Skip to main content
Download PDF

Soil fungal community structure and function response to rhizoma perennial peanut cultivars

BMC Plant Biology volume 24, Article number: 582 (2024) Cite this article

Abstract

Background

Crop-associated microorganisms play a crucial role in soil nutrient cycling, and crop growth, and health. Fine-scale patterns in soil microbial community diversity and composition are commonly regulated by plant species or genotype. Despite extensive reports in different crop or its cultivar effects on the microbial community, it is uncertain how rhizoma peanut (RP, Arachis glabrata Benth.), a perennial warm-season legume forage that is well-adapted in the southern USA, affects soil microbial community across different cultivars.

Results

This study explored the influence of seven different RP cultivars on the taxonomic composition, diversity, and functional groups of soil fungal communities through a field trial in Marianna, Florida, Southern USA, using next-generation sequencing technique. Our results showed that the taxonomic diversity and composition of the fungal community differed significantly across RP cultivars. Alpha diversity (Shannon, Simpson, and Pielou’s evenness) was significantly higher in Ecoturf but lower in UF_Peace and Florigraze compared to other cultivars (p < 0.001). Phylogenetic diversity (Faith’s PD) was lowest in Latitude compared to other cultivars (p < 0.0001). The dominant phyla were Ascomycota (13.34%), Mortierellomycota (3.82%), and Basidiomycota (2.99%), which were significantly greater in Florigraze, UF_Peace, and Ecoturf, respectively. The relative abundance of Neocosmospora was markedly high (21.45%) in UF_Tito and showed large variations across cultivars. The relative abundance of the dominant genera was significantly greater in Arbrook than in other cultivars. There were also significant differences in the co-occurrence network, showing different keystone taxa and more positive correlations than the negative correlations across cultivars. FUNGuild analysis showed that the relative abundance of functional guilds including pathogenic, saprotrophic, endophytic, mycorrhizal and parasitic fungi significantly differed among cultivars. Ecoturf had the greatest relative abundance of mycorrhizal fungal group (5.10 ± 0.44), whereas UF_Peace had the greatest relative abundance of endophytic (4.52 ± 0.56) and parasitic fungi (1.67 ± 0.30) compared to other cultivars.

Conclusions

Our findings provide evidence of crop cultivar’s effect in shaping fine-scale fungal community patterns in legume-based forage systems.

Graphical abstract

Peer Review reports

Background

In agricultural ecosystems, there is an increasing demand to boost food production in response to the rapid growth of the global population. However, the traditional approach that relies on high external inputs to increase crop yield has been demonstrated to be unsustainable in agricultural management practices [1]. Crop-associated microbiomes play an important role in regulating many key ecological processes, including carbon (C) and nitrogen (N) cycling [2], nutrient acquisition [3], and soil formation [4], consequently affecting crop growth and health [5]. In a recent study, early season soil microbiome has been shown a better ability for predicting wheat grain quality [6]. Soil fungi, such as Penicillium [7], Trichoderma [8], and arbuscular mycorrhiza fungus (AMF) [9], can promote plant growth. These fungal members, known as plant growth promoting fungi (PGPF), exert a positive effect on plants by a variety of mechanisms, such as facilitating plant nutrient uptake (e.g., nitrogen and phosphorous) [2], and enhancing plant resistance against abiotic stresses [10] and pathogenic microorganisms [11]. Understanding fungal diversity, composition and functions, and their relationships with crops is particularly important for the development of microbial-based indicators and fertilizers for sustainable agriculture and soil health [12, 13].

Soil fungi are highly diversified and serve crucial roles in ecosystems. Most of them are saprotrophs and can work as decomposers to promote nutrient cycling [14]. For example, Basidiomycota plays important roles in the decomposition of plant litter and complex organic materials (cellulose, lignin, and pectin) in soils [15], by producing extracellular hydrolytic and oxidative enzymes [16]. Some fungi can also form mutualistic relationships with their hosts [17, 18], which provide various benefits to plant growth including nutrient mobilization, hormone production, biological dinitrogen fixation (BNF), and drought resistance [19, 20]. For example, mutualistic, endophytic fungus Piriformospora indica has been shown to improve plant growth, increase nutrient uptake, and enhance resistance to various stresses such as drought and salinity [21]. Numerous reports have shown that AMF are one of the most important groups of symbionts that live among the roots of most plant species. These fungi enhance plant growth by promoting root formation [22] and optimizing resistance to abiotic stresses [23]. Previous studies have reported that soil fungi have biological control actions against pathogenic microorganisms, which generate a favorable impact on plant productivity [24, 25].

Soil microbial communities are generally influenced by climatic and soil factors [26, 27], but fine-scale assembly patterns in microbial communities are closely associated with host plant characteristics such as root exudates and root morphology. Due to the differences in root structure and exudates [28], volatile organic compounds [29], and quality and quantity of carbon input [30], different plant species or genotype can serve to induce specific taxa of microbial communities in their rhizosphere and recruit symbiotic organisms to roots. In crop systems, growing evidence has shown that the composition and diversity of soil microbial communities varied largely among cultivars in various crops [31, 32], including wheat [33], rice [34], sorghum [35], chickpea [36] and peanut [37, 38]. Understanding the effects of different plant species or genotypes on microbial communities is important for optimizing agricultural practices, enhancing soil health, and promoting sustainable crop production through modulating plant-microorganism interactions. However, our understanding of cultivar effects on soil fungal communities remains very limited, especially in forage systems.

Rhizoma peanut (RP; Arachis glabrata Benth.) is a perennial warm-season legume forage that is adapted to sandy soils in southern USA [39, 40] and is a beneficial option for pasture integration [41]. RP has a considerable potential to increase soil N supply in grasslands. Like many other perennial legume species, RP supplies N through biological N2 fixation (BNF), which is a major source of N in agricultural systems (50–70 Tg N annually) [42]. When grown with companion grasses, N from RP can be shared with pasture grasses by plant litter, root exudates, and grazing animals via animal excreta [40, 43]. In addition, RP increases soil N accumulation and enriches litter quality in C4 grass pastures [44].

Several RP cultivars exist in Florida and serve different purposes. Some cultivars, such as Arbrook, UF_Peace, and UF_Tito, are grown as forages, while others serve as groundcover, like Ecoturf. Others are known for being disease-resistant, such as UF_Tito and UF_Peace. According to Dubeux et al. [40], the potential of BNF in RP is cultivar-dependent and may be linked to variation in the diversity and composition of the rhizosphere microbial communities. Ecoturf and Florigraze are the two most commonly used RP cultivars in Florida. Erhunmwunse et al. [27] reported changes in soil fungal communities across the two cultivars. However, further evidence is needed to evaluate the effects of these RP cultivars and other cultivars on soil fungal communities. In this study, we hypothesized that the host plant cultivar would lead to significant changes in soil fungal community structure and function. The objectives of this study are to (i) examine the changes in soil fungal community diversity and composition across different RP cultivars; and (ii) identify the changes in functional groups and keystone taxa of fungal communities among the different RP cultivars. “Keystone taxa are species within an ecosystem that have a disproportionately large impact on the structure and function of that ecosystem”.

This study characterized the soil fungal community structure and function under seven perennial RP cultivars under the same soil type and conditions. Our study lays the framework for understanding the role of RP-based forage systems on soil fungal composition, function, and contributions to pasture growth and soil health.

Materials and methods

Study site and sampling

This study was conducted at the North Florida Research and Education Center (NFREC) in Marianna, Florida, Southeastern United States (30°52′N, 85°11′W). The soil at the experimental site was Red Bay fine sandy loam fine-loamy, thermic, and kaolinitic, Rhodic Kandiudults; USDA Soil Survey Staff [45]. The average annual rainfall in the experimental area was 1360 mm over the past 30 years, and the average altitude was 35 m a.s.l. The average temperature in 2020 was 20.0 °C (6.7 and 31.7 °C min/max, respectively). A total of seven different cultivars (Arblick, Latitude, UF_Tito, UF_Peace, Florigraze, Arbrook and Ecoturf) were planted in September 2010. The experiment was established in a randomized complete block design with four replicates for each cultivar. The size of each plot was 2 m × 3 m, and there was a 2-m alleyway between the plots. Planting materials were obtained from the NFREC. In April 2015, the herbicide [5-methyl-2-(4-methyl-5-oxo-4-pro-pan-2-yl-1 H-imidazol-2-yl) py-ridine-3-carbo-xylic acid] was used. In addition, 56 and 74 kg ha− 1 potassium and 29 and 10 kg ha− 1 phosphorus were applied to these plots in June 2014 and April 2015, respectively. A detailed description of the plot design and management practices was reported in a previous study [40].

Soil sampling and DNA extraction

In April 2017, we randomly selected three soil cores (3 cm diameter × 10 cm depth) in each plot, resulting in twelve soil samples per cultivar to minimize the random effect of spatial differences. A total of 84 samples were thus collected from the experimental field. Roots affect the entire soil surface because of the horizontal growth pattern of RP, which occurs via rhizomes. Therefore, the soil samples we collected comprised both bulk and rhizosphere soils. The samples were immediately placed in an icebox after being sealed in a sterile plastic bag and transported to the laboratory within 2 h. The soil samples were sieved using a 2-mm sieve to remove roots, debris, and rocks. Subsequently, the samples were thoroughly mixed to achieve homogeneity and then preserved at -80 °C for DNA extraction. Total soil DNA was extracted according to the manufacturer’s instructions using the Qiagen’s DNeasy PowerSoil Kit (Qiagen Inc., CA, USA). The quality and quantity of the extracts were evaluated using a spectrophotometer (NanoDrop (ND-ONE-W), ThermoFisher Scientific, Waltham, MA, USA). The quantity and quality of DNA were determined by measuring the absorbance ratios (A260/A280 and A260/A230) using a NanoDrop TM One (NanoDrop Technologies Inc., ThermoScientific, USA). The absorbance ratios ranging from 1.8 to 2.2 are considered indicative of high-quality DNA extraction.

Amplicon sequencing data analysis

Composition and diversity of soil fungal community was determined using a modified form of the three-step PCR method targeting fungal ITS1 region, as Chen et al. [46] described. In brief, fungal ITS1 genes were amplified using the primer pair ITS1F (5’ -CTTGGTCATTTAGAGGAAGTAA-3’) and ITS2R (5’-GCTGCGTTCTTCATC GATGC-3’) for ten PCR cycles (first-step PCR). In addition to the sequencing primer, six frameshifting primers were used in ten additional PCR cycles (2nd -step PCR). The frameshifting primers were made up of the primer pair used in the first step of PCR along with frameshifting nucleotides. This was done to increase diversity and reduce sequence bias in the initial bases [47]. We then used the third-step PCR to add error-tolerant barcodes through ten more PCR cycles. Prior to aggregation, we individually purified the third-step PCR products using bead cleaning (AMPure XP, Beckman Instruments, Brea, CA, USA). A spectrophotometer (NanoDrop™) was used to measure the amount and quantity of PCR products. Moreover, 1.7% (w/v) agarose gels were used to screen the PCR products to confirm their size and quantity. The Illumina (Illumina Inc., San Diego, CA, USA) Miseq Nano (v2 250 bp, 500 Mb sequencing capability) at the Duke Center for Genomic and Computational Biology (GCB, Durham, NC, USA) was used to pool and sequence the barcode PCR products.

Sequencing data were processed at the Chinese Academy of Sciences Research Center for Eco-Environmental Sciences, (http://mem.rcees.ac.cn:8080/root/) using an in-house pipeline developed on the Galaxy platform [48]. In summary, the forward and reverse threads of the same sequence were combined using FLASH v1.2.5 to create a single sequence with at least 30 bp of overlap and 0.25 mismatches [49]. The sequences were then quality trimmed using Btrim [50] with a Phred-score threshold of 30 over a 5-bp window size. Next, sequences were clustered using UPARSE at the 97% identity threshold to create operational taxonomic units (OTUs) [51]. OTUs that had only one read (singletons) were removed. Based on the clustering results, the final OTUs were produced. The UNITE ITS reference database provided a taxonomy annotation for representative sequences of OTUs [17]. Using the resampled OTU table available at Dryad (https://doi.org/10.5061/Dryad 8080), we rarefied all samples to an equal sampling depth of 1800 sequences for subsequent community analysis.

Statistical analysis

Four indices, including Shannon index, Simpson index, Pielou’s evenness, and phylogenetic diversity (Faith’s PD), were used to evaluate fungal alpha diversity in this study. Based on the phylogenetic tree and OTU table, Faith’s PD was calculated using the pd function from the picante package in R version 3.5.3.​​​​​​​ The graphs of alpha diversity and the Venn diagram were made using omics studios (https://www.omicstudio.cn/). Principal coordinate analysis (PCoA) were used to visualize dissimilarity between samples using CANOCO 5 software (version 4.5 for Windows; Ithaca, NY, USA) (Canoco5, 2012). The anosim function in the vegan package was used to test the effects of cultivars on the fungal community structure. We selected ten dominant phyla and 20 dominant genera (mean relative abundance > 1% across all samples) to examine the differences in composition among seven different cultivars. Canoco software (version4.5 for Windows; Ithaca, NY, USA) was used to perform Principal component analysis (PCA) to investigate taxonomic distributions at the genus level across cultivars. Circos 0.67-7 software was used to display the Circos graph to reveal the changes in fungal taxonomic interactions across seven different cultivars. The network analysis was carried out using the Wekemo Bioincloud (https://www.bioincloud.tech/) for the 20 dominant bacterial genera across RP cultivars, which was measured by Spearman rank correlation coefficients with p-value of 0.05. If the data does not meet the assumptions of normality of variance, the data was log-transformed or square-root transformed. Significant differences in alpha diversity metrics were tested using the ANOVA with Tukey’s HSD test. FUNGuild was used to predict the functions of the fungal communities in seven different RP soil samples. The fungal functional group (guild) was determined by FUNGuild v1.0 [52]. We used FUNGuild to analyze the high-throughput sequencing datasets from the treatments and put them into three trophic modes based on fungi feeding habits: symbiotroph, saprotroph, and pathotroph. Significant differences were tested in the relative abundance of taxonomic groups at all taxonomic levels (phylum, family and genus) using one-way ANOVA with Tukey’s HSD test. Test results with p < 0.05 were considered statistically significant.

Results

Alpha diversity

A total of 622,361 high-quality sequences were obtained for soil fungi across all samples. After clustering sequences at the 97% similarity threshold and removing singletons, we obtained 1853 operational taxonomic units (OTUs) for fungi. Overall, alpha diversity significantly differed among cultivars (p < 0.01) (Fig. 1 and Table S1). Ecoturf had the greatest alpha diversity estimated using Shannon, Simpson, and Pielou’s evenness indices, whereas UF_Peace and Florigraze had the least alpha diversity than other cultivars (p < 0.001) (Fig. 1A, B, C and Table S1). Latitude had the lowest alpha diversity estimated by Faith’s PD compared to other cultivars (p < 0.0001) (Fig. 1D and Table S1).

Fig. 1
figure 1

Shannon index (A), Simpson index (B) Pielou’s evenness index (C), and Phylogenetic diversity (D) of the fungal communities across seven rhizoma peanut cultivars in April. Colored dots represent individual data points. Different lowercase letters inicate significant differences (ANOVA, p < 0.05) among cultivars

Full size image

Comparison of the fungal OTUs shared among the seven different RP cultivars showed that the number of unique OTUs in Latitude, UF_Tito, UF_Peace, Florigraze, Arbrook, Ecoturf, and Arblick cultivars were 486, 477, 498, 472, 461, 489, and 500, respectively. The shared fungal OTUs among the seven RP cultivars were 117, which made up 24.21% of the total OTUs (Fig. 2).

Fig. 2
figure 2

Venn diagram of the number of operational taxonomic units (OTUs) of fungi obtained across seven different RP cultivars

Full size image

Beta diversity and fungal community composition

Variations in fungal community structures among RP cultivars were shown on the first two axes of the PCoA (Fig. 3). The first and second axis explained 30.54% and 13.59% of the variance in fungal communities, respectively (Fig. 3). Fungal community structure significantly differed across seven cultivars (R = 0.48; p = 0.0001).

Fig. 3
figure 3

Principal coordinate analysis (PCoA) of fungal β diversity across rhizoma peanut cultivars based on Bray-Curtis distance matrices

Full size image

At the phylum level, a total of eight dominated phyla of fungi were present across all cultivars including, Ascomycota, Basidiomycota, Mortierellomycota, Chytridiomycota, Rozellomycota, Olpidiomycota, Calcarisporiellomycota, Glomeromycota, Mucoromycota, Blastocladiomycota, and Entomophthoromycota. Of these phyla, Ascomycota (13.34%), Mortierellomycota (3.82%), and Basidiomycota (2.99%) were the dominant taxa (Fig. 4A). The relative abundance of the dominant fungal taxa was significantly different among RP cultivars (p < 0.05) (Fig. 4A and Table S2). The relative abundance of Ascomycota was significantly greater in Florigraze cultivar soils (11.36 ± 0.92%) than in the soils of Arblick (9.18 ± 0.93), Ecoturf (9.27 ± 0.85) and UF_Peace cultivars (10.00 ± 0.68) (p < 0.05) (Table S2). Ecoturf cultivar soils had greater relative abundance of Basidiomycota (3.92 ± 0.46) than the soils of Arblick (1.51 ± 0.34), Florigraze (1.51 ± 0.44), Latitude (2.04 ± 0.54), UF_Peace (2.24 ± 0.71), and UF_Tito cultivars (1.51 ± 0.67) (p < 0.05) (Table S2). The relative abundance of Mortierellomycota was significantly greater in the soils of UF_Peace cultivar (3.53 ± 1.0) than in the soils of Arblick (2.56 ± 0.78) and Florigraze cultivars (1.65 ± 0.54) (p < 0.05) (Table S2).

Fig. 4
figure 4

Relative abundance of the dominant fungal groups at the phylum level (A) and at the genera level fungi (B) across rhizoma peanut cultivars. The data was visualized via Circos software (http://circos.ca/). The thickness of each ribbon in represented the relative abundance of taxa in each phyla group. In the taxonomic OTU bubble plot, circle sizes represent the relative abundance of the group at the family level. In the heat map of genera, the color bar indicates the range of contribution of a genus across cultivars

Full size image

The relative abundance of the dominant genera was also significantly different across RP cultivars (p < 0.05) (Table S3). The relative abundance of Neocosmospora was greater in the soils of UF_Tito cultivar (48.96 ± 9.07) than in the soils of other cultivars (p < 0.0001) (Fig. 4B and Table S3). The relative abundance of Epicoccum (21.93 ± 3.28), Alternaria (23.55 ± 2.21), Stagonosporopsis (17.44 ± 1.52), Pseudopithomyces (27.94 ± 3.34), Neopyrenochaeta (21.5 ± 2.17), and Pleurotus (22.77 ± 4.20) was significantly greater in the soils of Arbrook cultivar than in the soils of other cultivars (p < 0.0001) (Fig. 4B and Table S3). Principal component analysis results indicate the distributions of the dominant genera of fungal communities among RP cultivars (Fig. 5). The first and second principal component explains 32.94% and 16.01% of the variation, respectively. The relative abundance of the major taxonomic groups varied across different cultivars (Fig. 5, Table S3). The major taxonomic groups in the soils of UF_Tito cultivar were Neocosmospora, Phaeosphaeria, and Microdochium, while Arxiella and Parastagonospora were mainly present in the soils of Florigraze cultivar. Epicoccum, Alternaria, Stagonosporopsis, and Pseudophiobolus were dominant in the soils of Arbrook cultivar. The major taxonomic groups in the soils of Arblick cultivar were Neocosmospora, Plectosphaerella, and Mortierella, while the soils of Latitude cultivar had mainly Neopyrenochaeta and Alternaria.

Fig. 5
figure 5

Principal component analysis of fungal (A and B) communities across RP cultivars Shapes with different colors represent rhizoma peanut cultivars (Variables) in fungi. We used taxonomic abundances data (OTUs defined at 97% sequence similarity) from 20 bacterial and fungal dominant genera samples (average abundance > 10 across all soil samples) as quantitative variables which were used to perform the PCA. The percentage of variability explained by two dimensions was given: 32.94% for the first axis and 16.01% for the second axis in fungi

Full size image

Co-occurrence networks

The co-occurrence patterns of the dominant fungal genera among the different RP cultivars were presented based on strong and significant taxonomic correlations. The number of positive correlations was greater than the negative correlations across seven RP cultivars (Fig. 6). There were significant differences in the co-occurrence network among RP cultivars (p < 0.05) (Fig. 6 and Table S4).

Fig. 6
figure 6

Co-occurrence network analysis of 20 dominant fungal genera among seven RP cultivars, (A) Latitude, (B) UF_Tito, (C) UF_Peace, (D) Florigraze, (E) Arbrook, (F) Ecoturf (G) Arblick, respectively. Each node was labelled at the genera level. A connection stand for a strong (Spearman’s p > 0.6) and significant (p < 0.05) correlation. The size of each node is in proportion to the relative abundance; the thickness of each connection between two nodes is in proportion to the value of spearman’s correlation co-efficient. Solid and dashed lines indicate positive and negative correlations, respectively

Full size image

The average connectivity was greater in the Florigraze and Ecoturf networks, with ≥ 6 node size ranging from 15 to 20 in two networks than in other cultivar networks (p < 0.05) (Table S4). The keystone taxa were different in different cultivars, with Alternaria, Neopyrenochaeta, and Neocosmospora detected in Latitude cultivar, Articulospora, Fusarium, and Phaeosphaeria in UF_Tito cultivar, Pseudophiobolus in UF_Peace cultivar, Neocosmospora and Stophoma in Florigraze cultivar, Fusarium, Knufia, and Microdocium in Arbrook cultivar, Knufia, Arxiella, Stagonosporsis, and Setophoma in Ecoturf cultivar, and Articulospora in Arblick cultivar (Fig. 6 and Table S4).

Functional characteristics

A total of 1,853 OTUs were assigned and annotated using the FUNGuild database. The relative abundance of functional groups including pathogenic, saprotrophic, endophytic, mycorrhizal, and parasitic fungi significantly differed among RP cultivars (p < 0.001) (Table S5). Soils of Ecoturf cultivar had the greatest relative abundance of mycorrhizal fungal group (5.10 ± 0.44) than other cultivars (p < 0.0001) (Fig. 7 and Table S5). The relative abundance of the endophytic (4.52 ± 0.56) and parasitic fungi (1.67 ± 0.30) was greatest in the soils of UF_Peace cultivar than others (Fig. 7 and Table S5). There were significantly lower proportions of mycorrhizal (0.39 ± 0.08), pathogenic (1.40 ± 0.21), and parasitic fungi (0.46 ± 0.09) but higher saprotrophic fungi (3.45 ± 0.35) in the soils of Arblick cultivars than other cultivars (Fig. 7 and Table S5) (p < 0.0001).

Fig. 7
figure 7

Predicted functional groups of fungal communities across cultivars. The functional groups of fungi were inferred using FUNGuild

Full size image

Discussion

Understanding the impact of legume forage on soil fungal communities is an important step toward identifying the overall benefits of incorporating legumes into grassland systems. Soil fungal communities play key roles in making plant nutrients available, facilitating soil nutrient cycling and promoting beneficial ecosystem services in many agricultural systems. Previous studies have shown that legume cultivars play a key role in shaping soil microbial communities [53, 54]. Our results demonstrated that RP cultivars were important determinants of soil fungal community structure and function. The findings showed that under the same soil type and conditions, different RP cultivars induced a shift in soil fungal communities. This is in line with previous reports showing that different cultivars of potato (Solanum tuberosum L.) and maize had significantly shifted soil fungal diversity and composition [55, 56]. For instance, Loit et al. [55] found that among twenty-one potato cultivars, Viviana, Solist, Glorieta, and Concordia significantly affect the overall fungal, pathogen, and saprotrophic community composition. Similarly, Li et al. [56] reported that cultivar Tiannuozao 60 (N) showed significant differences in fungal diversity compared with Junlong1217 (QZ) and Fujitai519 (ZL) cultivars.

Generally, patterns of fungal diversity and composition can be mediated by multiple factors including plant species and biomass, soil biotic and abiotic factors, and climatic factors [57, 58]. However, fine-scale effects of host plants on soil microbial community are often cultivar or genotype dependent. In this study, our results showed that the alpha and beta diversity of fungal communities significantly differed across RP cultivars. Ecoturf cultivar had the greatest alpha diversity than other RP cultivars. This difference might be due to the specific cultivar differences in the morphology and biochemistry of RP above and belowground components [40, 42]. In a concurrent study, Dubeux et al. [40] found out that RP cultivars differed in aboveground and belowground characteristics and BNF capacities. Ecoturf and Latitude had the greatest root + rhizome mass and N pool than Florigraze and some other cultivars. Belowground biomass serves as the main soil organic input, providing substrate for soil microorganisms, particularly soil fungi, to mediate multiple processes in soils [59].

Consistent with our study, Erhunmwunse et al. [60] identified Ascomycota, Mortierellomycota, and Basidiomycota as predominant phyla within RP systems in Florida. At the genus level, our study found that some fungal genera such as Neocosmospora and Epicoccum were dominant across all RP cultivars, suggesting their potential as key fungal indicators for RP irrespective of cultivar type. Neocosmospora, (previously known as Fusarium solani species complex), was the most abundant fungal genus, representing 21% of the fungal genera across all RP cultivars. This aligns with the findings of Erhunmwunse et al. [60] who, within the same soil type and location, reported Fusarium (Nectriaceae) as the primary fungal genus within Ecoturf and Florigraze RP soils. This shows the importance of this fungal genus within RP systems, warranting further investigation into their ecological roles and implications for RP management strategies.

The abundance of soil fungal genera known for their roles in nutrient cycling, plant defense, and soil health differed among RP cultivars. For example, Phaeosphaeria and Microdochium were prevalent in UF_Tito, while Arxiella and Parastagonospora were mainly present in the soils of Florigraze, and Plectosphaerella and Mortierella were dominant in the soils of Arblick cultivar. These fungal groups are responsible for nutrient cycling, decomposition of plant litter, production of antibiotics, and release of plant hormones like IAA, gibberellic acid (GA), and ACC deaminase [61, 62]. The impact of plant cultivars on soil fungal community composition is influenced by various factors including soil pH, plant root exudates, and agricultural practices. Previous studies have shown the differences in the above and belowground morphology and biochemistry of different RP cultivars [40, 42], which might have impacted soil fungal communities, in part, in our study. Studies describing the quality and quantity of root exudates specific to RP are noticeably lacking, even though differences in root exudate quality and quantity have been shown to strongly influence fungal taxa among plant cultivars [63]. Such information may provide important context for understanding the differences in soil microbial communities under RP systems.

Positive and negative edges in cooccurrence network depict interactions and competition among soil microbial communities. These interactions are crucial for ecological activities and community assemblage in any system [64]. Positive interactions play a crucial role for maintaining species diversity and ecosystem functioning [65]. In our study, co-occurrence network of dominant fungal genera among the different RP cultivars showed more positive interactions (indicating mutualism) in the forage system. The positive interactions that exist between fungi-fungi may be due to their mutualistic or commensal ecological interactions [66]. Compared to other RP cultivars, soils of Florigraze and Ecoturf RP had greater number of positive interactions. Generally, more positive interactions in network imply higher degree of cooperation and symbiotic relationships among microbial taxa. More symbiotic interactions between microbial taxa are beneficial for diversity maintenance and soil nutrient acquisition [67], which might have a positive effect on plant growth and health. In contrast, more negative interactions were observed in Latitude soil, which may be due to substrate limitation [68], and consequently leading to competition among fungal taxa in this cultivar.

Soil fungal communities can be grouped into different functional groups based on their roles in agricultural systems [69]. Symbiotrophic fungi are beneficial as they form mutualistic relationships with plants to assess plant nutrients and protect plants from diseases [70]. On the other hand, parasitic fungi can have a negative impact on plant growth and development by causing diseases such as root rot, leaf spot, powdery mildew, and rust, and by redirecting plant nutrients and resources for their growth [71, 72]. Overall, the results of FUNGuild, a functional analysis of fungal communities, revealed that the relative abundance of endophytes, mycorrhizal, and saprotrophs were significantly greater among RP cultivars compared to parasites and pathogens (Fig. 6 and Table S5). This suggests that the presence of RP stimulated the relative abundance of beneficial soil fungal communities. The implication of this is that the incorporation of RP into any grassland systems may promote soil fungal community shifts that may benefit plant growth and soil nutrient cycling. Understanding how fungal communities vary across RP cultivars can provide insights into plant-microbe interactions, disease resistance, and overall crop health, with implications for healthy and sustainable pasture management strategies.

Conclusion

This study showed that RP cultivars significantly affected fungal diversity, composition, taxonomic interactions and functions. We found that fungal alpha diversity estimated using Shannon, Simpson, and Pielou’s evenness was significantly greater in Ecoturf. Moreover, the fungal phyla Ascomycota, Mortierellomycota and Basidiomycota​​​​​​​ were found as keystone species and were dominant in Florigraze, UF_Peace, and Ecoturf, respectively. The relative abundance of Neocosmospora was greater in the soil of UF_Tito. In general, RP cultivars had greater relative abundances of endophytes, mycorrhizal, and saprotrophs than of parasites and pathogens. However, compared to other RP cultivars, the soils of UF_Peace, Ecoturf, and Arblick had greater abundances of saprotrophs, endophytes, and mycorrhizal functional groups. Our findings provide evidence of crop cultivar’s effect in shaping fine-scale microbial patterns in legume-based forage systems. We highlight an importance of crop-associated soil microbiome in agroecosystems and suggesting that interacting different RP cultivars with beneficial soil fungi could be a new path for improving crop productivity, soil nutrient availability, and minimizing farm input costs through applying fungal biota as biofertilizer resource for sustainable agroecosystems.

Data availability

The sequenced raw dataset generated in this study have been submitted to the National Center for Biotechnology Information (NCBI) with BioProject ID: PRJNA1099792,

(https://www.ncbi.nlm.nih.gov/sra/PRJNA1099792).

References

  1. Rehman A, Farooq M, Lee DJ, Siddique KHM. Sustainable agricultural practices for food security and ecosystem services. Environ Sci Pollut Res. 2022;29:84076–95.

    Article  Google Scholar 

  2. Xiong C, Lu Y. Microbiomes in agroecosystem: diversity, function and assembly mechanisms. Environ Microbiol Rep. 2022;14:833–49.

    Article  CAS  PubMed  Google Scholar 

  3. Singh SK, Wu X, Shao C, Zhang H. Microbial enhancement of plant nutrient acquisition. Stress Biology. 2022;2:1–14.

    Article  Google Scholar 

  4. Kaviya N, Upadhayay VK, Singh J, Khan A, Panwar M, Singh AV. Role of Microorganisms in Soil Genesis and Functions. In: Varma, A., Choudhary, D, editors Mycorrhizosphere and Pedogenesis. Springer. 2019. https://doi.org/10.1007/978-981-13-6480-8-2

  5. Molefe RR, Amoo AE, Babalola OO. Communication between plant roots and the soil microbiome; involvement in plant growth and development. Symbiosis. 2023;90:231–9.

    Article  Google Scholar 

  6. Asad NI, Wang XB, Dozois J, Azarbad H, Constant P, Yergeau E. Early season soil microbiome best predicts wheat grain quality. FEMS Microbiol Ecol. 2023;99:fiac144.

    Article  CAS  Google Scholar 

  7. Kaur R, Saxena S. Penicillium Citrinum, a Drought-Tolerant Endophytic Fungus isolated from wheat (Triticum aestivum L.) leaves with Plant Growth-promoting abilities. Curr Microbiol. 2023;80:184.

    Article  CAS  PubMed  Google Scholar 

  8. López AC, Giorgio EM, Vereschuk ML. Ilex paraguariensis hosts Root-Trichoderma spp. with plant-growth-promoting traits: characterization as Biological Control agents and Biofertilizers. Curr Microbiol. 2023;80:120.

    Article  PubMed  Google Scholar 

  9. Wang B, Xiao Q, Geng X, Lin K, Li Z, Li Y, et al. Arbuscular mycorrhizal fungi alter rhizosphere bacterial diversity, network stability and function of lettuce in barren soil. Sci Hortic. 2024;323:112533.

    Article  CAS  Google Scholar 

  10. Schmitz L, Yan Z, Schneijderberg M, de Roij M, Pijnenburg R, Zheng Q, et al. Synthetic bacterial community derived from a desert rhizosphere confers salt stress resilience to tomato in the presence of a soil microbiome. ISME J. 2022;16:1907–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Guo S, Tao C, Jousset A, Xiong W, Wang Z, Shen Z, et al. Trophic interactions between predatory protists and pathogen-suppressive bacteria impact plant health. ISME J. 2022;16:1932–43.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Haskett TL, Tkacz A, Poole PS. Engineering rhizobacteria for sustainable agriculture. ISME J. 2021;15:949–64.

    Article  PubMed  Google Scholar 

  13. D’Hondt K, Kostic T, McDowell R, Eudes F, Singh BK, Sarkar S, Sessitsch A. Microbiome innovations for a sustainable future. Nat Microbiol. 2021;6:138–42.

    Article  PubMed  Google Scholar 

  14. Zak DR, Argiroff WA, Freedman ZB, Upchurch RA, Entwistle EM, Romanowicz KJ. Anthropogenic N deposition, fungal gene expression, and an increasing soil carbon sink in the Northern Hemisphere. Ecology. 2019;100:e02804.

    Article  PubMed  Google Scholar 

  15. Bastian F, Bouziri L, Nicolardot B, Ranjard L. Impact of wheat straw decomposition on successional patterns of soil microbial community structure. Soil Biol Biochem. 2009;41:262–75.

    Article  CAS  Google Scholar 

  16. Baldrian P, Kolařík M, Štursová M, Kopecký J, Valášková V, Větrovský T, et al. Active and total microbial communities in forest soil are largely different and highly stratified during decomposition. ISME J. 2012;6:248–58.

    Article  CAS  PubMed  Google Scholar 

  17. Nilsson RH, Anslan S, Bahram M, Wurzbacher C, Baldrian P, Tedersoo L. Mycobiome diversity: high-throughput sequencing and identification of fungi. Nat Rev Microbiol. 2019;17:95–109.

    Article  CAS  PubMed  Google Scholar 

  18. Tedersoo L, Bahram M, Zobel M. How mycorrhizal associations drive plant population and community biology. Science. 2020;367:eaba1223.

    Article  CAS  PubMed  Google Scholar 

  19. Tarin MWK, Fan L, Xie D, Tayyab M, Rong J, Chen L, et al. Response of soil fungal diversity and community composition to varying levels of bamboo biochar in red soils. Microorganisms. 2021;9:1385.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Silvana VM, Carlos FJ, Lucía AC, Natalia A, Marta C. Colonization dynamics of arbuscular mycorrhizal fungi (AMF) in Ilex paraguariensis crops: seasonality and influence of management practices. J King Saud Uni Sci. 2020;32:183–8.

    Article  Google Scholar 

  21. Abdelaziz ME, Kim D, Ali S, Fedoroff NV, Al-Babili S. The endophytic fungus piriformospora indica enhances Arabidopsis thaliana growth and modulates Na+/K + homeostasis under salt stress conditions. Plant Sci. 2017;263:107–15.

    Article  CAS  PubMed  Google Scholar 

  22. Sun X, Wang N, Li P, Jiang Z, Liu X, Wang M, et al. Endophytic fungus Falciphora Oryzae promotes lateral root growth by producing indole derivatives after sensing plant signals. Plant Cell Environ. 2020;43:358–73.

    Article  CAS  PubMed  Google Scholar 

  23. Kannadan S, Rudgers JA. Endophyte symbiosis benefits a rare grass under low water availability. Funct Ecol. 2008;22:706–13.

    Article  Google Scholar 

  24. Chapelle E, Mendes R, Bakker P. Fungal invasion of the rhizosphere microbiome. ISME J. 2016;10:265–8.

    Article  CAS  PubMed  Google Scholar 

  25. Frąc M, Hannula SE, Bełka M, Jędryczka M. Fungal biodiversity and their role in Soil Health. Front Microbiol. 2018;13:707.

    Article  Google Scholar 

  26. Fu F, Li Y, Zhang B, Zhu S, Guo L, Li J, et al. Differences in soil microbial community structure and assembly processes under warming and cooling conditions in an alpine forest ecosystem. Sci Total Environ. 2024;907:167809.

    Article  CAS  PubMed  Google Scholar 

  27. Erhunmwunse AS, Mackowiak CL, Blount ARS, Dubeux JCB, Ogram A, Liao HL. Short-term perennial peanut integration into bahiagrass system influence on soil microbial-mediated nitrogen cycling activities and microbial co-occurrence networks. Eur J Soil Biol. 2023;119:103566.

    Article  CAS  Google Scholar 

  28. Veach AM, Morris R, Yip DZ, Yang ZK, Engle NL, Cregger MA, et al. Rhizosphere microbiomes diverge among Populus trichocarpa plant-host genotypes and chemotypes, but it depends on soil origin. Microbiome. 2019;7:1–15.

    Article  Google Scholar 

  29. Schmidt R, Ulanova D, Wick LY, Bode HB, Garbeva P. Microbe-driven chemical ecology: past, present and future. ISME J. 2019;13:2656–63.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Semchenko M, Xue P, Leigh T. Functional diversity and identity of plant genotypes regulate rhizodeposition and soil microbial activity. New Phytol. 2021;232:776–87.

    Article  CAS  PubMed  Google Scholar 

  31. Gil-Martínez M, López-García Á, Domínguez MT, Kjøller R, Navarro-Fernández CM, Rosendahl S, et al. Soil fungal diversity and functionality are driven by plant species used in phytoremediation. Soil Biol Biochem. 2021;153:108102.

    Article  Google Scholar 

  32. Liu S, Garcia-Palacios P, Tedersoo L, Guirado E, van der Heijden MG, Wagg C, et al. Phylotype diversity within soil fungal functional groups drives ecosystem stability. Nat Ecol Evol. 2022;6:900–9.

    Article  PubMed  Google Scholar 

  33. Germida J, Siciliano S. Taxonomic diversity of bacteria associated with the roots of modern, recent and ancient wheat cultivars. Biol Fertil Soils. 2001;33:410–5.

    Article  Google Scholar 

  34. Feng Y, Yu Y, Tang H, Zu Q, Zhu J, Lin X. The contrasting responses of soil microorganisms in two rice cultivars to elevated ground-level ozone. Environ Pollut. 2015;197:195–202.

    Article  CAS  PubMed  Google Scholar 

  35. Schlemper TR, van Veen JA, Kuramae EE. Co-variation of bacterial and fungal communities in different sorghum cultivars and growth stages is soil dependent. Microb Ecol. 2018;76:205–14.

    Article  PubMed  Google Scholar 

  36. Yang C, Hamel C, Gan Y, Vujanovic V. Pyrosequencing reveals how pulses influence rhizobacterial communities with feedback on wheat growth in the semiarid Prairie. Plant Soil. 2013;367:493–505.

    Article  CAS  Google Scholar 

  37. Wang XB, Hsu CM, Dubeux JCB Jr, Mackowiak C, Blount A, Han XG, et al. Effects of rhizoma peanut cultivars (Arachis glabrata Benth.) On the soil bacterial diversity and predicted function in nitrogen fixation. Ecol Evol. 2019;9:12676–87.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Daraz U, Erhunmwunse AS, Dubeux JCB, Mackowiak C, Guerra VA, Hsu CM, et al. Soil bacterial communities across seven Rhizoma Peanut cultivars (Arachis glabrata Benth.) Respond to Seasonal Variation. Microb Ecol. 2023;86:2703–15.

    Article  CAS  PubMed  Google Scholar 

  39. Ortega -SJA, Sollenberger LE, Quesenberry KH, Cornell JA, Jones CS Jr. Productivity and persistence of rhizoma peanut pastures under different grazing managements. Agron J. 1992;84:799–804.

    Article  Google Scholar 

  40. Dubeux JCB Jr, Blount ARS, Mackowiak C, Santos ERS, Pereira NJDU, Riveros L, et al. Biological N2 fixation, belowground responses, and forage potential of rhizoma peanut cultivars. Crop Sci. 2017;57:1027–38.

    Article  Google Scholar 

  41. Garay AH, Sollenberger LE, Staples CR, Pedreira CGS. Florigraze’ and ‘Arbrook’ Rhizoma Peanut as pasture for growing Holstein heifers. Crop Sci. 2004;44:1355–60.

    Article  Google Scholar 

  42. Santos ERS, Dubeux JCB Jr, Sollenberger LE, Blount ARS, Mackowiak C, DiLorenzo N, et al. Herbage responses and biological N2 fixation of bahiagrass and rhizoma peanut monocultures compared with their binary mixtures. Crop Sci. 2018;58:2149–63.

    Article  CAS  Google Scholar 

  43. Santos ER, Dubeux JCB, Sollenberger LE, Siqueira B, Vancleef FOS, Jaramillo D, et al. Composition and decomposition of rhizoma peanut (Arachis glabrata Benth.) Belowground biomass. Sci Rep. 2022;12:9967.

    Article  Google Scholar 

  44. Shepard EM, Sollenberger LE, Kohmann MM, da Silva LS, Harling JF Jr, Dubeux JC Jr, et al. Establishing rhizoma peanut-bahiagrass mixtures. Agrosyst Geosci Environ. 2022;5:e20285.

    Article  CAS  Google Scholar 

  45. Soil SS. Keys to Soil Taxonomy. 8th ed. Washington, DC: USDA-Natural Resources Conservation Service; 1999.

    Google Scholar 

  46. Chen KH, Liao HL, Arnold AE, Bonito G, Lutzoni F. RNA-based analyses reveal fungal communities structured by a senescence gradient in the moss Dicranum scoparium and the presence of putative multi-trophic fungi. New Phytol. 2018;218:15971611.

    Article  Google Scholar 

  47. Lundberg DS, Yourstone S, Mieczkowski P, Jones CD, Dangl JL. Practical innovations for high-throughput amplicon sequencing. Nat Methods. 2013;10:999–1002.

    Article  CAS  PubMed  Google Scholar 

  48. Feng K, Zhang Z, Cai W, Liu W, Xu M, Yin H, et al. Biodiversity and species competition regulate the resilience of microbial biofilm community. Mol Ecol. 2017;26:6170–82.

    Article  PubMed  Google Scholar 

  49. Magoč T, Salzberg SL. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics. 2011;27:2957–63.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Kong Y, Btrim. A fast, lightweight adapter and quality trimming program for next-generation sequencing technologies. Genomics. 2011;98:152–3.

    Article  CAS  PubMed  Google Scholar 

  51. Edgar RC. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat Methods. 2013;10:996–8.

    Article  CAS  PubMed  Google Scholar 

  52. Nguyen NH, Song ZW, Bates ST, Branco S, Tedersoo L, Menke J, et al. FUNGuild: an open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecol. 2016;20:241–8.

    Article  Google Scholar 

  53. Zhou Y, Zhu H, Fu S, Yao Q. Variation in Soil Microbial Community structure Associated with different legume species is greater than that Associated with different grass species. Front Microbiol. 2017;8:1007.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Brown SP, Grillo MA, Podowski JC, Heath KD. Soil origin and plant genotype structure distinct microbiome compartments in the model legume Medicago truncatula. Microbiome. 2020;28:139.

    Article  Google Scholar 

  55. Loit K, Soonvald L, Astover A, Runno-Paurson E, Öpik M, Tedersoo L. Temporal and Cultivar-Specific effects on Potato Root and Soil Fungal Diversity. Agronomy. 2020;10:1535.

    Article  CAS  Google Scholar 

  56. Li Y, Qu Z, Xu W, Chen W, Hu Y, Wang Z. Maize (Zea mays L.) genotypes induce the changes of rhizosphere microbial communities. Arch Microbiol. 2022;204(6):321.

    Article  CAS  PubMed  Google Scholar 

  57. Větrovský T, Kohout P, Kopecký M, Machac A, Man M, Bahnmann BD, et al. A meta-analysis of global fungal distribution reveals climate-driven patterns. Nat Commun. 2019;10:5142.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Chauhan S, Ganure P, Dandin CJ. Impact of abiotic conditions on fungal diversity and comparative analysis of soil quality of two distinct locations. AGBIR. 2023;39:457–63.

    CAS  Google Scholar 

  59. Eisenhauer N, Lanoue A, Strecker T, Scheu S, Steinauer K, Thakur MP, et al. Root biomass and exudates link plant diversity with soil bacterial and fungal biomass. Sci Rep. 2017;7:44641.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Erhunmwunse AS, Queiroz LMD, Zhang K, Mackowiak CL, Blount AR, Dubeux JC Jr, et al. Changes in soil microbial diversity and community composition across bahiagrass and rhizoma peanut pastures. Biol Fertil Soils. 2023;59:285–300.

    Article  CAS  Google Scholar 

  61. Klomchit A, Calderin JD, Jaidee W, Watla-Iad K, Brooks S. Napthoquinones from Neocosmospora sp. Antibiotic activity against Acidovorax citrulli, the Causative Agent of Bacterial Fruit Blotch in Watermelon and Melon. J Fungi. 2021;7:370.

    Article  CAS  Google Scholar 

  62. LeBlanc N, Kinkel L, Kistler HC. Plant diversity and plant identity influence fusarium communities in soil. Mycologia. 2017;109:128–39.

    Article  PubMed  Google Scholar 

  63. Fan D, Subramanian S, Smith DL. Plant endophytes promote growth and alleviate salt stress in Arabidopsis thaliana. Sci Rep. 2020;10:1–18.

    Article  Google Scholar 

  64. Williams A, Langridge H, Straathof AL, Muhamad AH, Hollywood KA, Goodacre R, et al. Root functional traits explain root exudation rate and composition across a range of grassland species. J Ecol. 2021;00:1–13.

    Google Scholar 

  65. Trivedi P, Leach JE, Tringe SG, Sa T, Singh BK. Plant-microbiome interactions: from community assembly to plant health. Nat Rev Microbiol. 2020;18:607–21.

    Article  CAS  PubMed  Google Scholar 

  66. Wright AJ, Wardle DA, Callaway R, Gaxiola A. The overlooked role of Facilitation in Biodiversity experiments. Trends Ecol Evol. 2017;32:383–90.

    Article  PubMed  Google Scholar 

  67. Zhang B, Zhang J, Liu Y, Shi P, Wei G. Co-occurrence patterns of soybean rhizosphere microbiome at a continental scale. Soil Biol Biochem. 2018;118:178–86.

    Article  CAS  Google Scholar 

  68. Kowal J, Pressel S, Duckett JG, Bidartondo MI, Field KJ. From rhizoids to roots? Experimental evidence of mutualism between liver-worts and ascomycete fungi. Ann Bot. 2018;121:221–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Faust K, Raes J. Microbial interactions: from networks to models. Nat Rev Microbiol. 2012;10:538–50.

    Article  CAS  PubMed  Google Scholar 

  70. Liu S, García-Palacios P, Tedersoo L, Guirado E, van der Heijden MGA, Wagg C, et al. Phylotype diversity within soil fungal functional groups drives ecosystem stability. Nat Ecol Evol. 2022;6:900–9.

    Article  PubMed  Google Scholar 

  71. Igiehon NO, Babalola OO. Biofertilizers and sustainable agriculture: exploring arbuscular mycorrhizal fungi. Appl Microbiol Biot. 2017;101:4871–81.

    Article  CAS  Google Scholar 

  72. Anthony MA, Frey SD, Stinson KA. Fungal community homogenization, shift in dominant trophic guild, and appearance of novel taxa with biotic invasion. Ecosphere. 2017;8:1–17.

    Article  Google Scholar 

Download references

Funding

This work was financially supported by the General Program of the National Natural Science Foundation of China (32271716); the Agriculture; the Soil, Water, and Ecosystem Sciences Graduate School Matching Funding to Adesuwa Erhunmwunse; the National Institute of Food and Agriculture; U.S. Department of Agriculture (2021-38640-34724) through the Southern Sustainable Agriculture Research and Education program under subaward number (GS22-268) to Hui-Ling Liao and Adesuwa Erhunmwunse; the USDA-NIFA grant (2019-67013-29107) to Hui-Ling Liao and Food Research Initiative Competitive of the USDA National Institute of Food and Agriculture (2019-67013-29107), and the National Key Research and Development Program of China (2021YFD1300504), the Key Projects of the Natural Science of Foundation of Gansu Province (23JRRA1023), and the Starting Research Fund for the Introduction of Talent of Lanzhou University (561120205).

Author information

Authors and Affiliations

  1. State Key Laboratory of Herbage Improvement and Grassland Agro-Ecosystems, College of Pastoral, Agriculture Science and Technology, Center for Grassland Microbiome, Lanzhou University, Lanzhou, China

    Umar Daraz & Xiao-Bo Wang

  2. North Florida Research and Education Center, University of Florida, Quincy, FL, USA

    Adesuwa S. Erhunmwunse, Cheryl Mackowiak & Hui-Ling Liao

  3. North Florida Research and Education Center, University of Florida, Marianna, FL, USA

    José C. B. Dubeux Jr.

Authors
  1. Umar Daraz
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Adesuwa S. Erhunmwunse
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. José C. B. Dubeux Jr.
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Cheryl Mackowiak
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hui-Ling Liao
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Xiao-Bo Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

H.-L.L. and J.C.B.D. designed the experiments, X.-B.W. performed the experiment, U.D. analyzed the data and wrote the paper with the reviews and revisions of X.-B.W., A.-S.E., H.-L.L and J.C.B.D. All coauthors contributed to manuscript editing.

Corresponding author

Correspondence to Xiao-Bo Wang.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Conflict of interest

The authors declare no conflict of interest.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Daraz, U., Erhunmwunse, A.S., Dubeux, J.C.B. et al. Soil fungal community structure and function response to rhizoma perennial peanut cultivars. BMC Plant Biol 24, 582 (2024). https://doi.org/10.1186/s12870-024-05209-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12870-024-05209-y

Keywords

BMC Plant Biology

ISSN: 1471-2229

Contact us