natural genetic variation of Na content in Arabidopsis thaliana (Baxter et al., 2010), or a strong peak for the N content at the locus of the NIA1 gene (Suppl. Fig. 2B), encoding for an isoform of the nitrate reductase required for the first step of nitrate reduction and associated with natural genetic variation of N content in A. thaliana (North et al., 2009).

GWA mapping revealed a polygenic architecture for each phenotypic trait, although its complexity largely differs among traits. For instance, very few and neat peaks of association were detected Na and Mn content under elevated CO2, or of Fe and Cu relative change between ambient and elevated CO₂ (Fig.5A, Suppl. Fig. 3). On the other hand, a more complex genetic architecture with the detection of a large number of QTLs was observed for traits related to N or C content (Fig.5A, Suppl. Fig. 3). For each of the traits that have been analyzed under elevated CO₂ or corresponding to the relative change of their content between ambient and elevated CO₂, we isolated the 50 SNPs with the most significant p-value, hereafter named top SNPs (Fig. 5A, Suppl. Tables 2 and 3). In order to identify the overlap between the genetic architecture of each trait, we looked whether some of the top SNPs were shared among traits. While the large majority of SNPs were specific to one trait, 30 and 21 SNPs were shared between two traits for the content under elevated CO₂ or for the relative change between ambient and elevated CO₂, respectively (Fig. 5B and C, Supplemental Tables 2 and 3). In addition, 8 and 2 SNPs were shared between three traits for the content under elevated CO₂ or for the relative change between ambient and elevated CO₂, respectively (Fig. 5B and C, Supplemental Tables 2 and 3). Most of the shared SNPs were associated with micronutrients (Fe, Mn, Zn and Mg content) and with N and/or with the first component of the PCA axis. An interesting QTL located on chromosome 1 was notably associated with 6 traits, displaying SNPs shared between Mn, Zn and N relative change and SNPs shared between Mn, N and PC1 content under elevated CO₂ (Fig. 5A, Suppl. Tables 2 and 3). Another QTL located on chromosome 3 encompasses SNPs shared between Fe, Zn and PC1 content under elevated CO₂ (Fig. 5A, Suppl. Table 2).

Genetic architecture of the response of the ionome to elevated CO₂ in the REGMAP panel of *Arabidopsis thaliana.*
A. Manhadan plots for the content of eight mineral elements under elevated CO₂, or for the relative change of the content of mineral elements between elevated CO₂ and ambient CO₂. For each Manhadan plot, SNPs with the 50 most significant P-value, located above the horizontal line, are colored. Bar plots showing the number of SNPs identified by GWAs for traits under elevated CO₂ (B) or for the relative change of the content of mineral elements between elevated CO₂ and ambient CO₂ (C) that are unique to one element or shared between 2 or 3 traits.

We next identified for each trait a list of the genes located at ±25 kb from the top 50 SNPs, which corresponds to the rough estimate of the decay of linkage disequilibrium identified in A. thaliana at the worldwide scale (Kim et al., 2007). This resulted in a list of genes for each element, ranging from 154 to 422 genes depending on the element (Suppl. Tables 2 and 3). Among others, several genes associated with top 50 SNPs were identified as obvious candidates of the effect of elevated CO₂ on plant nutrition and ionome content. This was the case of ZINC INDUCED FACILITATOR 1 (ZIF1, AT5G13740) and ZIF-LIKE1 (AT5G13750), linked with SNPs identified for Zn content under elevated CO₂, and involved Zn sequestration mechanisms (Lee et al., 2021). We also noticed the link between SNPs identified for Zn relative change and TIP2;2 (AT4G17340), known to be involved in Zn root-to-shoot translocation (Wang et al., 2022). Concerning N relative change, some of the top 50 SNPs were linked to ASN1 (AT3G47340), which is an actor of N status and remobilization (Lam et al., 2003; Gaufichon et al., 2017). Some of the top 50 SNPs identified for Fe relative change were linked to MCO2 (AT5G21100) and MCO3 (AT5G21105) genes, which have been recently characterized as actors of the regulation of Fe homeostasis (Brun et al., 2022). Finally, it is interesting to note that the QTL located on chromosome 3 mentioned above displaying significant shared SNPs identified for Fe, Zn and PC1 content under elevated CO₂ was associated among other genes with ISU2 (AT3G01020), coding for one of the Fe-S clusters in Arabidopsis thaliana, which are known to be essential for photosynthesis and metabolism (Balk and Schaedler, 2014). Altogether, this demonstrated that genes identified through this approach represent a large and valuable reservoir of candidates to study and to counteract the effect of elevated CO₂ on plant nutrition and ionome content.

To analyze how these genes identified by GWA mapping are regulated by elevated CO₂, we performed RNA-seq from shoots and roots grown under ambient and elevated CO₂. Differentially expressed genes (DEG) associated to the effect of elevated CO₂ were identified from shoots and roots (Suppl. Table 4). We compared the list of shoots or roots elevated CO₂-DEG with the list of genes identified by GWA mapping for each element, which resulted in a list of 182 genes identified by GWA mapping and differentially regulated by elevated CO₂ in shoot or in roots (Suppl. Table 5), making them relevant candidates to be involved in the response of the mineral composition of plants to elevated CO₂. Most of these genes were deregulated by elevated CO₂ in shoot (Fig. 6A, B). In shoot or in roots, these genes mainly showed an association with C-, Mg- or Zn-related traits (Fig. 6A, B). Several of these genes, identified by GWA mapping and whose expression is deregulated in response to high CO₂, were known for their role in nutrient homeostasis. This was the case for the ASN1 and DUR3 genes, encoding an asparagine synthase and a urea transporter involved in N metabolism and remobilization, both associated here with a N-related peak of association, and whose expression is modulated by high CO₂ in leaves (Fig. 6C). We also observed in the leaves an interesting profile for several genes related to C metabolism and photosynthesis. This was the case for the BGP3 gene, involved in chloroplast development, or for the carbonic anhydrase CA1, both showing a decreased expression in response to high CO₂ and both associated with a peak in C-related GWA mapping under elevated CO₂ (Fig. 6C). In roots, the gene most deregulated in response to high CO₂ was AT1G64710, encoding a GroES-type alcohol dehydrogenase, which interestingly is also deregulated in leaves (Fig. 6D). We also observed in the roots that the expression of the TIP2;2 gene, associated here with a peak detected for Zn relative change GWA mapping, was deregulated in response to elevated CO₂ (Fig. 6D).

Identification of genes detected by GWA mapping and differentially regulated by elevated CO₂.
Intersection between elevated CO₂-DEG in shoot (A) or root (B) and genes identified by GWA mapping. UpSet plots display the number of elevated CO₂-DEG that are associated to a locus identified for the content or the relative change of one or several mineral elements under elevated CO₂. Illustration of the padern of elevated CO₂-DEG in shoot (C) or root (D) also identified by GWA mapping.

To go further, we selected one of the association peaks identified by GWA mapping, and sought to functionally validate the importance of this QTL in response to elevated CO₂, in order to demonstrate the value of our data set and GWA mapping analyses. To do so, we selected an association peak located on chromosome 4 and associated with Zn relative change (Fig. 7A). More precisely, this association peak displayed the SNPs with the most significant p-values and more largely three SNPs that fell into the top 10 SNPs of the trait corresponding to the Zn relative change between ambient and elevated CO₂. The SNPs corresponding to the alternative alleles were associated to an increase of Zn content under elevated CO₂ (Fig. 7B). These SNPs are located very close to the TIP2;2 (AT4G17340) gene, which has been recently characterized as an actor of Zn root-to-shoot translocation (Wang et al., 2022). We thus selected a set of accessions from haplotype 0 (reduced Zn content under elevated CO₂) or haplotype 1 (increased Zn content under elevated CO₂), and analyzed TIP2;2 expression in the roots under ambient and elevated CO₂. This analysis revealed a haplotype-specific difference in TIP2;2 expression: under ambient and elevated CO₂, accessions from haplotype 1 (correlated with a higher Zn content in the shoot (Fig. 7B)) show a reduced TIP2;2 expression in the roots compared to those from haplotype 1 (Fig. 7C & D), with a reduction being more pronounced under elevated CO₂. To test the effect of TIP2;2 expression of Zn content under elevated CO₂, we used the tip2;2-1 knock-out mutant and compared its Zn content under ambient and elevated CO₂ to this of the WT. We observed that the tip2;2-1 mutant line did not present any decrease in Zn shoot content in response to elevated CO₂, in opposition to what is observed for the WT (Fig. 7E). In the tip2;2-1 mutant, Zn content under elevated CO₂ was even slightly higher than under ambient CO₂. Altogether, these results demonstrated that these data sets generated in this study and the associated analyses are a valuable resource to identify genes and associated mechanisms involved in the effect of elevated CO₂ on the mineral composition of plants.

Natural variation of the *TIP2;2* gene is associated with improved responses of Zn content to elevated CO₂.
A. Manhattan plot of the relative change of Zn content between elevated CO₂ and ambient CO₂ showing the presence of a peak closed to the *TIP2;2* locus. B. Comparison of haplotypes and their relative change of Zn content between elevated CO₂ and ambient CO₂. Three SNPs located at the *TIP2;2* locus are associated to an improvement of Zn content under elevated CO₂ for accessions that possess them (haplotype 1) compared to the rest of the population (haplotype 0). **C, D.** Relative expression of *TIP2;2* in the roots under ambient (C) or elevated (D) CO₂ for accessions belonging to haplotype 0 or haplotype 1. Relative expression levels were calculated based on *UBQ10* as internal control. Horizontal black line represented the median of each group of haplotypes. ***P < 0,001, **P < 0,01, unpaired Mann-Whitney test. E. Shoot Zn content under ambient or elevated CO₂ for WT (Columbia) and *tip2;2-1* mutant. Data are presented as the mean (with SD) of 5 and 6 biological repeats for the WT and *tip2;2-1*, respectively.**P < 0.01, unpaired Mann-Whitney test.

Discussion

The natural variation of ionome response to elevated CO₂ in Arabidopsis thaliana displays a high degree of genetic variation

In the present work, we analyzed the diversity of leaf ionome response to elevated CO₂ present in the natural variation of Arabidopsis thaliana. In agreement with several other phenotypic traits related to phenology and disease resistance (Brachi et al., 2013; Huard-Chauveau et al., 2013; Roux and Frachon, 2022), we observed a wide range of responses at complementary geographical scales, from accessions with an ionome negatively affected by high CO₂ to accessions with an ionome benefiting from high CO₂. This confirms for the first time on large and complementary sets of natural genotypes what has been observed by meta-analysis on isolated groups of plants worldwide (Loladze, 2014; Myers et al., 2014). The global analysis of the distribution of each mineral element studied suggests firstly a trend where the whole ionome would evolve in a unified manner in response to high CO₂, and in an opposite manner to C. This is in line with a number of studies that have proposed that the accumulation of carbohydrates due to the stimulation of photosynthesis by high CO₂ would be the cause of the decrease in plant mineral composition (Ainsworth and Long, 2005; Thompson et al., 2017; Dusenge et al., 2019; Tausz-Posch et al., 2020). However, the reading of the genetic architecture performed here by a genome-wide association genetics approach suggests that the majority of the genetic mechanisms underlying the negative effect of elevated CO₂ on the ionome are specific to each mineral element. Some specific cases, such as the QTL detected on chromosome 1 and associated with the natural genetic variation of 6 traits among the 20 considered, will certainly deserve a more in-depth analysis.

By clustering globally distributed accessions according to their ionome sensitivity to high CO₂, we were able to observe that the geographic origin of the accessions likely did not determine their response to CO₂. This suggests that inherent genetic factors, more than those due to local adaption, direct the response of plants to elevated CO₂. This seems consistent since the CO₂ elevation applied here to natural Arabidopsis thaliana variants does not correspond to any environment experienced by plants yet, at least for several tens of millions of years (Pearson and Palmer, 2000; Luthi et al., 2008). In this context of brutal and highly impactful environmental change, the presence of cryptic genetic variation often explains the appearance of relatively rapid adaptive mechanisms (Pauls et al., 2013; Cortés and López-Hernández, 2021). Although not formally tested here, it would be interesting to examine whether the variation in the ionome in response to elevated CO₂ shows evidence of cryptic variation. In any case, the presence of high phenotypic diversity in these natural populations of A. thaliana demonstrates very clearly the possibility of taking advantage of this genetic variation to understand and alleviate the negative response of plant mineral composition to high CO₂.

GWA mapping of ionome variation under elevated CO₂ identified a large number of genes to understand and mitigate the negative effect of high CO₂ on plant mineral composition

In order to understand the genetic mechanisms underlying the effect of high CO₂ on plant mineral composition, and to enable future breeding approaches, we adopted an association genetics approach. This led to the identification of a large number of candidate genes associated to the variation of nutrients under elevated CO₂. Several genes in this list can easily attract attention. In particular, we can note the identification of ASN1 and DUR3 genes in two of the loci associated with N content variation under elevated CO₂. ASN1, and to a lesser extent DUR3, play an important role in the remobilization and the reallocation of N within the plant, and their manipulation can lead to variation in N use efficiency (Lam et al., 2003; Bohner et al., 2015; Gaufichon et al., 2017). This is interesting because for the moment, root N uptake and N assimilation seemed to be the key targets of the negative effect of high CO₂ on plant N content (Bloom et al., 2010; Cassan et al., 2023), but these results suggest that remobilization of N may also be involved. We also identified the CA1 gene, coding for a carbonic anhydrase, in the vicinity of a QTL associated with C variation under high CO₂. CA1 is involved in the regulation of stomatal opening by elevated CO₂ (Hu et al., 2015), and the β carbonic anhydrase family of which CA1 belongs is involved in the regulation of photosynthetic efficiency, although CA1 shows no significant effect under standard conditions (Sharma et al.). It would be therefore interesting to assess the role of CA1 natural genetic variation under elevated CO₂. If CA1 regulates the C variation of the ionome under elevated CO₂, this could, according to our observations, significantly influence the global mineral composition of plants. Interestingly, the genes identified by GWA mapping in the ionome response to high CO₂, including those mentioned above, showed substantial variation at the gene expression level. We ended this study with the functional validation of an association peak identified by GWA mapping for the relative change of Zn content between ambient and elevated CO₂. Zn is an essential element for a large number of metabolic processes in humans, and Zn deficiency, found in up to one third of the world’s population, leads to severe health problems. We demonstrated that TIP2;2 gene expression varied in a haplotype-specific manner, in both ambient and elevated CO₂. In parallel to this, we show that loss of TIP2;2 expression using a knock-out mutant can abolish the Zn decrease observed under high CO₂. It therefore seems that variation in TIP expression is associated with the effect that atmospheric CO₂ can have on zinc levels. A recent study demonstrated that TIP2;2 was responsible for Zn retention in the roots (Wang et al., 2022). It therefore seems consistent that natural accessions with the lowest expression levels of this gene are those with the highest Zn content in aerial parts, due to low retention in their roots. This example illustrates the potential of the resource we have generated here towards the identification of genes involved in the variation of leaf ionome in response to rising CO₂, and towards the characterization of the associated mechanisms. The understanding of these mechanisms represents a considerable challenge in view of the current rise in atmospheric CO₂, which might be useful to the coming breeding programs for crops adapted to a forthcoming CO₂-rich atmosphere (Shahzad and Rouached, 2022). It must however be recalled that leaf ionome is not always correlated with seed ionome, in particular in Arabidopsis thaliana accessions (Campos et al., 2021). Therefore, the effect of elevated CO₂ on seed ionome, certainly in major crops, must be the next target to analyze in order to pave the way for the development of nutritious crops adapted to elevated CO₂.

Methods

Data and code availability

Data and R notebooks containing the analyses performed in this article can be found at https://src.koda.cnrs.fr/groups/ipsim/sirene-team. RNA-seq data generated for this study are available at https://www.ebi.ac.uk/biostudies/arrayexpress/studies using the accession no E-MTAB-13661.

Plant Material

A subset of the REGMAP panel, the LANGUEDOC panel and the TOU-A panel were used in this study. These populations were previously described here (Horton et al., 2012; Brachi et al., 2013; Frachon et al., 2017). These populations were grown on Jiffy-7 peat pellets (Jiffy Products International, NL) under ambient (∼420 ppm) or elevated (900 ppm) CO₂ in the growth chambers of the Microcosms experimental platform at the Montpellier European Ecotron CNRS. Five replicates of each accession were randomly distributed in the growth chambers. The concentration of 900 ppm of CO₂ was chosen as current CO₂ emissions align with the IPCC’s RCP8.5 model, which predicts a CO2 concentration of around 900 ppm in 2100. Growth conditions were 6-h/22-h light (22°C) / dark (20°) photoperiod, with 200 µmol m^-2 s^-1 light intensity and 65% of hygrometry. Plants were watered twice a week with a growth solution containing KH₂PO₄ 1 mM, MgSO₄ 1 mM, K₂SO₄ 250 µM, CaCl₂ 250 µM, Na-Fe-EDTA 100 µM, KNO₃ 10 mM, KCl 50 µM, H₃BO₃ 30 µM, MnSO₄ 5 µM, ZnSO₄ 1 µM, CuSO₄ 1 µM, (NH₄)₆Mo₇0₂₄ 0,1 µM, as described by (Gansel et al., 2001). The entire rosettes were collected three weeks after sowing. The tip2;2-1 mutant line corresponds to the SALK_152463 allele (Wang et al., 2022).

Ionome analysis

From 3 to 5 replicates per accession were pooled and used for each ionome analysis. Total C and N content was obtained from dried shoot tissue using an Elementar Pyrocube analyzer. Cu, Fe, Mg, Mn, Na and Zn content was obtained from dry shoot tissue mixed with 750 µl of nitric acid (65% [v/v]) and 250 µl of hydrogen peroxide (30% [v/v]). After one night at room temperature, samples were mineralized at 85°C during 24 hours. Once mineralized, 4 ml of milliQ water was added to each sample. Mineral contents present in the samples were then measured by microwave plasma atomic emission spectroscopy (MP-AES, Agilent Technologies).

Removal of outlier observations

Prior to GWAS and multivariate analyses such as PCA or clustering, mineral composition measures were pre-processed to remove technical outliers. For a given element and CO₂ condition, the values positioned more than 5 median absolute deviations away from the median were removed from the dataset. The number of outliers removed from each dataset is indicated in Supplemental Table 7.

PCA and Clustering

Principal Component Analysis was performed using the R ade4 package after the prior scaling of the variables to a z-score. Clustering of the REGMAP panel based on the relative changes of the mineral composition of each accession has been done using a k-means clustering with the R kmeans function. For this step, the variables were also scaled to a z-score. The number of clusters in the k-means algorithm was chosen by the elbow method on the criteria of cluster homogeneity (within-sum of squares).

GWAs

Genome-Wide Association mapping was performed using the R statgenGWAs package. Genotype data was prepared using the codeMarkers function, removing duplicated SNPs and filtering for a minimum allele relative frequency of 0.04. Associations were performed by the runSingleTraitGwas function, that implements the EMMA algorithm. Population structure was modeled via a kinship matrix built from the Astle method. Manhattan plots were drawn using the manPlotFast function of the ramwas R package.

RNA-seq experiments

Plants from the Columbia accession were grown in hydroponics to have access to the roots in addition to the shoot, as previously described in (Cassan et al., 2023). Shoot or root from 5 plants were pooled into one biological replicate, flash frozen in liquid nitrogen, and stored at -80◦C. RNA of three biological replicates were extracted from shoot or root tissues using Direct-zol RNA Miniprep (Zymo Research, CA, USA), according to the manufacturer recommendations. RNA-sequencing libraries were done from shoot or root total RNA using standard RNA-Seq protocol method (Poly-A selection for mRNA species) by the Novogene company. RNA-sequencing was performed using Illumina technology on a NovaSeq6000 system providing PE150 reads. The quality control and adapter trimming of raw paired-end fastq files was done with fastp and its default parameters. Mapping to the TAIR10 reference genome was performed with STAR, and using the following options:

--outSAMtype BAM SortedByCoordinate

--outFilterMismatchNmax 1

--outFilterMismatchNoverLmax 0.15

--alignIntronMin 30

--alignIntronMax 5000

Quantification of the bam files against the TAIR10 GFF3 annotation file was done using htseq- count with options:

-f bam --type gene -r pos

--idattr=Name --stranded=no

Normalization and differential expression were performed using DIANE R package (Cassan et al., 2021), with no fold change constraint, and an adjusted p-value threshold (FDR) of 0.05. Lowly expressed genes with an average value across conditions under 25 reads were excluded from the analysis.

Quantitative real-time PCR

Plants were grown in hydroponics to have access to the roots, as previously described in (Cassan et al., 2023). Root tissue from 5 plants were pooled into one biological replicate, flash frozen in liquid nitrogen, and stored at -80◦C. RNA were extracted from shoot or root tissues using TRIZOL (Invitrogen, USA), according to the manufacturer recommendations, and DNAse treated using RQ1 (Promega, USA). Reverse transcription was achieved from 1 𝜇g of total RNA with M-MLV reverse transcriptase (RNase H minus, Point Mutant, Promega, USA) using an anchored oligo(dT)20 primer. Accumulation of transcripts was measured by qRT-PCR (LightCycler 480, Roche Diagnostics, USA) using the SYBR Premix Ex TaqTM (TaKaRa, Japan). Gene expression was normalized using UBQ10 and ACT2 as internal standards. Results are presented as the expression relative to UBQ10. Sequences of primers used in RT-qPCR for gene expression analysis are listed in Supplemental Table 6.

Acknowledgements

This work was supported by the I-Site Montpellier Université d’Excellence (MUSE; project ECO2THREATS), the CNRS through the Mission for Transversal and Interdisciplinary Initiatives (MITI) 80 PRIME program, and the Plant Biology and Breeding department of INRAE. O.C. was recipient of a PhD fellowship from the CNRS. T.M. was recipient of a PhD fellowship from INRAE and Région Occitanie. We thank Jiping Liu from Cornell University for the gift of tip2;2-1 mutant line. This study benefited from the CNRS human and technical resources allocated to the Ecotron Research Infrastructure and from the state allocation “Investissement d’Avenir” AnaEE France ANR-11-INBS-0001. A CC-BY public copyright license has been applied by the authors to the present document.

References

1. Ainsworth E.A.
2. Long S.P
2005What have we learned from 15 years of free-air CO2 enrichment (FACE)? A meta-analytic review of the responses of photosynthesis, canopy properties and plant production to rising CO2New Phytol 165:351–371
1. Arouisse B.
2. Korte A.
3. van Eeuwijk F.
4. Kruijer W.
2020Imputation of 3 million SNPs in the Arabidopsis regional mapping populationThe Plant Journal 102:872–882
1. Balk J.
2. Schaedler T.A
2014Iron cofactor assembly in plantsAnnu Rev Plant Biol 65:125–153
1. Baxter I.
2. Brazelton J.N.
3. Yu D.
4. Huang Y.S.
5. Lahner B.
6. Yakubova E.
7. Li Y.
8. Bergelson J.
9. Borevitz J.O.
10. Nordborg M.
11. Vitek O.
12. Salt D.E
2010A Coastal Cline in Sodium Accumulation in Arabidopsis thaliana Is Driven by Natural Variation of the Sodium Transporter AtHKT1;1PLOS Genetics 6
1. Bloom A.J.
2. Burger M.
3. Rubio Asensio J.S.
4. Cousins A.B
2010Carbon dioxide enrichment inhibits nitrate assimilation in wheat and ArabidopsisScience 328:899–903
1. Bohner A.
2. Kojima S.
3. Hajirezaei M.
4. Melzer M.
5. von Wirén N.
2015Urea retranslocation from senescing Arabidopsis leaves is promoted by DUR3-mediated urea retrieval from leaf apoplastThe Plant Journal 81:377–387
1. Bouain N.
2. Cho H.
3. Sandhu J.
4. Tuiwong P.
5. Prom U.T.C.
6. Zheng L.
7. Shahzad Z.
8. Rouached H
2022Plant growth stimulation by high CO2 depends on phosphorus homeostasis in chloroplastsCurr Biol
1. Brachi B.
2. Villoutreix R.
3. Faure N.
4. Hautekèete N.
5. Piquot Y.
6. Pauwels M.
7. Roby D.
8. Cuguen J.
9. Bergelson J.
10. Roux F
2013Investigation of the geographical scale of adaptive phenological variation and its underlying genetics in Arabidopsis thalianaMolecular Ecology 22:4222–4240
1. Brun A.
2. Smokvarska M.
3. Wei L.
4. Chay S.
5. Curie C.
6. Mari S.
2022MCO1 and MCO3, two putative ascorbate oxidases with ferroxidase activity, new candidates for the regulation of apoplastic iron excess in ArabidopsisPlant Direct 6
1. Campos A.
2. van Dijk W.F.A.
3. Ramakrishna P.
4. Giles T.
5. Korte P.
6. Douglas A.
7. Smith P.
8. Salt D.E.
20211,135 ionomes reveal the global pattern of leaf and seed mineral nutrient and trace element diversity in Arabidopsis thalianaPlant J 106:536–554
1. Cassan O.
2. Lebre S.
3. Martin A
2021Inferring and analyzing gene regulatory networks from multi-factorial expression data: a complete and interactive suiteBMC Genomics 22
1. Cassan O.
2. Pimpare L.L.
3. Dubos C.
4. Gojon A.
5. Bach L.
6. Lebre S.
7. Martin A
2023A gene regulatory network in Arabidopsis roots reveals features and regulators of the plant response to elevated CO(2)New Phytol 239:992–1004
1. Cortés A.J.
2. López-Hernández F
2021Harnessing Crop Wild Diversity for Climate Change AdaptationGenes 12
1. Dusenge M.E.
2. Duarte A.G.
3. Way D.A
2019Plant carbon metabolism and climate change: elevated CO2 and temperature impacts on photosynthesis, photorespiration and respirationNew Phytol 221:32–49
1. Ebi K.L.
2. Loladze I
2019Elevated atmospheric CO(2) concentrations and climate change will affect our food’s quality and quantityLancet Planet Health 3:e283–e284
1. Frachon L.
2. Libourel C.
3. Villoutreix R.
4. Carrere S.
5. Glorieux C.
6. Huard-Chauveau C.
7. Navascues M.
8. Gay L.
9. Vitalis R.
10. Baron E.
11. Amsellem L.
12. Bouchez O.
13. Vidal M.
14. Le Corre V.
15. Roby D.
16. Bergelson J.
17. Roux F.
2017Intermediate degrees of synergistic pleiotropy drive adaptive evolution in ecological timeNat Ecol Evol 1:1551–1561
1. Gansel X.
2. Munos S.
3. Tillard P.
4. Gojon A
2001Differential regulation of the NO3- and NH4+ transporter genes AtNrt2.1 and AtAmt1.1 in Arabidopsis: relation with long-distance and local controls by N status of the plantPlant J 26:143–155
1. Gao Y.
2. de Bang T.C.
3. Schjoerring J.K.
2019Cisgenic overexpression of cytosolic glutamine synthetase improves nitrogen utilization efficiency in barley and prevents grain protein decline under elevated CO2Plant Biotechnology Journal 17:1209–1221
1. Gaufichon L.
2. Marmagne A.
3. Belcram K.
4. Yoneyama T.
5. Sakakibara Y.
6. Hase T.
7. Grandjean O.
8. Clément G.
9. Citerne S.
10. Boutet-Mercey S.
11. Masclaux-Daubresse C.
12. Chardon F.
13. Soulay F.
14. Xu X.
15. Trassaert M.
16. Shakiebaei M.
17. Najihi A.
18. Suzuki A
2017ASN1-encoded asparagine synthetase in floral organs contributes to nitrogen filling in Arabidopsis seedsThe Plant Journal 91:371–393
1. Gojon A.
2. Cassan O.
3. Bach L.
4. Lejay L.
5. Martin A
2023The decline of plant mineral nutrition under rising CO2: physiological and molecular aspects of a bad dealTrends in Plant Science 28:185–198
1. Horton M.W.
2. Hancock A.M.
3. Huang Y.S.
4. Toomajian C.
5. Atwell S.
6. Auton A.
7. Muliyati N.W.
8. Platt A.
9. Sperone F.G.
10. Vilhjálmsson B.J.
11. Nordborg M.
12. Borevitz J.O.
13. Bergelson J
2012Genome-wide patterns of genetic variation in worldwide Arabidopsis thaliana accessions from the RegMap panelNature Genetics 44:212–216
1. Hu H.
2. Rappel W.-J.
3. Occhipinti R.
4. Ries A.
5. Böhmer M.
6. You L.
7. Xiao C.
8. Engineer C.B.
9. Boron W.F.
10. Schroeder J.I
2015Distinct Cellular Locations of Carbonic Anhydrases Mediate Carbon Dioxide Control of Stomatal MovementsPlant Physiology 169:1168–1178
1. Huard-Chauveau C.
2. Perchepied L.
3. Debieu M.
4. Rivas S.
5. Kroj T.
6. Kars I.
7. Bergelson J.
8. Roux F.
9. Roby D
2013An atypical kinase under balancing selection confers broad-spectrum disease resistance in ArabidopsisPLoS Genet 9
1. Kim S.
2. Plagnol V.
3. Hu T.T.
4. Toomajian C.
5. Clark R.M.
6. Ossowski S.
7. Ecker J.R.
8. Weigel D.
9. Nordborg M
2007Recombination and linkage disequilibrium in Arabidopsis thalianaNature Genetics 39:1151–1155
1. Lam H.-M.
2. Wong P.
3. Chan H.-K.
4. Yam K.-M.
5. Chen L.
6. Chow C.-M.
7. Coruzzi G.M
2003Overexpression of the ASN1 Gene Enhances Nitrogen Status in Seeds of ArabidopsisPlant Physiology 132:926–935
1. Lee S.
2. Ricachenevsky F.K.
3. Punshon T
2021Functional overlap of two major facilitator superfamily transporter, ZIF1, and ZIFL1 in zinc and iron homeostasisBiochemical and biophysical research communications 560:7–13
1. Loladze I
2014Hidden shift of the ionome of plants exposed to elevated CO(2)depletes minerals at the base of human nutritionElife 3
1. Luthi D.
2. Le Floch M.
3. Bereiter B.
4. Blunier T.
5. Barnola J.M.
6. Siegenthaler U.
7. Raynaud D.
8. Jouzel J.
9. Fischer H.
10. Kawamura K.
11. Stocker T.F.
2008High-resolution carbon dioxide concentration record 650,000-800,000 years before presentNature 453:379–382
1. Marcos-Barbero E.L.
2. Pérez P.
3. Martínez-Carrasco R.
4. Arellano J.B.
5. Morcuende R
2021Screening for Higher Grain Yield and Biomass among Sixty Bread Wheat Genotypes Grown under Elevated CO2 and High-Temperature ConditionsPlants 10
1. Medek D.E.
2. Schwartz J.
3. Myers S.S
2017Estimated Effects of Future Atmospheric CO2 Concentrations on Protein Intake and the Risk of Protein Deficiency by Country and RegionEnviron Health Perspect 125
1. Myers S.S.
2. Zanobetti A.
3. Kloog I.
4. Huybers P.
5. Leakey A.D.
6. Bloom A.J.
7. Carlisle E.
8. Dietterich L.H.
9. Fitzgerald G.
10. Hasegawa T.
11. Holbrook N.M.
12. Nelson R.L.
13. Ottman M.J.
14. Raboy V.
15. Sakai H.
16. Sartor K.A.
17. Schwartz J.
18. Seneweera S.
19. Tausz M.
20. Usui Y
2014Increasing CO2 threatens human nutritionNature 510:139–142
1. North K.A.
2. Ehlting B.
3. Koprivova A.
4. Rennenberg H.
5. Kopriva S
2009Natural variation in Arabidopsis adaptation to growth at low nitrogen conditionsPlant Physiology and Biochemistry 47:912–918
1. Pauls S.U.
2. Nowak C.
3. Balint M.
4. Pfenninger M
2013The impact of global climate change on genetic diversity within populations and speciesMol Ecol 22:925–946
1. Pearson P.N.
2. Palmer M.R
2000Atmospheric carbon dioxide concentrations over the past 60 million yearsNature 406:695–699
1. Roux F.
2. Frachon L
2022A Genome-Wide Association study in Arabidopsis thaliana to decipher the adaptive genetics of quantitative disease resistance in a native heterogeneous environmentPLoS One 17
1. Shahzad Z.
2. Rouached H
2022Protecting plant nutrition from the effects of climate changeCurr Biol 32:R725–R727
1. Sharma N.
2. Froehlich J.E.
3. Rillema R.
4. Raba D.A.
5. Chambers T.
6. Kerfeld C.A.
7. Kramer D.M.
8. Walker B.
9. Brandizzi F
2023Arabidopsis stromal carbonic anhydrases exhibit non-overlapping roles in photosynthetic efficiency and developmentPlant J 2023:386–397
1. Sun P.
2. Isner J.C.
3. Coupel-Ledru A.
4. Zhang Q.
5. Pridgeon A.J.
6. He Y.
7. Menguer P.K.
8. Miller A.J.
9. Sanders D.
10. McGrath S.P.
11. Noothong F.
12. Liang Y.K.
13. Hetherington A.M
2022Countering elevated CO2 induced Fe and Zn reduction in Arabidopsis seedsNew Phytol 235:1796–1806
1. Tausz-Posch S.
2. Tausz M.
3. Bourgault M
2020Elevated [CO2] effects on crops: Advances in understanding acclimation, nitrogen dynamics and interactions with drought and other organismsPlant Biol (Stuttg 22:38–51
1. Thompson M.
2. Gamage D.
3. Hirotsu N.
4. Martin A.
5. Seneweera S
2017Effects of Elevated Carbon Dioxide on Photosynthesis and Carbon Partitioning: A Perspective on Root Sugar Sensing and Hormonal CrosstalkFront Physiol 8
1. Umnajkitikorn K.
2. Sade N.
3. Rubio Wilhelmi M.D.M.
4. Gilbert M.E.
5. Blumwald E
2020Silencing of OsCV (chloroplast vesiculation) maintained photorespiration and N assimilation in rice plants grown under elevated CO(2)Plant Cell Environ 43:920–933
1. Wang Y.
2. Kang Y.
3. Yu W.
4. Lyi S.M.
5. Choi H.W.
6. Xiao E.
7. Li L.
8. Klessig D.F.
9. Liu J
2022AtTIP2;2 facilitates resistance to zinc toxicity via promoting zinc immobilization in the root and limiting root-to-shoot zinc translocation in Arabidopsis thalianaEcotoxicology and Environmental Safety 233
1. Yang A.
2. Li Q.
3. Chen L.
4. Zhang W.-H
2020A rice small GTPase, Rab6a, is involved in the regulation of grain yield and iron nutrition in response to CO2 enrichmentJournal of Experimental Botany 71:5680–5688
1. Zhu C.
2. Kobayashi K.
3. Loladze I.
4. Zhu J.
5. Jiang Q.
6. Xu X.
7. Liu G.
8. Seneweera S.
9. Ebi K.L.
10. Drewnowski A.
11. Fukagawa N.K.
12. Ziska L.H
2018Carbon dioxide (CO2) levels this century will alter the protein, micronutrients, and vitamin content of rice grains with potential health consequences for the poorest rice-dependent countriesSci Adv 4

Article and author information

Author information

Océane Cassan
IPSiM, Univ Montpellier, CNRS, INRAE, Institut Agro, 34060, Montpellier, France
ORCID iD: 0000-0002-4595-2457
Léa-Lou Pimparé
IPSiM, Univ Montpellier, CNRS, INRAE, Institut Agro, 34060, Montpellier, France
Timothy Mozzanino
IPSiM, Univ Montpellier, CNRS, INRAE, Institut Agro, 34060, Montpellier, France
ORCID iD: 0009-0004-9617-7536
Cécile Fizames
IPSiM, Univ Montpellier, CNRS, INRAE, Institut Agro, 34060, Montpellier, France
ORCID iD: 0000-0002-0551-8250
Sébastien Devidal
Montpellier European Ecotron, Univ Montpellier, CNRS, Campus Baillarguet, 34980, Montferrier-sur-Lez, France
Fabrice Roux
Laboratoire des Interactions Plantes-Microbes-Environnement, Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, CNRS, Université de Toulouse, Castanet-Tolosan, France
ORCID iD: 0000-0001-8059-5638
Alexandru Milcu
Montpellier European Ecotron, Univ Montpellier, CNRS, Campus Baillarguet, 34980, Montferrier-sur-Lez, France, CEFE, Univ Montpellier, CNRS, EPHE, IRD, 34293, Montpellier, France
ORCID iD: 0000-0002-2889-1234
Sophie Lèbre
IMAG, Univ Montpellier, CNRS, Montpellier, France
ORCID iD: 0000-0003-3444-2416
Alain Gojon
IPSiM, Univ Montpellier, CNRS, INRAE, Institut Agro, 34060, Montpellier, France
ORCID iD: 0000-0001-5412-8606
Antoine Martin
IPSiM, Univ Montpellier, CNRS, INRAE, Institut Agro, 34060, Montpellier, France
ORCID iD: 0000-0002-6956-2904
- Author for correspondence: antoine.martin@cnrs.fr

Version history

Preprint posted: June 7, 2023
Sent for peer review: July 5, 2023
Reviewed Preprint version 1: November 30, 2023
Reviewed Preprint version 2: May 7, 2024
Version of Record published: May 23, 2024
Version of Record updated: May 28, 2024

Copyright

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

Revised: This Reviewed Preprint has been revised by the authors in response to the previous round of peer review; the eLife assessment and the public reviews have been updated where necessary by the editors and peer reviewers.

Reviewing Editor
Magnus Nordborg
Gregor Mendel Institute, Vienna, Austria
Senior Editor
Jürgen Kleine-Vehn
University of Freiburg, Freiburg, Germany

Reviewer #1 (Public Review):

This study offers good evidence pointing to a genetic basis for Arabidopsis thaliana's response to elevated CO2 (eCO2) levels and its subsequent impact on the leaf ionome. The natural variation analyses in the study support the hypothesis that genetic factors, rather than local adaptation, guide the influence of eCO2 on the ionome of rosette leaves in Arabidopsis.

Comments on current version:

I appreciate the revisions and the effort the authors have made.

Most of the abstract now accurately reflects the results and methods. It would be nice to have a few more technical details in the abstract, such as:
* What was the CO2 level?
* Which gene was identified?

I still have a problem with this sentence:

"The elevation of atmospheric CO2 leads to a decline in plant mineral content, which might pose a significant threat to food security in the coming decades."

The authors provide a wide range of published studies that support this statement. I fully agree that this is what the literature suggests. However, I think the literature has asked the wrong question.

In general, these studies addressed the question: Given no time for adaptation, do plants grown under high CO2 have a different mineral composition? The answer is yes.

But a more important question is: Can plants and food crops adapt in time? I believe the strength of this study is that it tests this, and it suggests that the answer is yes. I also think there is a lot of unpublished results and greenhouse breeding success that supports the contention that most plants can adapt to the CO2.

"The artificial elevation of atmospheric CO2 leads to a physiological response and decline in plant mineral content, which might pose a significant threat to food security in the coming decades if plants cannot adapt."

It needs to be made clear throughout the paper when high CO2 levels lead to low mineral composition. These are all artificial manipulations without allowing the plants to adapt to the new environment.

"The elevation of atmospheric CO2 concentration leads to a decline in the mineral composition of C3 plants (Gojon et al., 2023)." - this is well supported in artificial environments.

Do wild plants have fewer minerals in their leaves today compared to plants in 1950? This would be great evidence and framing for this experiment.

Crop plants having lower nitrogen and different mineral compositions over time is substantially a product of breeders initially increasing inputs and then, over the last decade, selecting for higher input efficiency.

At the end of the introduction or the beginning of the results, please define why the CO2 level was chosen and its context as being at the high end of current predictions.

"According to the literature, this results in a 20-25% reduction in vitamin C or lycopene and requires a significantly higher nitrogen and water intake to reach expected sugar levels (Doddrell H (2023), Horticulture Research). In addition, the negative effect of elevated CO2 on tomato nutrient content seems to have significant repercussions on nutrition-health properties (Boufeldja (2023), Molecules)."

Thank you for sharing these reviews. These suggest to me that breeders favored the 80% yield bump over other traits. Either there was no breeding, or the breeding focused on other traits. It is important to mention that breeders should include mineral nutrition in their selection index while they maximize yield. Simpler breeding strategies can sometimes heavily favor one trait over others, but cattle breeders today regularly use selection indices that incorporate weights for two dozen traits.

This study provides nice evidence that an annual weed species is likely to be able to adapt easily to high eCO2. Whether perennial species will be able to adapt in time is clearly a topic that needs to be investigated.

https://doi.org/10.7554/eLife.90170.2.sa1

Reviewer #2 (Public Review):

The research uses a large collection of Arabidopsis thaliana accessions from various geographic scales to investigate the natural genetic variation underlying the response of ionome (elemental) composition to elevated CO2 (eCO2), a concern for future food security. While most accessions show a decrease in elemental accumulation, the authors demonstrate a wide variety of responses to eCO2 across the diversity of Arabidopsis, including lines that increase elemental content in eCO2. The demonstration of genetic diversity in eCO2 response is a significant contribution to our understanding of this important phenomenon.

Comments on revised version:

The authors made significant improvements in the manuscript from the original preprint, and the conclusions are now well supported by the evidence presented.

https://doi.org/10.7554/eLife.90170.2.sa0

Author response:

The following is the authors’ response to the original reviews.

eLife assessment

This paper provides useful information about how the ionome of Arabidopsis thaliana adapts to very high CO2-levels, backed up by solid evidence and carefully designed studies. However, the broader claims of the paper about climate change and food security - heavily emphasized in the abstract, introduction, and discussion - are inappropriate, as there is no direct link to the presented work.

We sincerely thank you for the work you have done in reviewing our manuscript. We very much appreciate your overall positive assessment of the experimental work as a whole, its value and robustness.

In this revised version, we took on board the majority of your suggestions and your comments. In particular, we understood your critical point about overstating our objectives, which might in turn seem uncorrelated with our results. We fully agree with the comments that have been made on this point. Consequently, we have made substantial modifications and corrections in order to clarify our objectives and their implications: exploring in depth the natural variation of the shoot ionome response to elevated CO2, and generating a valuable resource allowing a better understanding of the genetic and molecular mechanisms involved in the regulation of plant mineral nutrition by the elevation of atmospheric CO2.

We also made modifications in response to the other suggestions, including a clarification of the functional experiments carried out around the function of TIP2;2 in response to elevated CO2. Figure 7 now comprises the comparison between both ambient and elevated CO2 conditions, which is much more informative that what appeared in the previous version.

Public Reviews:

Reviewer #1 (Public Review):

Summary:

The study's abstract, introduction, and conclusions are not supported by the methods and results conducted. In fact, the results presented suggest that Arabidopsis could easily adapt to an extremely high CO2 environment.

We understand the reviewer’s comment. Although our work is considered useful, robust and well designed, we agree with the reviewer's point. We have certainly overemphasized the significance of our work to address the issue of food security in response to rising atmospheric CO2, at the expense of the factual description of the results of our fundamental study of the mechanisms at the interface between CO2 and mineral nutrition. We have clarified this focus by modifying the text of the introduction, objectives and discussion. We hope that these modifications will enable readers to better appreciate the core of this work.

Regarding the last part of the comment, our results do suggest that genetic variation could allow adaptation to rising atmospheric CO2, and our study does indeed aim to identify the extent and basis of this genetic variation.

This study offers good evidence pointing to a genetic basis for Arabidopsis thaliana's response to elevated CO2 (eCO2) levels and its subsequent impact on the leaf ionome. The natural variation analyses in the study support the hypothesis that genetic factors, rather than local adaptation, guide the influence of eCO2 on the ionome of rosette leaves in Arabidopsis. However, the manuscript's claim regarding its role in "the development of biofortified crops adapted to a high-CO2 world" (line 23) is overstated, especially given the absence of any analysis on the influence of eCO2 on the seed ionome and Arabidopsis is a poor model for harvest index for any crop. The manuscript, in its current form, necessitates massive revisions, particularly in clarifying its broader implications and in providing more substantial evidence for some of its assertions.

We thank the reviewer for this comment, and we would like to thank the reviewer for the positive appreciation for the identification of genetic basis for Arabidopsis thaliana's response to elevated CO2 and its subsequent impact on the leaf ionome. Nevertheless, it is true that the study of the leaf ionome is far from being able to lead to the development of biofortified plants. Some papers described that nutrient harvest index in Arabidopsis is a potential indicator of nutrient use efficiency (for instance, Masclaux-Daubresse and Chardon, Journal of Experimental Botany 2011 or Aranjuelo et al., Journal of Experimental Botany 2013). However, as we did not include any seed ionome data in the paper, we added clear mentions that our analyses were made on leaves (lines 56/57/250/319) and a comment in the discussion section to address this limitation (lines 325-328).

Major Drawbacks and Questions:

(1) Evidence for the Central Premise:

The foundational premise of the study is the assertion that rising atmospheric CO2 levels result in a decline in plant mineral content. This phenomenon is primarily observed in C3 plants, with C4 plants seemingly less affected. The evidence provided on this topic is scant and, in some instances, contradicts the authors' own references. The potential reduction of certain minerals, especially in grains, can be debated. For instance, reduced nitrogen (N) and phosphorus (P) content in grains might not necessarily be detrimental for human and animal consumption. In fact, it could potentially mitigate issues like nitrogen emissions and phosphorus leaching. Labeling this as a "major threat to food security" (line 30) is exaggerated. While the case for microelements might be more compelling, the introduction fails to articulate this adequately. Furthermore, the introduction lacks any discussion on how eCO2 might influence nutrient allocation to grains, which would be crucial in substantiating the claim that eCO2 poses a threat to food security. A more comprehensive introduction that clearly delineates the adverse effects of eCO2 and its implications for food security would greatly enhance the manuscript.

We partially agree with this comment. The decline in mineral status of C3 plants under conditions of elevated atmospheric CO2 has been widely described in the literature, and specifically documented for the cereal grains. While there are variations in this effect (depending on species, ecotype, cultivar), there is no debate about its acceptance. Here are just a few of the many works describing this effect, both on a global scale and at the level of the individual plant (Cotrufo MF (1998) Elevated CO2 reduces the nitrogen concentration of plant tissues. Global Change Biology 4: 43-54; Loladze I (2014) Hidden shift of the ionome of plants exposed to elevated CO(2)depletes minerals at the base of human nutrition. eLife 3: e02245; Myers SS (2014) Increasing CO2 threatens human nutrition. Nature 510: 139-142; Poorter H (1997) The effect of elevated CO2 on the chemical composition and construction costs of leaves of 27 C3 species. Plant, Cell & Environment 20: 472-482 ; Soares JC (2019) Preserving the nutritional quality of crop plants under a changing climate: importance and strategies. Plant and Soil 443: 1-26; Stitt] M (1999) The interaction between elevated carbon dioxide and nitrogen nutrition: the physiological and molecular background. Plant, Cell & Environment 22: 583-621; Uddling J (2018) Crop quality under rising atmospheric CO2. Curr Opin Plant Biol 45: 262-267).

In addition to this, the threat to food security posed by this alteration in plant mineral status has also been well described in the literature by several modeling approaches (Beach RH (2019) Combining the effects of increased atmospheric carbon dioxide on protein, iron, and zinc availability and projected climate change on global diets: a modelling study. Lancet Planet Health 3: e307-e317; Ebi KL (2019) Elevated atmospheric CO(2) concentrations and climate change will affect our food's quality and quantity. Lancet Planet Health 3: e283-e284; Medek DE (2017) Estimated Effects of Future Atmospheric CO2 Concentrations on Protein Intake and the Risk of Protein Deficiency by Country and Region. Environ Health Perspect 125: 087002; Smith MR (2018) Impact of anthropogenic CO2 emissions on global human nutrition. Nature Climate Change 8: 834-839; Weyant C (2018) Anticipated burden and mitigation of carbon-dioxide-induced nutritional deficiencies and related diseases: A simulation modeling study. PLoS Med 15: e1002586; Zhu C (2018) Carbon dioxide (CO2) levels this century will alter the protein, micronutrients, and vitamin content of rice grains with potential health consequences for the poorest rice-dependent countries. Sci Adv 4: eaaq1012). To reinforce this point, we have added a sentence and references (lines 30-33). Nevertheless, we understand the reviewer's comment on the nuance to be given to the intensity of this potential threat. We have therefore modified the text, replacing "major threat" by "significant threat" (lines 3 and 29).

We also would like to answer the reviewer’s comment on the potential environmental benefit associated with reduced N and P content in grains (mitigation of N emissions and P leaching). Indeed, if this reduced N and P content results from a lowered use efficiency of soil nutrients by plants, as suggested by several studies (Bloom 2010, Cassan 2023, Gojon 2023 and references therein), this may at the opposite favor N oxides emission and P leaching from the soil.

(2) Exaggerated Concerns:

The paper begins with the concern that carbon fertilization will lead to carbon dilution in our foods. While we indeed face numerous genuine threats in the coming decades, this particular issue is manageable. The increase in CO2 alone offers many opportunities for boosting yield. However, the heightened heat and increased evapotranspiration will pose massive challenges in many environments.

While there are indeed multiple threats that we are facing in the coming decades, we don't fully agree with this comment. At present, there's no evidence to say that the negative effect of CO2 on plant mineral content will be manageable. Furthermore, there is compelling evidence that altered mineral nutrition and mineral status of plants will be an important factor limiting the high CO2-induced increase in yield, as will be heat or increased evapotranspiration (see for instance Coskun et al (2016) Nutrient constraints on terrestrial carbon fixation: The role of Nitrogen. J. Plant Physiol. 203: 95-109; Jiang M (2020) Low phosphorus supply constrains plant responses to elevated CO2 : A meta-analysis. Glob Chang Biol 26: 5856-5873 ; Reich PB (2006) Nitrogen limitation constrains sustainability of ecosystem response to CO2. Nature 440: 922-925). Thus, although we do not negate the crucial importance of heat and water stress, we believe it is relevant to study the basic mechanisms responsible for the negative effect of CO2 on plant mineral composition.

Figure 4 in fact suggests that 43% of the REGMAP panel (cluster 3) is already pre-adapted to very high CO2 levels. This suggests annual species could adapt very rapidly.

We agree with the reviewer. However, this suggests that genetic variation exists in some ecotypes to support adaptation to elevated CO2. The purpose of this work is indeed to identify this genetic variation, in order to characterize the mechanisms behind.

(3) Assumptions on CO2 Levels:

The assumption of 900ppm seems to be based on a very extreme climate change scenario. Most people believe we will overshoot the 1.5°C scenario, however, it seems plausible that 2.5 to 3°C scenarios are more likely. This would correspond to around 500ppm of CO2. https://www.nature.com/articles/s41597-022-01196-7/tables/4

We agree with the reviewer that the CO2 concentration we used corresponds to a high value in the IPCC projections. That said, this value is currently considered very plausible: the following figure (from Smith and Myers (2018) Nature Climate Change) shows that current CO2 emissions align with the IPCC's most extreme model (RCP 8.5), which would result in a CO2 concentration of around 900 ppm in 2100. Furthermore, nothing allows to exclude the 4°C scenario in the 6th IPCC report.

Author response image 1.

(4) Focus on Real Challenges:

We have numerous real challenges, such as extreme heat and inconsistent rainfall, to address in the context of climate change. However, testing under extreme CO2 conditions and then asserting that carbon dilution will negatively impact nutrition is exaggerated.

While we fully agree that several threats linked to climate change exist, and all deserve to be studied, we find it questionable to consider that the potential effect of high CO2 on the mineral nutrition of plants is not a real challenge. The mineral nutrition of plants is already a current major environmental challenge. This perspective seems to reflect the reviewer's personal opinion rather than an analysis of our work.

In contrast, the FACE experiments are fundamental and are conducted at more realistic eCO2 levels. Understanding the interaction between a 20% increase in CO2 and new precipitation patterns is key for global carbon flux prediction.

Again, we do not fully understand this comment, as the aim of our study was not to perform a global carbon flux prediction, but to unravel genes and mechanisms underlying the negative effect of elevated CO2 on the nutrient content of Arabidopsis rosettes. However, we agree with the reviewer’s comment and with the fact that FACE are useful facilities to explore the CO2 response in more natural environments, and we highlight the fact that the decrease in mineral status of C3 plants has been widely documented in FACE studies. FACE experiments do not facilitate, however, to conduct fully controlled experiments (temperature, rainfall, wind and light intensities are not controllable in FACE), that allow to disentangle the mechanisms by which elevated CO2 regulates the signaling pathways associated with the plant mineral composition. In the longer term, studying the mechanisms we have identified in a more global context of climate change could be highly relevant.

As I look at the literature on commercial greenhouse tomato production, 1000ppm of eCO2 is common, but it also looks like the breeders and growers have already solved for flavor and nutrition under these conditions.

Indeed, tomato is often cultivated in CO2-enriched greenhouses at 1000 ppm. According to the literature, this results in a 20-25% reduction in vitamin C or lycopene, and requires a significantly higher nitrogen and water intake to reach expected sugar levels (Doddrell H (2023) Horticulture Research). In addition, the negative effect of elevated CO2 on tomato nutrient content seems to have significant repercussions on nutrition-health properties (Boufeldja (2023), Molecules).

Conclusion:

While the study provides valuable insights into the genetic underpinnings of Arabidopsis thaliana's response to elevated CO2 levels, it requires an entirely revised writeup, especially in its abstract, broader claims and implications. The manuscript would benefit from a more thorough introduction, a clearer definition of its scope, and a clear focus on the limits of this study.

We thank the reviewer for the comments made on our manuscript. In addition to the responses that we provide to these comments, we have modified the main text of the introduction, objectives and discussion to take these comments into consideration. We believe that this will significantly improve the manuscript.

Reviewer #2 (Public Review):

Strengths:

The authors have conducted a large, well-designed experiment to test the response to eCO2. Overall, the experimental design is sound and appropriate for the questions about how a change in CO2 affects the ionome of Arabidopsis. Most of the conclusions in this area are well supported by the data that the authors present.

We thank the reviewer for this positive appreciation.

Weakness:

While the authors have done good experiments, it is a big stretch from Arabidopsis grown in an arbitrary concentration of CO2 to relevance to human and animal nutrition in future climates. Arabidopsis is a great model plant, but its leaves are not generally eaten by humans or animals.

We agree with the reviewer’s comment. We recognized that implying a direct contribution of our work to human nutrition in the future climates is overstated, as mentioned by the reviewer 1 as well. This was not an intentional overstatement, as we have always been convinced that our work contributed to the understanding of the basic mechanisms involved in the negative regulation of plant mineral nutrition by high CO2. We have significantly modified the text to correct any misunderstanding of our work’s implication.

The authors don't justify their choice of a CO2 concentration. Given the importance of the parameter for the experiment, the rationale for selecting 900 ppm as elevated CO2 compared to any other concentration should be addressed. And CO2 is just one of the variables that plants will have to contend with in future climates, other variables will also affect elemental concentrations.

We agree with this comment. We added a justification of the high CO2 concentration used in this work in the Material and Methods section (lines 343-344). You can also read the explanation of this choice in the response to the reviewer 1’s point 3.

Given these concerns, I think the emphasis on biofortification for future climates is unwarranted for this study.

Anew, we agree with this comment and we have significantly modified the text to correct any misunderstanding of our work’s implication.

Additionally, I have trouble with these conclusions:

-Abstract "Finally, we demonstrate that manipulating the function of one of these genes can mitigate the negative effect of elevated CO2 on the plant mineral composition."

-Discussion "Consistent with these results, we show that manipulating TIP2;2 expressions with a knock-out mutant can modulate the Zn loss observed under high CO2."

The authors have not included the data to support this conclusion as stated. They have shown that this mutant increases the Zn content of the leaves when compared to WT but have not demonstrated that this response is different than in ambient CO2. This is an important distinction: one way to ameliorate the reduction of nutrients due to eCO2 is to try to identify genes that are involved in the mechanism of eCO2-induced reduction. Another way is to increase the concentration of nutrients so that the eCO2-induced reduction is not as important (i.e. a 10% reduction in Zn due to eCO2 is not as important if you have increased the baseline Zn concentration by 20%). The authors identified tip2 as a target from the GWAS on difference, but their validation experiment only looks at eCO2.

We thank the reviewer for this comment, and we agree with it. It is much more interesting, especially in the context of this paper, to analyze the function of a candidate gene not only in elevated CO2, but in both ambient and elevated CO2. Therefore, we added in Figure 7 data for the expression of TIP2;2 in contrasted haplotypes under ambient CO2, in comparison to those already presented under elevated CO2 (now Fig. 7C and 7D). This showed that TIP2;2 expression is lower in haplotype 0 also under ambient CO2. We also added in Figure 7 (Fig. 7E) the Zn level in WT and tip2;2-1 mutant under ambient CO2, in comparison to those already presented under elevated CO2. This showed that that the tip2;2-1 mutant line did not present any decrease in Zn shoot content in response to elevated CO2, in opposition to what is observed for the WT.

We have added comments associated to these new results in the Results and Discussion sections and in the discussion section (lines 233-242 in the results section, and lines 310-314 in the discussion section).

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

Reviewer Comments on the Article's Approach to Ionome Analysis

(1) Omission of Phosphorus from the Ionome:

It's surprising that phosphorus (P) was not measured in the ionome. After nitrogen (N), P is often the most limiting mineral for plant development and yield, making it a significant component of the ionome. Why did the authors omit this crucial element?

We agree with the reviewer that P is an important mineral for plant growth. The absence of data related to P content is due to feasibility constraints rather than oversight. The MP-AES instrument we used to analyze the ionome (except N and C, that we obtained from an Elementar Analyzer) would have required an extra-step and an extra-analysis to obtain data for macronutrient such as P or K. In the context of this large-scale experiment, we faced the necessity to compromise and proceed without these data.

(2) Relationship Between Leaf Ionome and Seed:

The manuscript lacks evidence demonstrating the relationship between the leaf ionome and the seed. This connection is vital to establish the study's aims as outlined in lines 20-24. If the central argument is that eCO2 threatens food security, it's essential for the authors to either:

Provide evidence that eCO2 induces changes in the ionome profiles of seeds.

Show that changes in the rosette leaf ionome lead to alterations in seed ionome profiles.

We agree with the reviewer. Although we know that seed ionome composition of Arabidopsis model accession such as Columbia is indeed negatively affected by eCO2, we do not provide the data that support some of the terms used in lines 20-24. The correspondence between leaf and seed ionome in natural population under eCO2 is certainly a next question that we will address. Therefore, to align our stated objectives with our data, we have modified the sentence in lines 20-24. We also added a comment on this point lines on the discussion section (lines 324-328).

(3) Analysis of Ionome in Rosette Leaves:

Why did the authors choose to analyze the ionome specifically in rosette leaves? Is there a known correlation between the ionome profile in rosette leaves and seeds?

See our answer to the above comment.

(4) Experimental Design Comments:

The layout of the accession growouts, the methods of randomization, blocking, and controls/checks should be detailed.

Were BLUEs (Best Linear Unbiased Estimators) or BLUPs (Best Linear Unbiased Predictors) employed to account for experimental design conditions? If not, it's recommended that they be used.

We thank the reviewer for this comment. A note on replicates has been added in the Method/Plant Material section. Concerning the BLUEs/BLUPs, although I am not familiar with their use, I do not think that these approaches are relevant in our experimental design. Indeed, we pooled 3 to 5 replicates for each accession to measure the ionome (as mentioned in the Method/Ionome analysis section – we realized this was perhaps not clear enough, and thus we reinforced this point in this section). Therefore, we do not have the variance data required to perform BLUEs/BLUPs.

(5) Carbon Dilution Effect:

The statement, "The first component of the PCA described a clear antagonistic trend between C content and the change of other mineral elements (Fig. 3B)..." suggests a well-understood carbon dilution effect. These results are anticipated and align with existing knowledge.

We thank the reviewer for this comment. However, this sentence does not relate to the biomass dilution hypothesis referred to by the reviewer. Indeed, the composition of each mineral (C and others) is expressed as a percentage of biomass, not as an absolute value. Therefore, this reflects more a probable effect of the increase in carbon compounds (notably soluble sugars), which could influence mineral composition.

(6) Heritability Estimates:

The authors should report both the broad-sense heritability and an estimate of heritability based on a GRM or Kinship matrix.

We thank the reviewer for this suggestion. We are skeptical of using a kinship matrix to estimate heritability in our study. Estimating narrow-sense heritability using a kinship matrix is conceptually based on the infinitesimal model of Fisher, thereby meaning that phenotypic variation is driven by hundreds to thousands of QTLs with small effects. If this is the case, GWAS conducted on several hundred (or even thousands) of genotypes will not be powerful enough to detect such QTLs. Accordingly, estimates of broad-sense heritability based on estimates of variance components can drastically differ from estimates of narrow-sense heritability based on the use of a kinship matrix, as illustrated in the study of Bergelson et al. (2019 Scientific Reports).

(7) Application of the Breeder's Equation:

It would be beneficial if the authors applied the breeder's equation to estimate the species' potential rate of response. Based on the allele frequency of the adapted cluster 3 (69 ecotypes or 43% frequency of Figure 3B), it seems plausible that the populations could adapt within 23 generations.

We thank the reviewer for this suggestion. Indeed, it would be really interesting to test whether sub-populations could adapt in comparison with others, and over what period of time. It is nevertheless not possible to do so using the Breeder’s equation in our case, as this requires fitness data under conditions of ambient or elevated CO2 (i.e. production of seeds) to be applied, and we do not have these data at the level of the whole population.

(8) Overall Quality:

In general, the authors have executed a high-quality ionome mapping experiment. However, the abstract, introduction, and discussion should be entirely rewritten and reframed.

We thank the reviewer for the positive evaluation of our experiment. As previously mentioned, we are for the most part in agreement with the comments made about the need to align our stated objectives with our experimental data and conclusions. To do so, we have rewritten part of the abstract, introduction and discussion. The details of these modifications are described in the responses made to each comment.

Here's a line-by-line list of suggestions on writing:

Line 30 would read better with a comma after thus (or by replacing thus with therefore and then a comma at the start of the sentence).

Line 33 nevertheless would read better in between commas.

Lines 45 - 48 sentence is too long, could probably divide it into two.

Lines 90 - 94 are hard to interpret, recommend rephrasing for clarity.

Line 130 - keep verbs in the past tense for consistency (ran instead of run).

Line 194 - what do the authors mean by crossed? I'm inferring they looked at the intersection of DEGs with the list of genes identified by GWA mapping, probably should use a more concise word.

There's a concurrent use of the adjective strong (Lines 80, 142, 144, 197, 245). I would advise using a more concise adjective or avoiding its use to let the reader form their own opinion on the data.

Lines 174-176 the cited reference (No. 15) is incorrect. The study by Katz et al. (2022) does not provide information on the role of ZIF1 in zinc sequestration mechanisms under elevated CO2 conditions.

We thank the reviewer for these detailed recommendations. We have corrected or rephrased the text according to these suggestions.

Reviewer #2 (Recommendations For The Authors):

Technical points:

900 ppm as elevated CO2: Given the importance of the parameter for the experiment, the rationale for selection 900 ppm as elevated CO2 compared to any other concentration should be addressed.

We acknowledge the reviewer's point and have previously addressed related aspects earlier in our response. In line with this, we have included a justification for this particular parameter in the Method section.

The authors do not mention what genotype was used for their root/shoot RNAseq experiment.

We thank the reviewer for this comment, and indeed, this information was not mentioned. This is now done, in the Method section.

Line 125: Spelling error "REGMPA".

This has been corrected.

Line 338: Removal of outlier observations - "Prior to GWAS and multivariate analyses such as PCA or clustering, mineral composition measures were pre-processed to remove technical outliers". The authors should mention the exact number of outliers that were removed and what the explicit criteria were for removal.

The number of outliers removed from each dataset is now indicated in Supplemental Table 7 (this is cited in the Method section). The explicit criteria used for this analysis is actually mentioned in the corresponding Method section: “the values positioned more than 5 median absolute deviations away from the median were removed from the dataset”.

Line 379: "Lowly expressed genes with an average value across conditions under 25 reads were excluded from the analysis". Providing information about the number of the lowly expressed genes that were removed from the analysis can help with the interpretation of the likelihood of the candidates selected being correct.

This is a standard procedure in RNAseq analysis. It avoids many false positives in the differential analysis of gene expression based on ratios (where a very small number in the denominator can lead to a very high variation in expression, of no real significance). For information, this step led to the removal of 11607 and 10121 genes for the shoot and root datasets.

Line 384: It's not clear how many biological replicates were used.

This has been corrected.

Additional comment: We have also become aware of a confusion concerning one of the candidate genes located close to GWA peaks: line 180 of the first version, we mentioned CAX1 (AT1G16380) for its role on nutrient deficiency response. There are actually two genes annotated as CAX1 in TAIR (both are cation exchangers), but the one involved in nutrient deficiency response is AT2G38170. We therefore removed the sentence mentioning AT1G16380/CAX1 as a potential candidate gene.

https://doi.org/10.7554/eLife.90170.2.sa3

Significance of findings

Strength of evidence

Abstract

Introduction

Results

Elevated CO2 negatively impacts the ionome content at the population-scale level in Arabidopsis thaliana.

Elevated CO2 globally decreases ionome content at the population level, whatever the geographic scale

The ionome of Arabidopsis thaliana natural accessions displays a high range of phenotypic diversity in response to elevated CO2

Elevated CO2 leads to high phenotypic diversity of ionome response in Arabidopsis thaliana.

Elevated CO2 results in a general pattern of ionome variation common to most accessions constituting natural populations of Arabidopsis thaliana.

Variation in the response of the ionome to elevated CO2 identifies contrasting subpopulations inside the REGMAP panel.

Genetic architecture of the ionome response to elevated CO2, and identification of genetic determinants

Genetic architecture of the response of the ionome to elevated CO2 in the REGMAP panel of Arabidopsis thaliana.

Identification of genes detected by GWA mapping and differentially regulated by elevated CO2.

Natural variation of the TIP2;2 gene is associated with improved responses of Zn content to elevated CO2.

Discussion

The natural variation of ionome response to elevated CO2 in Arabidopsis thaliana displays a high degree of genetic variation

GWA mapping of ionome variation under elevated CO2 identified a large number of genes to understand and mitigate the negative effect of high CO2 on plant mineral composition

Methods

Data and code availability

Plant Material

Ionome analysis

Removal of outlier observations

PCA and Clustering

GWAs

RNA-seq experiments

Quantitative real-time PCR

Acknowledgements

References

Article and author information

Author information

Océane Cassan

Léa-Lou Pimparé

Timothy Mozzanino

Cécile Fizames

Sébastien Devidal

Fabrice Roux

Alexandru Milcu

Sophie Lèbre

Alain Gojon

Antoine Martin

Version history

Copyright

Peer review process

Editors

Elevated CO₂ negatively impacts the ionome content at the population-scale level in Arabidopsis thaliana.

Elevated CO₂ globally decreases ionome content at the population level, whatever the geographic scale

The ionome of Arabidopsis thaliana natural accessions displays a high range of phenotypic diversity in response to elevated CO₂

Elevated CO₂ leads to high phenotypic diversity of ionome response in Arabidopsis thaliana.

Elevated CO₂ results in a general pattern of ionome variation common to most accessions constituting natural populations of Arabidopsis thaliana.

Variation in the response of the ionome to elevated CO₂ identifies contrasting subpopulations inside the REGMAP panel.

Genetic architecture of the ionome response to elevated CO₂, and identification of genetic determinants

Genetic architecture of the response of the ionome to elevated CO₂ in the REGMAP panel of Arabidopsis thaliana.

Identification of genes detected by GWA mapping and differentially regulated by elevated CO₂.

Natural variation of the TIP2;2 gene is associated with improved responses of Zn content to elevated CO₂.

The natural variation of ionome response to elevated CO₂ in Arabidopsis thaliana displays a high degree of genetic variation

GWA mapping of ionome variation under elevated CO₂ identified a large number of genes to understand and mitigate the negative effect of high CO₂ on plant mineral composition