Microbiota provide diverse benefits to their hosts, including nutrient acquisition, stress tolerance, and disease resistance. However, the mechanisms by which plants coordinate intrinsic and extrinsic cues to shape microbial communities remain poorly understood. Receptor-like kinases (RLKs), one of the largest gene families in plants, are central to the perception of both exogenous and endogenous signals, including pathogens, mutualists, and plant physiology. Indeed, recent evidence has identified RLKs that regulate microbiome structure and function. This minireview focuses on how their quantity and ability to transduce diverse signals make RLKs strong candidates to coordinate plant physiology and immunity with the microbiome.

Legume root nodules are important for biological nitrogen fixation, a process critical for plants to gain additional nitrogen from the environment. Nodule quantification is valuable for evaluating nitrogen fixation efficiency, assessing symbiotic relationships, monitoring responses to nitrogen, and supporting genetic studies on legume adaptation and productivity. However, accurate quantification of root nodules is difficult and time-consuming due to the complexity of the root system and soil interference. Here, we explore the utility of hyperspectral imaging as a non-destructive tool to detect active fixing root nodules with minimal preparation and show that we can differentiate nodules and root tissues through unique spectral signatures while also distinguishing between fixing and non-fixing nodules. We applied deep learning techniques to develop an automated nodule counting pipeline adaptable across different legume species and under diverse growth conditions. This approach eliminates the need for labor-intensive counting and enables the detection of nodules embedded within dense root tangles with high accuracy. This automated hyperspectral approach offers a promising alternative to support assessments of nodule abundance and their activity across legume species grown under various environments.

Chickpea (Cicer arietinum L.) is a vital/essential legume crop valued for its nutritional, agricultural, and economic importance, with a relatively large genome size of approximately 738 megabases. Chickpea roots establish symbiotic relationships with soil microorganisms, resulting in the formation of root nodules essential for biological nitrogen fixation. In this study, 20 chickpea genotypes were selected from a genome-wide association panel to assess nodulation traits under eight different treatment combinations involving biofertilizers (Rhizobium, vesiculararbuscular mycorrhiza -VAM) and inorganic fertilizers (NPK) using a randomized block design with three replications. Pre-planting soil preparation included the application of fertilizers and biofertilizers. Comprehensive analyses including descriptive statistics, correlation, path analysis, principal component analysis, agglomerative hierarchical clustering, and gene expression studies were conducted. Among treatments, the NPK+Rhizobium combination significantly enhanced nodulation across genotypes, while the Rhizobium+VAM (T7) treatment identified ICC-9085 as a superior donor for the number of nodules, aiming for sustainable chickpea productivity. Gene expression profiling through qRT-PCR revealed that the RZ+VAM treatment notably upregulated several key genes, including CaNFP, GST, Leghemoglobin, Nodulin6, and CaLYK3, with CaNFP emerging as a pivotal regulator of nodulation. The marked upregulation of CaNFP underlines its potential as a target for enhancing symbiotic efficiency. The availability of the chickpea draft genome opens new avenues for employing genome editing tools such as CRISPR/Cas systems. Targeted editing of the CaNFP gene offers a promising strategy to improve nodule formation, nitrogen fixation, and overall plant vigor. Integrating CaNFP gene through genome editing with potential genotypes and use of microbial treatments can accelerate the development of elite chickpea cultivars, enhancing productivity while reducing reliance on chemical fertilizers and supporting sustainable agricultural practices.

Symbiosis between Bradyrhizobium strains isolated from Lao People’s Democratic Republic (Lao PDR) and intercropped legumes (Arachis hypogaea, Vigna radiata, and V. mungo) was regulated by the type III secretion system (T3SS), which delivers effector proteins (T3Es) into host plant cells to modulate nodulation. To explore this mechanism, we sequenced and analyzed seven Bradyrhizobium genomes, identifying putative T3Es across five T3SS groups (G.1–G.5), which were classified based on the sequence of rhcN, a conserved ATPase gene essential for T3SS function. Phylogenetic analysis of rhcN more closely reflected the evolutionary relationships of nodulation genes than those based on 16S rRNA or whole-genome comparisons, underscoring its symbiotic relevance. Functional assays using rhcN mutants revealed group-specific effects on nodulation; G.1 strains showed neutral effects on A. hypogaea, negative effects on V. radiata, and positive effects on V. mungo. G.2 strains consistently promoted nodulation across all hosts and lacked effectors related to SUMO (small ubiquitin-like modifier) pathways, which have been implicated in host defense regulation. G.3 strains reduced nodulation in A. hypogaea but enhanced it in Vigna species. G.4 strains suppressed nodulation in A. hypogaea, and G.5 strains inhibited nodulation across all tested legumes. These findings highlight the diversity in T3SS organization, effector composition, and symbiotic responses among native Bradyrhizobium strains. The identification of known and uncharacterized effectors suggests roles in host compatibility and specificity. These strains, along with their effector profiles, provide a foundation for future functional studies to better understand T3SS-mediated interactions and support the development of targeted inoculants for legume hosts.

Strigolactones are ecologically, developmentally, and physiologically important hormones, but much remains unknown about their evolution and role in non-model species. Sorghum is an important C4 cereal for ∼1 billion people globally and exhibits natural variation in root-exuded strigolactones. Differences in sorghum strigolactone stereochemistry are associated with resistance to a parasitic plant, but with evidence for potential trade-offs. In the present study, we studied sorghum mutants of loci in the strigolactone biosynthetic pathway, CAROTENOID CLEAVAGE DIOXYGENASE 8 (CCD8) and LOW GERMINATION STIMULANT 1 (LGS1). We found that CCD8 CRISPR-Cas9 deletions changed the accumulation of low abundance metabolites, reduced net carbon assimilation rate, altered root architecture and anatomy, and reduced the establishment and benefit of mycorrhizal symbionts. For LGS1 CRISPR-Cas9 deletions, we found net carbon assimilation rate to be reduced, the colonization of mycorrhizal symbionts to be delayed, and evidence for regulatory pathways involved in stress response and growth to be impacted. We further tested the impacts of restoring functionality of LGS1 into a normally non-functional background (RTx430). Notably, we did not see consistent impacts of LGS1 loss-of-function across LGS1 deletion and insertion mutants, though root exudates from insertion mutants increased stimulation of Striga germination, suggesting that background specific modifiers may buffer the strigolactone impacts of loss-of-function at LGS1. Our study begins to give context to the trade-offs associated with a host resistance strategy to a parasitic plant and more broadly contributes to understanding the role strigolactones play in sorghum physiological processes, growth, and development.

This study explores the potential of machine learning to predict nitrogen fixation efficiency in rhizobia strains associated with cowpea (Vigna unguiculata), aiming to optimize bioinoculant selection for sustainable agriculture. Eight native strains were isolated from soils in the Brejo Paraibano region (Brazil), characterized morphologically on Yeast Mannitol Agar YMA medium, and evaluated in greenhouse bioassays for nitrogen accumulation and Relative Index of Nitrogen Fixation Efficiency (IRF%). A Ridge Regression model was then developed using phenotypic colony traits as predictors to estimate Total Nitrogen and IRF%. The results demonstrated strong correlations between predicted and actual values (r = 0.95–0.96), suggesting that visible colony characteristics can serve as reliable proxies for strain efficiency. This approach has the potential to offer a cost-effective alternative to traditional greenhouse trials, with indications of reduced time and resource demands. However, these results are theoretical and require validation through larger datasets and field conditions before broad application in sustainable agriculture can be considered.

Nitrogen-fixing root nodule symbiosis (RNS) occurs in some eudicots, including legumes, and is regulated by the transcription factor NODULE INCEPTION (NIN), derived from the NIN-LIKE PROTEIN (NLP) family. However, how the NIN protein acquired RNS-specific functions remains unclear. We identify a previously undescribed motif in Lotus japonicus NIN, located downstream of the RWP-RK domain, which we term the FR. This motif broadens the DNA-binding specificity of NIN by stabilizing the RWP-RK dimer interface. nin mutants lacking the FR motif show defective nodulation and impaired nitrogen fixation. Arabidopsis NLP2 carries a NIN-type FR and shares key features with NIN. Furthermore, the NIN-type FR likely originated as early as gymnosperms, suggesting that the molecular feature of NIN for RNS regulation was inherited from ancestral NLPs before RNS emerged.

Plant–microbe symbioses such as the legume–rhizobium mutualism are vital in the web of ecological relationships within both natural and managed ecosystems, influencing primary productivity, crop yield, and ecosystem services. The outcome of these interactions for plant hosts varies quantitatively and can range from highly beneficial to even detrimental depending on natural genetic variation in microbial symbionts. Here, we take a systems genetics approach, harnessing the genetic diversity present in wild rhizobial populations to predict genes and molecular pathways crucial in determining partner quality, i.e., the benefits of symbiosis for legume hosts. We combine traits, dual-RNAseq of both partners from active nodules, pangenomics/pantranscriptomics, and Weighted Gene Co-expression Network Analysis (WGCNA) for a panel of 20 Sinorhizobium meliloti strains that vary in symbiotic partner quality. We find that genetic variation in the nodule transcriptome predicts host plant biomass, and WGCNA reveals networks of genes in plants and rhizobia that are coexpressed and associated with high-quality symbiosis. Presence–absence variation of gene clusters on the symbiosis plasmid (pSymA), validated in planta, is associated with high or low-quality symbiosis and is found within important coexpression modules. Functionally our results point to management of oxidative stress, amino acid and carbohydrate transport, and NCR peptide signaling mechanisms in driving symbiotic outcomes. Our integrative approach highlights the complex genetic architecture of microbial partner quality and raises hypotheses about the genetic mechanisms and evolutionary dynamics of symbiosis.

Heat stress is a major limiting factor for soybean productivity worldwide. Recent studies have highlighted the critical role of the plant microbiome in enhancing plant resilience to heat stress. However, our understanding of the molecular and physiological mechanisms underlying root-microbiome interactions under heat stress remains limited. To elucidate the role of native soil microbes in the heat tolerance of soybean genotypes, we analyzed rhizosphere bacterial and fungal communities via 16S rRNA and ITS sequencing, and characterized root metabolites and anatomical traits in response to microbiome composition and heat stress. Soybean plants were grown under controlled conditions in either natural soil containing native microbiota or in microbiome-disturbed soil (via 3-hour autoclaving), under both optimal and elevated temperature regimes. Alpha and beta diversity analyses revealed significant microbial shifts between treatments. Distinct clustering of bacterial, fungal, and metabolite profiles was observed under high temperature and microbial disturbance. Nodule-forming bacteria such as Rhizobium and Janthinobacterium were markedly suppressed, and belowground traits exhibited sensitivity, with significantly reduced nodule numbers and nodulation efficiency under high temperature and soil microbial perturbation. Non-targeted root metabolomics identified 372 differentially accumulated metabolites. Integrative multi-omics analysis revealed associations between metagenomic profiles, metabolite levels, and nitrogen-fixation traits, implying a coordinated modulation of root physiological processes. These findings contribute to a growing understanding of how heat stress interacts with rhizosphere microbial communities and may support future efforts in breeding climate-resilient soybean cultivars.

Arbuscular mycorrhizal fungi (AMF) are ubiquitous in cultivated soils, forming symbiotic relationships with the roots of crop species. This ancient symbiosis, which originated >450 MYA and persists in 85% of plant species, has attracted increasing attention as a breeding target for improved crop nutrient use efficiency. Greenhouse studies have demonstrated the potential of the symbiosis to enhance crop growth. It is difficult, however, to estimate the actual benefit in crop fields due to the lack of suitable AMF-free controls. Here we report the use of maize genetic mutants to incorporate AMF-incompatibility into genetic mapping populations, allowing for an AMF-free contrast condition to characterize the impact of host genotype on AMF response. Through the introgression of transposon insertion mutant alleles of AM symbiosis genes (CASTOR, POLLUX, and CCaMK) into mapping families, loci responsible for variation in yield can be evaluated in the presence and absence of AMF. We are using these populations for trait mapping by estimating QTL and QTLxAMF effects by comparison of 300 mycorrhizal families and 150 non-mycorrhizal families. Following two years of field evaluations, we present evidence of whole-genome plant genetic trade-offs between performance with and without AMF. Identifying loci associated with AMF response has enabled us to determine gene networks regulating AM symbiosis across soil environments, including low nitrogen conditions in which hybrid mutant genotypes deficient in AMF yielded 40.8% less grain by weight. Utilizing root transcriptomes of the founder inbreds and their hybrids in greenhouse conditions, we have identified cis-regulated QTLs more amenable to downstream breeding efforts. Identifying these significant QTLxAMF effects and cis-regulatory variants indicates the potential for tailoring crop varieties to optimize AMF benefits across agroecosystems with diverse inputs and management. The integrated approaches we present apply to other crop species, permit further mechanistic study, and are scalable to larger yield trials.

Legumes (Fabaceae) form symbiotic associations with rhizobia (Rhizobiaceae), but unchecked bacterial proliferation can lead to loss of host fitness. In the Inverted Repeat Lacking Clade (IRLC) legumes, Nodule-specific Cysteine-Rich (NCR) peptides regulate rhizobial differentiation, limiting their pathogenic potential and maintaining a balanced symbiosis that supports plant growth. In planta screening of NCRs is challenging for multiple reasons; hence, bioinformatics prediction from genomic and transcriptomic data offers a high-throughput alternative. In this study, an \textit{in silico} workflow was developed that incorporates established bioinformatics tools with R programming and local BLASTp to identify NCR-like peptides from genomic data. Various R libraries, including packages of the Bioconductor suite, ampir,and dplyr, were used to screen peptides based on specific criteria, such as a length of 20–180 amino acids and at least four cysteine residues. The identified peptides were further analyzed for motif patterns, sequence similarity with NCRs previously reported by Montiel et al. [1], and signal peptide cleavage sites. Using this approach, 284 and 497 NCR-like peptides with conserved cysteine positions were identified in Trigonella foenum-graecum and Medicago truncatula genome assemblies, respectively. The predicted physicochemical properties of the screened peptides from the two legumes were comparable because they are evolutionarily closely related. This suggests that the workflow can be applied to other IRLC legumes to screen for NCRs and explore their functions in rhizobial symbiosis and antimicrobial defense.

Soybean serves as a crucial source of plant-based protein for human diets. Recently, there is a growing incentive to extend the range of this crop to more northern latitudes, in order to enable profitable soybean production in Europe. To reach economic yields, soybean requires inoculation with symbiotic, diazotrophic rhizobial bacteria. However, the performance of commercial inocula is often variable under local conditions. Here, we present the citizen science project “Soy in 1,000 Gardens”, a large-scale trapping experiment for isolating local soybean-nodulating rhizobia in Flanders, Belgium. We identified two locally isolated Bradyrhizobium strains performing at least as well as commercial strain B. diazoefficiens G49 in local field trials. Additionally, we found that nutrient content, microbial alpha diversity, and the presence of arbuscular mycorrhizal fungi in the soil were correlated with nodulation. Finally, we report a correlation between low bacterial alpha diversity and red nodule interior, and identified Tardiphaga as a dominant colonizer of red nodules.

Symbiotic nitrogen fixation (SNF) is a key trait in legume productivity, yet the genetic and regulatory basis underlying its natural variation remains poorly understood. Here, we integrated genome, transcriptome, and chromatin accessibility data from a soybean diversity panel comprising 380 accessions, including 108 wild and 272 cultivated lines. Genome-wide association studies (GWAS) detected multiple loci for SNF traits but with limited resolution due to polygenic architecture and environmental influences. Independent component analysis (ICA) identified 136 co-expression modules; ten ICs were strongly correlated with SNF phenotypes and enriched in circadian clock components (e.g., GmLHY1a/b), lipid metabolism, or defense signaling pathways. Transcriptome-wide association studies (TWAS) linked 1,453, 806, and 178 genes to NFP, NW, and NFE traits, respectively. Among TWAS hits, 185 transcription factors were identified, with 39.0% overlapping selective sweeps, suggesting regulatory evolution under domestication. To further dissect expression regulation, we performed eQTL mapping and detected 4,654 significant eQTLs, including 1,241 local (cis), 2,505 distal (trans), and 908 mixed. By integrating ATAC-seq data from sorted nodule nuclei, we found that eQTLs, particularly local eQTLs, are significantly enriched within open chromatin regions, indicating their regulatory potential. Notably, we validated the circadian clock gene GmLHY1b as a negative regulator of nodulation using CRISPR mutagenesis and CUT&Tag. Our integrative study provides comprehensive genomic and transcriptomic resources from a diverse soybean population, offering novel insights into SNF regulatory networks and a valuable foundation for future SNF research and soybean improvement.

Reverse genetics, facilitated by CRISPR technologies and comprehensive sequence-indexed insertion mutant collections, has advanced the identification of plants genes essential for arbuscular mycorrhizal (AM) symbiosis. However, a mutant phenotype alone is generally insufficient to reveal the specific role of the protein in AM symbiosis and in many cases, identifying interacting partner proteins is useful. To enable identification of protein:protein interactions during AM symbiosis, we established a Medicago truncatula -Diversispora epigaea yeast-two-hybrid (Y2H) library which, through Y2H-seq screening, can provide a rank-ordered list of candidate interactors of a protein of interest. We also developed a vector system to facilitate bimolecular fluorescence complementation assays (BIFC) in mycorrhizal roots so that protein interactions can be assessed in their native cell types and sub-cellular locations. We demonstrate the utility of a Y2H-seq screen coupled with BIFC in mycorrhizal roots, with a search for proteins that interact with CYCLIN DEPENDENT LIKE KINASE 2 (CKL2), a kinase essential for AM symbiosis. The Y2H-seq screen identified three 14-3-3 proteins as the highest ranked CKL2 interacting proteins. BIFC assays in mycorrhizal roots provided evidence for a CKL2:14-3-3 interaction at the periarbuscular membrane (PAM) in colonized root cells. Down-regulation of 14-3-3 by RNA interference provides initial evidence for a function in AM symbiosis. Thus, CKL2 may utilize 14-3-3 proteins to direct signaling from the PAM. The Y2H and BIFC resources will accelerate understanding of protein functions during AM symbiosis.

Sinorhizobium meliloti forms a robust N2-fixing root-nodule symbiosis with Medicago sativa. We are interested in identifying the minimal symbiotic genome of the model strain S. meliloti Rm1021. This gene set refers to the minimal genetic determinants required to form a robust N2-fixing symbiosis. Many symbiotic genes are located on the 1,354 kb pSymA megaplasmid of S. meliloti Rm1021. We recently constructed a minimalized pSymA, minSymA2.1, that lacked over 90% of the pSymA genes. Relative to the wild-type, minSymA2.1 showed a reduction in M. sativa shoot biomass production and nodule size with an increase in total nodule number. Here we show that the addition of either the stachydrine (stc) or trigonelline (trc) catabolism genes from pSymA to minSymA2.1 restores nodule size and total nodule number to levels indistinguishable from the wild-type but does not restore reduced shoot biomass production. In the context of the complete Rm1021 genome, removing the stc genes reduced nodule size and increased total nodule number while removal of the trc genes alone had no apparent effect. Together, these observations implicate stachydrine catabolism as an important determinant of root nodule symbiosis between S. meliloti and M. sativa while trigonelline catabolism seems to contribute in a more conditional manner, in the context of the minimized genome. These findings highlight the minimal symbiotic genome as a tool for investigating the impact individual genetic determinants have in conferring an optimal symbiosis. Factors whose impact, in the context of a complete genome, may be hidden or dampened due to redundancies.

Purpose
Crop domestication reshapes rhizosphere microbial communities, yet its effects on nitrogen use efficiency (NUE) in C4 cereals such as millet remain unclear.

Methods
We assessed how domestication influences rhizosphere microbiome assembly and its association with NUE in millet. Six genotypes representing wild (Setaria viridis), landrace, and cultivated (Setaria italica) stages were grown under two nitrogen levels (N0, N25) in a greenhouse. Rhizosphere bacterial and fungal communities were profiled using 16S rRNA and ITS sequencing. Diversity indices, PERMANOVA, LEfSe, correlation analysis, structural equation modeling, and network analysis were applied.

Results
Fungal communities were more strongly affected by domestication than bacterial communities, showing marked reductions in alpha diversity and shifts in community composition across genotype groups. In contrast, bacterial diversity remained relatively stable. Under nitrogen addition (N25), wild genotypes with higher NUE were positively associated with specific fungal taxa, including Phlyctis (Lecanorales, Ramalinaceae), Trichoderma, and Gibellulopsis, whereas these associations were absent in highly domesticated cultivated genotypes. In wild millet, plant traits mediated the enrichment of Phlyctis (Lecanorales, Ramalinaceae), while nitrogen addition enhanced its network centrality but reduced the connectivity of other NUE-associated fungal taxa.

Conclusion
These findings suggest that domestication weakens beneficial plant-fungal interactions critical for nitrogen acquisition, providing insights into ecological trade-offs of crop improvement and highlighting the potential of microbiome-informed breeding strategies to enhance NUE in millet.