Understanding plant microbiomes requires a genotype × environment framework
2021-10-01

Plant microbiomes have become one of the hottest topics in plant biology. Driven by the increased availability of microbiome sequencing methods, analyses of plant-associated microbiomes have been skyrocketing during the last decade. They have generally taken one of two main perspectives: (1) a focus on the microbiome itself, where researchers describe microbiome diversity and attempt to understand its drivers (Figure 1A), or (2) a focus on the consequences of microbiomes, where researchers analyze effects of microbiomes on plants (Figure 1B). Below, we briefly discuss these two perspectives, and we argue that for both a genotype-by-environment (G × E) framework will be key for achieving a deeper and more general understanding of plant microbiomes. Studies with a microbiome focus typically describe the diversity and composition of the root or leaf microbiomes of plants, and they often test influences of plant characteristics or environmental conditions on the microbiomes (Figure 1A). For instance, previous studies have shown that microbiome composition varies within and among plant species, with significant influences of plant genotype (Agler et al., 2016; Wagner et al., 2016; Bowen et al., 2017; Bergelson et al., 2019) and phylogeny (Fitzpatrick et al., 2018) and that not only plant tissue but also plant age and developmental stage (Chaparro et al., 2014; Wagner et al., 2016) influence plant microbiomes. In addition to plant characteristics, environmental conditions also play a role in microbiome development. For instance, soil conditions and root exudates strongly influence root microbiomes (Fitzpatrick et al., 2018; Hu et al., 2018; Sasse et al., 2018), and leaf microbiomes vary predictably among different habitats (Agler et al., 2016; Wagner et al., 2016). Microbiome studies with a plant focus, in contrast, are interested in how the microbiome of a plant affects its growth or environmental tolerances. They test—through experiments or association patterns—how plant performance is influenced by the presence or composition of microbiota, sometimes also taking plant or environmental characteristics into account (Figure 1B). Studies with individual microbial taxa have demonstrated that these can promote growth and stress tolerance of plants (Lugtenberg and Kamilova, 2009) and influence pathogen and herbivore resistance (Pieterse et al., 2014; Hu et al., 2018). More recent studies with complex microbiomes have confirmed these effects: inoculation with diverse microbiota altered plant growth and physiology (Fitzpatrick et al., 2019; Belimov et al., 2020), phenology (Panke-Buisse et al., 2015), and pathogen resistance (Berendsen et al., 2018; Berg and Koskella, 2018), sometimes in a genotype- or environment-dependent fashion (Berg and Koskella, 2018; Belimov et al., 2020). In summary, recent research has demonstrated the ubiquity and importance of plant microbiomes, but this work has also shown that microbiomes are complex and influenced by a range of plant and environmental factors. Another challenge is that drivers of microbiome variation often interact. For instance, in a multi-site field experiment with different genotypes of Boechera stricta, Wagner et al. (2016) found that genotype and age effects on bacterial microbiomes were often site-specific. In an experiment with natural accessions of Arabidopsis thaliana, Fitzpatrick et al. (2019) found that the effects of a natural soil microbiome on plant fitness depended not only on the plant genotype but also on the ecological context. Similarly, Petipas et al. (2020) showed that the effects of soil microbes on the growth and fitness of Hypericum perforatum were habitat- and plant-genotype-specific. In spite of the many and often interacting drivers of microbiome diversity and microbiome effects, the vast majority of previous studies focused on one or few drivers, often in reductionist laboratory settings, and there have been few solid multifactorial studies to date that allowed testing for interactions between different factors. As a result, the generality of many previous results, and their transferability to more natural environmental conditions, remains uncertain, and we are still far from truly understanding natural plant microbiomes. A significant step forward could be to embrace an important conceptual framework from evolutionary ecology: that of genotype-by-environment interactions. Genotype-by-environment (G × E) interactions are statistical interactions between the effects of genotypes and environment on phenotypes, that is, when phenotypic differences among genotypes depend on the environment in which they are tested, or when phenotypic responses to environment depend on the genotype. The G × E concept has long been central to plant evolutionary ecology (Nicotra et al., 2010), and a large body of research has often found strong G × E interactions in many plant species, to the extent that genotype effects may be strong in some but absent in other environments, and phenotypic responses to environment are sometimes opposite for different genotypes. Similar results in animal research confirmed that G × E interactions are the rule in natural populations and that caution is needed with generalizing from single-factor studies. G × E experimental designs are essential for understanding and documenting local adaptation, and they are also relevant for adjusting agricultural and forestry practices to changing environments (Nicotra et al., 2010). The classic experimental approach to testing G × E interactions is a common garden experiment where multiple genotypes are replicated across different environments in a multifactorial design, so that the generality of genotype and environment effects, as well as their interactions, can be statistically tested. The results of such experiments are often visualized through reaction norm plots that show genotype-specific responses to environment or other relevant interactions (Figure 1C, D). We can easily apply these concepts and experimental approaches to a multifactorial study of plant microbiomes, both for the microbiome and the plant perspective. Microbiome-focused studies with a G × E character essentially treat the microbiome as an "extended phenotype" of the plant that is subject to the same complex influences as other plant phenotypes. Such studies will, for example, test the influence of plant genotype on plant microbiomes under different environmental conditions, or they will examine environmental effects on plant microbiomes across multiple plant genotypes (Figure 1C). For instance, field experiments can transplant multiple plant genotypes into different habitats and test the interactive effects of genotype and habitat on spontaneous microbiome development (Wagner et al., 2016). In laboratory experiments, different plant genotypes can be inoculated with identical microbial communities and their divergence followed under different growth conditions. An extension of the G × E concept may also include plant factors other than genotype (e.g., plant tissue, age, or even species). More complex studies may include several environmental factors and/or additional microbial drivers of microbiome composition (Figure 1A). Plant-focused studies with a G × E framework generally test microbiome effects on plant performance or stress tolerance not only for one narrow type of experimental set-up but across a range of different environments and/or multiple plant genotypes (Figure 1B). For instance, beneficial or pathogenic effects of different microbial inoculates can be studied under several, controlled levels of resource availability or abiotic stress (Fitzpatrick et al., 2019). For more realistic tests, seedlings can be inoculated with different microbial communities and planted in a range of natural habitats (Petipas et al., 2020). Depending on one's perspective and strategy of data analysis, these approaches will examine how microbiome effects on plants are modulated by environmental influences or, equally important, how plant responses to the environment (phenotypic plasticity; environmental tolerances) are modulated by microbes (Figure 1D). Finally, the environmental component in such experiments may also include additional biotic factors such as competitors (Fitzpatrick et al., 2019), herbivores, or other (background) microbiota, which will allow for testing microbe–microbe interactions or other complex biotic interactions. The study of plant microbiomes is an important frontier in current plant biology, with many open questions, particularly from an ecological-evolutionary (Koskella et al., 2017; Fitzpatrick et al., 2020) and agricultural perspective (Toju et al., 2018). Irrespective of whether the focus is on the plant or the microbiome, studies that are too simple may overlook important interactions between different factors, and they run the risk of overestimating or overgeneralizing results. A more thorough understanding of plant microbiomes will require working with a broader range of plant genotypes and nonmodel species, and to take a G × E perspective and explicitly test the generality of plant–microbiome interactions across multiple interacting drivers. Such studies will not only be relevant for researchers with an ecological-evolutionary mindset, but they will ultimately also allow those with a more reductionist focus on functional and molecular details to better understand the robustness of their insights and refine their models of plant–microbe interactions. We thank Pam Diggle and two anonymous reviewers for helpful comments on previous versions of this manuscript. Our work was supported by the Deutsche Forschungsgemeinschaft (DFG; projects BO 3241/10-1 and BO 3241/11-1 to O.B.) as part of the priority programme 2125 Deconstruction and Reconstruction of the Plant Microbiota "DECRyPT", and by the German Federal Ministry of Education and Research (BMBF; MOPGA project 306055 to C.L.R.). Open Access funding enabled and organized by Projekt DEAL. All authors jointly developed the ideas in this essay and contributed to writing the manuscript.