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. 2026 Apr 6;19(4):e70351. doi: 10.1111/1751-7915.70351

Can We Breed Microbiomes to Sustain Plant Productivity?

Noémie De Zutter 1,✉, Kris Audenaert 1
PMCID: PMC13052011  PMID: 41940567

ABSTRACT

Global food systems face challenges from population growth, shifting diets and climate change. While decades of plant‐centric breeding and high‐input agriculture have generated high yielding crops, this strategy has unintentionally reshaped the plant associated microbiomes, often coinciding with a depletion of their functional diversity. We revisit these breeding strategies and propose extending breeding targets beyond the plant genome to include the plant microbiome. In this regard, resistance breeding shows, albeit unintended, that plant genetics shape the microbiome: by narrowing the genetic base, we have selected for highly specialised pathogenic microbiomes. This raises a key question: can we intentionally apply the same principle to select for beneficial microbiomes? To answer this question, a thorough insight into microbial community architecture, hubs and functional redundancy is key. We outline two complementary avenues: (i) rewilding to restore ancestral microbial partners and (ii) microbiome breeding guided by QTL/GWAS mapped host loci that gate microbial recruitment, immune filtering and exudate composition. This approach comprises the integration of trait‐based phenotyping, multi‐omics, network‐informed SynCom design and field testing across environments to capture G × E × M (genotype × environment × microbiome) interactions. Treating the microbiome as a selectable, designable and heritable trait can convert small gains into durable long‐lasting crop resilience.

Keywords: G × E × M interactions, microbiome‐centric breeding, plant‐microbiome interactions, QTL‐guided recruitment, rewilding

Plant domestication unintentionally reshaped crop microbiomes. We propose extending breeding beyond plant genomes to include the microbiome, integrating rewilding, QTL‐guided recruitment and ecological network design. Treating the microbiome as a selectable trait may unlock durable crop resilience under climate stress.

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1. Plant Centric Breeding to Feed the Future in a Changing Climate

Global agriculture and food production are under pressure. Increasing population numbers, shifting dietary preferences and expanding agricultural demands will require higher crop productivity in the coming decades (European Commission 2025; Zhao et al. 2025). At the same time, climate change is undermining the basis of food production: drought periods, heatwaves, extreme rainfall and soil degradation are intensifying, while plant pathogens and pests are becoming more adapted to changing climate zones (Bebber et al. 2013; Farah et al. 2025; Raza and Bebber 2022; Rezaei et al. 2023). For decades, conventional plant breeding has managed to raise yields by exploiting genetic plant traits (Figure 1A). This however resulted in a so‐called ‘domestication syndrome’ (Alam and Purugganan 2024) which not only reshaped plant phenotypes but also unintentionally weakened the plant‐microbe partnerships by focusing on improving plant genetic traits for yield and quality (Ramirez‐Villacis et al. 2025). An insight into how domestication and breeding have reshaped plant microbiomes is a critical first step for determining how these microbial communities can be restored.

FIGURE 1.

FIGURE 1

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(A) Traditional plant centric breeding has focused on selecting desirable plant traits in modern crops, while unintentionally relaxing the selection of microbiome interactive traits (MITs), resulting in increased yield but weakened microbial partnerships compared to wild ancestors. (B) The plant‐microbiome performance depends on the microbial community composition, community network architecture and functional diversity. (C) Rewilding approaches aim to reintroduce ancestral microbial partners lost during domestication, restoring plant‐microbiome associations that support health and resilience. (D) Integrated holobiont breeding framework: key steps include identifying MIT quantitative trait loci (QTLs), trait‐based phenotyping to enlighten microbial functions, modelling genotype × environment × microbiome interactions and integrating microbiomes in plant breeding pipelines.

2. The Impact of Domestication and Subsequent Plant Breeding on Plant Microbiomes

Plants as sessile organisms do not operate alone. In a natural ecosystem, they function as integrated holobionts whose performance depends on a diverse assemblage of microbes that supply nutrients, enhance stress tolerance, modulate defences, and contribute to overall resilience (Hacquard 2016; Hassani et al. 2018; Mesny et al. 2023; Ullah et al. 2025; Vandenkoornhuyse et al. 2015). These ecological services have been taken over by plant‐genetics directed evolution, which raises a provocative question: if crop productivity depends not only on plant genomes but also on microbial genomes, should we also be breeding microbiomes and why aren't we breeding for them yet (Gopal and Gupta 2016). Positioning microbiomes as selectable, designable and heritable components opens new paths to sustain plant productivity under climate uncertainty.

To understand why microbiomes have become central in this discussion, it is important to recollect what they represent. Plants establish multi‐kingdom interactions with communities of bacteria, fungi, archaea and protists, called the microbiota, which colonise roots, leaves, fruits and internal tissue of their hosts. Together with their functional genes, metabolites and ecological interactions, these communities constitute the plant microbiome (Berg et al. 2020). The composition of plant‐associated microbiota varies between host species and environments, with specific microbial communities associated with different tissues within the same organism (Rosenberg and Zilber‐Rosenberg 2016). Microorganisms can contribute to plant fitness by assisting in processes like nitrogen fixation, phosphate solubilisation, micro‐nutrient availability, nutrient mobilisation, regulation of hormone signalling and increasing plant immunity to protect the plant against pathogens (Clouse and Wagner 2021; De Zutter et al. 2022; Liu et al. 2025; Trivedi et al. 2020). By establishing associations with microbial endo‐ and exosymbionts, whose genomes exceed the host's in both size and functional depth, plants effectively extend their own genetic potential, illustrating the basis of the holobiont concept, which considers the plant and its microbiome as an integrated evolutionary and ecological unit (Vandenkoornhuyse et al. 2015; Zilber‐Rosenberg and Rosenberg 2008).

To reshape the plant and its microbiome, the fundamentals of plant breeding should be revisited. While domestication has transformed wild species into crops, crop breeding has taken this a step further by refining the genetics of crops to one or a few desired agricultural traits. In plant breeding, desirable genetic traits are selected and combined to develop new, improved crop varieties with beneficial characteristics, such as higher yield, better disease resistance or better adaptations to a changing climate. While selecting for desired traits, other traits are, often unintentionally, relaxed (Singh and van der Knaap 2022; Yue et al. 2023). The balance between targeted selection and untargeted loss of other traits illustrates the distinction between improvement and domestication. Plant domestication has beneficially altered morphological, physiological and phenotypical traits of crops, but the subsequent breeding for desired traits in an agro‐ecological context has also reduced genetic diversity in plants by only selecting the desired alleles (Raaijmakers and Kiers 2022). As a result, plant breeding has not only shaped the plant phenotype, but has also profoundly influenced the plant's microbiome structure and function (Ramirez‐Villacis et al. 2025; Yue et al. 2023; Zhao et al. 2025).

Multiple studies illustrate that modern crop cultivars differ from their wild ancestors in both taxonomic composition and functional capacities of their (rhizosphere) microbiome (Hernández‐Terán et al. 2025; Pérez‐Jaramillo et al. 2016; Yue et al. 2023). These shifts reflect changes in plant characteristics that facilitate microbial recruitment and management, called microbiome‐interactive traits (MIT), which often result in shifts in the ability of a crop to engage in beneficial interactions with bacteria and fungi (Clouse and Wagner 2021; Zhao et al. 2025). For example, in wheat, Yue et al. (2023) found that domestication changed the overall assembly of the rhizosphere microbiota, with wild wheat harvesting slow‐growing fungi‐dominated communities and domesticated wheat fast‐growing, bacteria‐dominated structures. However, Hernández‐Terán et al. (2025) found that plant domestication does not consistently result in a reduction in bacterial diversity, but indicated that an additional functional characterisation would be necessary to better understand the consequences of domestication and subsequent breeding on the plant microbiome and its interactions with the plant host.

Before considering whether we can deliberately breed crops for beneficial microbiomes, it is important to recognise that anthropogenic plant breeding has already shaped microbial communities in unintended ways, and disease‐resistance breeding is one of the clearest examples. Indeed, breeding for disease resistance using single dominant resistance genes is a well‐known example of how narrowing the genetic base of crops can unintentionally shape the pathogenic plant microbiome. By creating highly uniform host genotypes, such approaches apply strong and predictable selection pressures that favour the emergence and proliferation of specialised pathogen strains adapted to these specific resistance backgrounds. Although the underlying mechanisms differ from breeding a beneficial microbiome, this illustrates how plant genetic uniformity as a result of rigorous breeding actively drives the evolution of the plant's pathogenic microbiome (Stukenbrock and McDonald 2008).

The emergence of these specialised pathogens, which are adapted to thrive on specific plant genotypes, is central to the question addressed in this opinion paper. If anthropogenic selection has unintentionally ‘bred’ pathogenic microbial communities in the past, could this evolution be reversed, bred and steered in the opposite direction towards diverse plant‐associated beneficial microbiomes that enhance resilience? A positive answer to this question would imply that, although not vertically inherited, a plant microbiome is a selectable trait rather than a passive consequence of crop genetics. Successful implementation of this concept would create a paradigm shift in crop breeding and open new opportunities for sustainable agriculture.

3. Plant Microbial Networks: Diversity, Hubs and Functional Redundancy

In an ecological setting, the microbiome performance does not only depend on the microbial community composition, but also on community architecture, functional diversity and redundancy (Figure 1B). Within a microbial community, a core microbiome comprises keystone microorganisms (hubs) that play a central role in plant‐associated microbial community structures (Mesny et al. 2023). Hubs in plant‐microbiota are often represented by (mycorrhizal) fungi, which affect bacterial assemblage by recruiting different bacterial communities. Through co‐occurrence with other taxa, keystone species are highly connected to other microbes in the network, and exert a strong influence on microbial community structure (Hassani et al. 2018). The core microbiome is dynamic throughout time (plant age) and space (environmental conditions) (Vandenkoornhuyse et al. 2015), hence, the structural layers of a microbial community are elastic rather than fixed (Berg et al. 2020). The elasticity of the core microbiome reflects the non‐linear link between microbial diversity and functional output, as multiple taxa can contribute to similar functions (Ramond et al. 2024). Consequently, shifts in taxonomic community compositions do not always reflect shifts in functionality (i.e., functional redundancy). This helps reconcile observations that taxonomic diversity does not always decline with domestication (Hernández‐Terán et al. 2025): functional capacity and network stability may still change in ways that matter for plant performance. These ecological and functional insights imply that domestication has not only reshaped the plant genome, but also their microbial associates, raising the question of whether breeding strategies should now extend beyond the plant to include the holobiont.

4. From Plant Breeding to Microbiome and Holobiont Breeding

By altering the plant genome, conventional breeding has also altered traits that manage microbiome assembly, clarifying the emerging focus on microbiome breeding. The MITs that once enabled wild ancestors to recruit, select and stabilise beneficial microbial partners have been relaxed, lost or reshaped as a consequence of domestication (Zhao et al. 2025). Despite increasing interest in manipulating plant‐associated microorganisms, the direct introduction of individual strains or microbial consortia into agricultural systems has resulted in inconsistent and often unsatisfactory results (Canfora et al. 2021; De Zutter et al. 2022; Gómez‐Godínez et al. 2021; Laplaze et al. 2016; Negi et al. 2024; Nunes et al. 2024). This underperformance is often due to lack of persistence of microorganisms in a competitive field environment. In synthetic communities (SynComs), the intended beneficial microorganism can be strengthened by keystone and accessory species, however, their performance frequently declines in heterogenous and stress‐prone environments (Clouse and Wagner 2021; Velte et al. 2025; Wang et al. 2025). Hence, many microbial inoculants fail to colonise the plants effectively, fail to outcompete the native microbiota, or fail to sustain activity over time in a changing environment.

These challenges highlight that microbiome engineering cannot solely rely on the introduction to microorganisms in an ecosystem but requires aligning microbial traits with crop genotypes and environmental conditions. As plants exert strong selective pressures on their associated microbiota through immunity and exudates, and conversely, microbial communities modulate the plant phenotype, the plant‐microbiome relationship is inherently bidirectional (Pascale et al. 2020; Rolfe et al. 2019; Van Rensburg et al. 2024; Vandenkoornhuyse et al. 2015). Instead of introducing exogenous strains or SynComs, microbiome breeding might offer a stable and predictive way to select for microbial communities that are already compatible with the host plant and native microbiome, and that are adapted to the target environment. Leveraging the evolutionary and ecological feedback loops offers a more stable and predictable way to shape beneficial microbiomes.

Microbiome recruitment in plants is a directed process shaped by environmental cues and plant‐encoded genes, enzymes and metabolites, enabling plants to respond to biotic and abiotic stresses. Importantly, wild crop relatives are frequently enriched in ancestral microbial taxa that exhibit higher activity or specialisation in these interactions. Rewilding builds on the principle of reintroducing or restoring these wild, ancestral microbial genera with specific traits that are scarce or absent in the microbiome of modern crops (Figure 1C) (Raaijmakers and Kiers 2022). By re‐exposing crops to microbiomes associated with wild relatives, or by selecting plants with ancestral MITs enabling recruitment of beneficial microbial partners, rewilding seeks to restore ecological interactions that were weakened or lost through domestication and intensive breeding (Clouse and Wagner 2021; Ramirez‐Villacis et al. 2025). Modern technologies, such as high‐resolution microbial community profiling, metagenome analysis, pan‐microbiome analysis and culturomics, enable the identification of these natural microbial communities and networks, and the traits that underpin their assembly.

5. Microbiome Breeding: Lessons From and Parallels With QTL Breeding

Recent work has demonstrated that plant genetics plays a decisive role in shaping microbiome assembly, with domestication and breeding having changed key host pathways that govern microbial recruitment and compatibility. It was illustrated that several MITs can be mapped to specific genomic regions, including QTLs (Box 1) that influence exudation patterns, immune signalling, root development and microbial recruitment (Escudero‐Martinez et al. 2022). These host loci act as genetic gatekeepers, determining which microbial partners are recruited, excluded or stabilised and thereby structuring the functional potential of the plant‐associated microbiome. These loci are also often involved in the recognition of pathogenic microbes, a trait which has been intensively bred for (Fitzpatrick et al. 2020). Combining QTL mapping with microbial metagenomic analysis would, in this context, be a promising strategy to pursue (Figure 1D).

BOX 1.

Definition and Principle.

Quantitative Trait Loci (QTLs) are genomic regions that contain genes contributing to, or associated with, a particular quantitative trait (Collard et al. 2005). QTL‐analysis combines phenotypic trait measurements with molecular marker data through statistical associations in order to explain the genetic basis of variation in complex traits (Collard et al. 2005; Kearsey 1998; Myles and Wayne 2008). QTLs can be classified by the magnitude of their effects (major‐ vs. minor‐effect QTLs) and by the type of genetic influence they exert, including pleiotropic effects, epistatic interactions and expression QTLs (Kumar et al. 2017).

Relevance of QTLs in Plant‐Microbiome Research

Although QTL‐mapping was originally developed for classical plant breeding, QTL‐mapping has increasingly been used to uncover host genetic control over microbiome assembly by identifying loci influencing root exudation, plant immunity, root architecture and microbial recruitment (Feng et al. 2024; Oyserman et al. 2022). These genomic regions shape which microbes can colonise the plant and thus influence the functional potential of the plant‐microbiome.

Besides the fact that MITs can be mapped to specific plant genomic regions, the idea of breeding for a beneficial plant microbiome shares, in our opinion, several key features with QTL‐based breeding for complex inherited plant traits on its own. Both microbiome breeding and QTL‐based plant trait breeding address traits that are inherently polygenic.

The ability of a plant to assemble a beneficial microbiome is shaped by multiple host‐controlled factors, including root architecture, exudate chemistry and innate immunity, which are all traits that to some extent have historically been targeted in QTL‐breeding programmes. Deng et al. (2021) used sorghum genotypes and 16S rRNA amplicon sequencing to identify rhizosphere‐associated bacteria exhibiting heritable associations with the plant genotype. Using a GWAS approach (Box 2), host loci that correlated with specific subsets of the rhizosphere microbiome were identified and its structure could be predicted for a test panel of unknown sorghum genotypes based solely on knowledge of the host genotype (Deng et al. 2021).

BOX 2. Genome Wide Association Study.

Definition and Principle

Genome Wide Association Studies (GWAS) identify genomic variants statistically associated with a particular trait by comparing allele frequencies across many individuals that differ phenotypically (Hutter 2026; Tam et al. 2019; Uffelmann et al. 2021). GWAS exploit natural variation to detect genotype–phenotype associations at a high resolution. Advances in high‐throughput genotyping, phenotyping and computational power have enabled routine genome‐wide screenings of numerous SNPs, allowing researchers to uncover loci and causal variants underlying complex traits (Liu and Yan 2019; Tibbs Cortes et al. 2021; Uffelmann et al. 2021).

Relevance of GWAS in Plant‐Microbiome Research

Complex traits underlying plant‐microbiome interactions, including microbial recruitment, metabolite production and root exudation, are shaped by multiple loci and influenced by environmental factors, rendering GWAS highly suitable to identify the plant genetic variation associated with its host microbial community (Beilsmith et al. 2019; Deng et al. 2021; Tibbs Cortes et al. 2021). The success of GWAS in plant systems illustrates how GWAS‐derived insights can accelerate breeding strategies aimed at modifying plant‐microbiome interactions for improved crop productivity and resilience (Bergelson et al. 2021).

Similar as to QTL‐breeding, microbiome breeding is complicated by genotype‐environment interactions. Although the host genotype contributes to microbiome heritability, environmental factors including soil type, climate, soil management and plant developmental stage, are often even more important players under field conditions. Several studies have shown that, although the host genotype contributes to microbiome heritability (Clouse and Wagner 2021; Singh and van der Knaap 2022; Zhao et al. 2025), environmental variation often dominates in field conditions, which makes predictive selection and breeding challenging. Precise and scalable phenotyping technologies will therefore be crucial for the success of microbiome breeding in the future (Wagner 2021).

A third parallel lies in the importance of ‘mutual interactions’ within the system: gene–gene interactions (epistasis) in QTL‐breeding and microbe‐microbe interactions in microbiome breeding. In the same manner that epistasis can mask additive or synergistic genetic effects, microbial interactions imply that selecting for one taxon may not result in the envisioned outcome unless the broader community architecture is considered. Network mapping would therefore be a useful tool, as illustrated by Li et al. (2022), who identified heritable microbial hubs in the Arabidopsis thaliana phyllosphere linked to host gene networks, demonstrating the necessity of treating the microbiome as an interacting system rather than a set of independent features. Finally, once breeding for a beneficial microbiome is successful, stability across generations is the next challenge that QTL‐ and microbiome breeding share. While microbiome traits can show heritable patterns, inheritance occurs indirectly via genotype‐mediated assembly rather than via vertical microbial transmission as in classical breeding. Standardising heritability metrics and localisation‐specific estimates (rhizosphere, root endosphere, phyllosphere) could improve breeding predictability, much like partitioning in QTL‐effects has advanced conventional breeding (Morris and Bohannan 2024).

6. Unexpected and Underexplored Microbial Drivers of Plant Productivity

Beyond the well‐studied plant‐growth promoting bacteria and fungi, a substantial proportion of the plant microbiome remains taxonomically, functionally and ecologically underexplored. Low abundant taxa can strongly influence plant performance by acting as keystone regulators, accessory species or helper organisms, yet they often slip through the cracks of current metabarcoding approaches (Dawson et al. 2017; Li et al. 2025). Standard 16S, ITS and COI markers lack the resolution and taxonomic accuracy to distinguish between closely related strains with divergent functionalities (Johnson et al. 2019), while other microbial groups such as archaea, microeukaryotes, protists, viruses and endophytic yeasts are often overlooked (Dumack and Bonkowski 2021; Gao et al. 2019; Poupin and González 2024). Integrating these underexplored microbial drivers into microbiome breeding and understanding their ecological roles can be a critical next step in expanding the pool of selectable traits and increasing the adaptive potential of synthetic communities.

At the same time, several ecologically important microbial lineages receive even less attention because of safety concerns. A striking example is Burkholderia spp., which hold great potential to promote plant growth and suppress plant pathogen infection (Coenye and Vandamme 2003; Eberl and Vandamme 2016), however are excluded from inoculant development pipelines due to the presence of opportunistic pathogens in the genus. This creates an interesting paradox, where functionally valuable species that are abundant in natural microbiomes remain unexplored, unexpected and even constrained in applied microbiome breeding due to their clinical relevance. To overcome these blind spots, deeper multi‐omics profiling will need to be combined with risk‐aware frameworks that differ between safe and unsafe lineages within functionally promising genera.

7. Concluding Remarks

Domestication and plant breeding have reshaped plant microbe partnerships. In our opinion, the way forward is not to abandon plant genetics, but to couple it with deliberate management of microbiome assembly, using the crop's own genetic handles, ecological design principles and knowledge from its wild relatives' microbiomes. In this way, we could turn the microbiome from a background variable into a sustainable breeding target. Several keystone hurdles were identified in this approach that should be taken to make this a successful strategy (Figure 1D):

  • Identify and validate QTLs/genes underlying exudation, immunity and genetic traits that control microbial partner recruitment.

  • Develop high‐throughput, trait‐based phenotyping that enlightens microbial functions such as nutrient use, stress mitigation and disease suppression.

  • Develop functional co‐occurrence and causal network analyses to identify hubs/keystones and functional microbiomes on which SynComs could be built.

  • Run multi‐site and multi‐season trials to model genotype × environment × microbiome interactions, quantify stability and define heritability metrics.

  • Rewild microbiomes and restore ancestral microbial partners where domestication expunged them and investigate the role of underexplored taxa in these wild microbiomes.

  • Integrate microbiomes in plant breeding pipelines: add microbiome functions to breeding selection indices and map this information to the genome where feasible.

  • Share interoperable datasets for microbiome functionality, heritability and stability in view of the complexity and high dimensionality of data.

When these hurdles are taken, we are convinced that breeding the plant and its microbiome is the path towards sustainable crop production that plant‐only approaches have failed to deliver in the past.

Author Contributions

Noémie De Zutter: conceptualization, writing – original draft, writing – review and editing, visualization. Kris Audenaert: conceptualization, writing – original draft, writing – review and editing, visualization.

Funding

The authors have nothing to report.

Conflicts of Interest

The authors declare no conflicts of interest.

Data Availability Statement

The authors have nothing to report.

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