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Review

Emerging Function of Ecotype-Specific Splicing in the Recruitment of Commensal Microbiome

by
Yue-Han Li
1,2,3,
Yuan-You Yang
1,
Zhi-Gang Wang
2,3,* and
Zhuo Chen
1,*
1
State Key Laboratory Breeding Base of Green Pesticide and Agricultural Bioengineering, Key Laboratory of Green Pesticide and Agricultural Bioengineering, Ministry of Education, Research and Development Center for Fine Chemicals, Guizhou University, Guiyang 550025, China
2
School of Life Science and Agriculture Forestry, Qiqihar University, Qiqihar 161006, China
3
Heilongjiang Provincial Technology Innovation Center of Agromicrobial Preparation Industrialization, Qiqihar 161006, China
*
Authors to whom correspondence should be addressed.
Int. J. Mol. Sci. 2022, 23(9), 4860; https://doi.org/10.3390/ijms23094860
Submission received: 19 March 2022 / Revised: 15 April 2022 / Accepted: 25 April 2022 / Published: 27 April 2022
(This article belongs to the Special Issue Alternative Splicing: From Abiotic Stress Tolerance to Evolutionary Genomics)
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Abstract

:
In recent years, host–microbiome interactions in both animals and plants has emerged as a novel research area for studying the relationship between host organisms and their commensal microbial communities. The fitness advantages of this mutualistic interaction can be found in both plant hosts and their associated microbiome, however, the driving forces mediating this beneficial interaction are poorly understood. Alternative splicing (AS), a pivotal post-transcriptional mechanism, has been demonstrated to play a crucial role in plant development and stress responses among diverse plant ecotypes. This natural variation of plants also has an impact on their commensal microbiome. In this article, we review the current progress of plant natural variation on their microbiome community, and discuss knowledge gaps between AS regulation of plants in response to their intimately related microbiota. Through the impact of this article, an avenue could be established to study the biological mechanism of naturally varied splicing isoforms on plant-associated microbiome assembly.

1. Introduction

The interaction between host plants and their commensal microbiome has become a research hotspot in recent years. As sessile organisms, plants have evolved a series of mechanisms to cope with changing environments [1,2]. In fact, the interaction between plant immunity and the plant microbiota is bidirectional, with plants, microbiota, and the environment forming a complex system and working together to coordinate the plant microbiota. An increasing number of researchers have suggested that those plant-associated microorganisms can be studied together with their host plants as one combined holobiont in the field [3]. Benefits from adequate mutualistic interactions will improve plant growth and soil productivity, inhibit pathogen propagation, enhance plant tolerance to adverse environments, and accelerate nutrient recycling in fields [4], ultimately providing an effective way for agriculture to increase crop yield in a sustainable manner [5].
Influencing factors that affect this mutualistic interaction have been extensively reported, including internal and external factors in both plants and microorganisms [6]. Specifically, there is a growing body of evidence that plant genetics information is crucial in response to microbial colonization, extending the knowledge of plant biology to other disciplines such as microbiology and ecology [7]. Studies using different plant ecotypes or cultivars have been conducted to unravel the underlying mechanism of this interaction [3]. For example, plants decode genetic information to determine the composition of root exudates [8], root architecture [9], or ingredients for the microbiome assembly to respond at its surface or rhizosphere. Current reports aim to understand the diversity and dynamics of indigenous microbial communities coupled with the identification of core microbiota or keystone species [3]. However, most of the studies are descriptive, paying little attention to the underlying mechanism to mediate this interaction [1,3].
In addition, plants can translate their genetic differences by adjusting the repertoire of proteins they express in response to surrounding abiotic and biotic factors. One post-transcriptional regulatory mechanism, notably alternative splicing (AS), has emerged as a pivotal process for plants, to adapt to changing environments by significantly increasing proteome diversity or fine-tuning transcript abundance [10]. To date, approximately 95% of human intron-containing genes undergo AS regulation and up to 35% of human diseases are related to mutations that can affect splicing [11,12]. Importantly, single nucleotide polymorphisms (SNPs) observed at a splice site will affect the expression of certain transcript isoforms, thus resulting in phenotypic diversity in research on human diseases [13]. In plants, 60–83% of intron-containing genes undergo AS [14]. Natural variation of AS, identified as splicing quantitative trait loci (functions of sQTLs) [15], and its contribution to plant traits has been observed by using population-level transcriptome analyses, providing evidence for linking genetic variants to plant trait variation [16,17,18]. However, which function of sQTLs contribute to plant–microbe interactions is poorly understood. To this end, we first introduce the current progress of these research questions in this review article. Then, we discuss the possible mechanism to connecting diverse plant ecotype–phenotype linkages, splicing isoforms, and commensal microbiomes. In addition, we discuss further investigation using modern high-throughput omics technology to identify target plant alleles that can modulate interactions between host plants and their intimately related microbiota.

2. Ecotype-Specific Microbial Community in Plants

2.1. Host Maintanence of Commensal Microbiome

The microbial community is a crucial environmental component, as approximately 10 billion microorganisms are present in every gram of soil [19]. The interaction between plants and microorganism communities is a vital driver of ecosystem functioning [20] and can affect the maintenance of agricultural ecosystems [21]. These microorganisms will form complex co-associations with plants and have necessary roles in promoting the productivity and health of the plant type in natural environments. In particular, plant-associated microbiota and plants from a ‘holobiont’, and evolutionary selection among microbes and plants contributes to the steadiness of an ecosystem [22,23]. Host-associated microbial communities have a crucial role in shaping the health and fitness of plants [24]. Diverse microbial communities colonize plant surfaces and tissues, and beneficial microbial groups provide plants with a large array of life supporting functions such as resilience to organic phenomena and abiotic stresses, growth promotion, and nutrient acquisition [25,26]. It is well known that many beneficial microorganisms in the soil after planting plants will enrich the roots of the plants [27]. Plants and microorganisms work together as an important part of plant growth and illustrate the importance of plant hosts; however, there is a need to better understand the governing plant–microorganism interactions at the community level and explore their potential agricultural application value. It was found that the composition of microbial communities among different plants is diverse in bulk soils under different vegetation covers [28]. Furthermore, the field bacterial community structure in the bulk and inter-root soils with different plant diversity treatments was examined, and significant differences in bacterial communities were observed in both bulk and inter-root soils [29]. In recent years, culture-independent high-throughput sequencing has greatly expanded the repertoire of microorganisms known to reside in and on plants [30,31,32]. Plant growth-promoting rhizobacteria (PGPR) are gradually attracting public research attention. If we visualize an ideal agricultural picture, crops produced should be equipped with disease resistance, salt tolerance, drought tolerance, serious metal stress tolerance, and higher nutritional value. One way is to use soil microorganisms (bacteria, fungi, algae, etc.) to achieve this goal [33]. Soil microbial populations are immersed in a framework of interactions known to have an effect on plant fitness and soil quality. Cooperative microbial activities may be exploited as a low-input biotechnology to assist sustainable, environmentally friendly, agro-technological practices. Among these potential soil microorganisms, PGPR bacteria are the most promising research targets. PGPR could also be used to enhance plant health and promote the plant growth rate without environmental contamination [34]. There have also been deeper developments in recent years regarding the separation of PGPR, which also has a positive effect on plants. The most remarkably studied bacteria in relation to biocontrol are members of the genera Pseudomonas spp., Bacillus spp., Azospirillum spp., and Streptomyce spp. [35,36,37]. For example, Bacillus thuringiensis is renowned as a good bioinsecticidal bacterium, and acyl homoserine lactone lactonase created by B. thuringiensis can open the lactone ring of N-acyl homoserine lactone, a signature molecule within the bacterial quorum-sensing system [38]. The capacity of microorganisms to rescue plants’ capacity of stress has been recently studied [39,40,41]. For example, wheat microbiome bacteria can relieve plant stress, and a compound secreted by the bacteria (phenazine-1-carboxamide) directly affects the activity of fungal protein FgGcn5, a histone acetyltransferase. This results in deregulation of simple protein acetylation at H2BK11, H3K14, H3K18, and H3K27 in F. graminearum, as suppression of fungal growth, virulence, and mycotoxin biogenesis [41]. Therefore, the associated degree of antagonistic bacteria can inhibit the growth and virulence of a plant pathogenic fungus by manipulating fungi simple protein modification. Strains of Chitinophaga spp., Chryseobacterium spp., Flavobacterium spp., Microbacterium spp., Pseudomonas spp., Sphingomonas spp., Stenotrophomonas spp., and Xanthomonas spp. are typically found to complement plant responses to totally different pathogen/pest attacks. However, the benefits of microorganisms on plants may occur via two modes. For example, a change in the structure of the inter-root microbiome would give the common tomato the property of resistance to wilt. The model dicot plant Arabidopsis thaliana specifically promotes three bacterial species within the rhizosphere upon foliar defence activation by the mildew pathogen Hyaloperonospora arabidopsidis [42]. 2,4-diacetylphloroglucinol (Phl) produced by Pseudomonas on roots of wheat grown in a soil suppressive to take-all of wheat. Phl-producing fluorescent Pseudomonas are key elements of the natural biological control that operates in take-all-suppressive soils [43]. Recruitment of microbes, via plant hosts, could have evolved to prime plant defence communication pathways and inhibit the expansion and virulence of pathogens that consequently ameliorate plant stresses [44,45,46]. This suggests that plant hosts largely determine the changes in plant microbial communities. Therefore, we believe that plants depend on microorganisms to bring them positive effects, and they have unique ways to ‘communicate’. These works need to be explored continuously and need more research to explore important research implications.

2.2. Function of Microbiome in Plant Defense and Immune Systems, Corollary of the Relationship between Plant Active and Passive Immunity

The plant microbiome is not static: its structure and therefore the provided host functions in response to stresses and environmental stimuli [47,48,49,50]. Recent studies suggest that the changes within the microbiome are not merely passive responses of plants, but rather a consequence of millions of years of coevolution [39,40,41,45,51].
Emerging evidence has indicated that plant-associated microbiomes are closely related to plant health [52] and the helpful features of plant-associated microbes will boost the immune responses in plants against biotic/abiotic environmental constraints [53,54]. In high abundance, beneficial microbes directly inhibit pathogens by producing antimicrobial compounds. However, beneficial microbes can also inhibit pathogens indirectly by stimulating the immune system of plants, a development referred to as induced systemic resistance (ISR) [55]. Two forms of systemic immunity triggered by plant–microbe interactions, systemic acquired resistance (SAR) and ISR, are classified due to differences in the site of induction and the manner in which the microbes are induced. Both SAR and ISR influence growth regulator crosstalk towards enhanced defence against pathogens, which affects the composition of the plant microbiome. ISR inducers include PGPR, such as Pseudomonas spp., Bacillus spp., streptomyces spp., and plant growth-promoting fungi (PGPF), as well as Trichoderma spp. and Serendipita indica (formerly Piriformospora indica) [56,57,58,59]. In plants, interaction with beneficial microbes of the microbiome will additionally result in the activation of the plant’s system, not least in the form of ISR. Reciprocally, the composition of the plant microbiome is influenced by plant immunity, which we call active immunity. This appears to be only determined by two main mechanisms thus far: direct microbe–microbe interactions and stimulation or priming of the plant immune system. For instance, a molecule secreted by the Pseudomonas piscium ZJU60 strain, which was isolated from infected wheat head, antagonizes the flora Fusarium graminearum by inhibiting its simple protein acetyltransferases [41]. The ability to antagonize other microbes, together with pathogens, may be a common attribute in bacteria isolated from the Arabidopsis leaf microbiome [60]. These studies all suggest that plant microbiota are a rich source of pathogen antagonists that act through direct inhibition [61].
Plant–pathogen interactions are mediated by the interplay of multifaceted processes, which are expedited by pathogen- and plant-oriented molecules [62,63]. Pathogens and commensal microbes that survive competition with different soil and plant-associated microbes then encounter the plant innate system, principally microbe-associated molecular patterns (MAMPs), triggered immunity (MTI), and effector triggered immunity (ETI), two layers of molecular defence referred to within the advanced zigzag defence model [64]. PTI and ETI both depend on SA, and each induce a systemic, SA-dependent defence response that is known as systemic acquired resistance (SAR) [65,66,67]. SAR may be a durable style of resistance against a broad spectrum of (hemi-)biotrophic pathogens [68].
The vital next step, currently, is to check these molecular mechanisms and unravel how commensal microbes move with plant immunity under various plant conditions. Such interactions between the system and microbiome are likely critical for plant defence against diverse stresses and influence host microbiota associations. Evidently, internal secretion signalling pathways of jasmonic acid (JA), salicylic acid (SA), and ethylene (ET) and their interactions are crucial in regulating plant defences and their associated microbiota [69,70]. Biotrophic and hemi-biotrophic pathogens that depend upon living host tissues and cells are fended off chiefly through SA-dependent immune mechanisms. Other findings show that the diversity of the endophytic microorganism community in Arabidopsis leaves is in response to the associated degree of activation of the SA signalling pathway [70] and SA signalling is involved in the modulation of root microbiota.
Taken together, unravelling the interactions between plant defence systems, microbiomes, and environmental factors will be an essential next step for understanding plant selection of microbes and immune modulation shifts of plant microbiota of various environmental conditions.

2.3. Plant Hosts Selectively Recruit Microbes via Ecotype Specificity

In light of growing concern over the threat of water and nutrient stress facing terrestrial ecosystems, particularly those used for agricultural production, increased emphasis has been placed on understanding how abiotic stress conditions influence the composition and functioning of the root microbiome and its ultimate consequences for plant health. However, under abiotic stress conditions, the composition of root microorganisms will change accordingly, which will be reflected in changes in root secretions. Although there are many conclusions about abiotic stresses on microbial community alteration, in recent years, attention has gradually shifted to the genotype differences of plant hosts. Following the appearance of next-generation sequencing, many studies have characterized the rhizospheric wheat microbiome and investigated the influence of the compartment (rhizoplane vs. endosphere), crop management, or wheat genotypes on the diversity and structure of those complicated microbial communities [71,72,73,74]. For many crops, studying soil microbial structure is indisputably the most necessary issue in crop management and plant genotype research. A number of studies have demonstrated that plants confirm changes of the microbial community under the same environmental conditions. There are many studies on the effect of different genotypes of the same plant on microorganisms (Table 1). The importance of genotype–environment interactions is in the structural assembly of plant microbiomes. For example, the reference plant Arabidopsis thaliana demonstrates that host cultivars (genotypes) mediate a weak but measurable impact on the root-associated microbiota [75]. Plant genotypes and soil have specific effects on the wheat rhizosphere microbial community [76]. The effect of plant genotypes on the inter-root microbial community of maize showed that the two genotypes had a significant effect on the inter-root microbial community of maize [77]. Lamit investigated different cottonwood genotypes supporting different aboveground fungal communities [78]. Jiang et al. investigated the inter-root bacterial community of 12 Rabbiteye blueberry (RB) cultivars and demonstrated that inter-rooting from plant cultivars affects the bacterial association network [79]. Microbial community (SMC) structure and root turnover were assessed in two contrasting Lolium perenne cultivars (AberDove and S23), and microbial communities with differences were discovered [80]. Hou et al. found significant differences in the composition of inter-root bacterial communities of different rice varieties under metal contamination conditions [81]. A significant genotypic variation in rhizosphere microbial communities in rice plants was reported [82]. Huang et al. showed significant differences in the inter-root microbial communities of two varieties of kale-type oilseed rape [83]. By analysing the soil samples of three different peony species, it was found that the microbial community structure was greatly influenced by the peony species [84]. Zhou et al. found significant differences in the inter-root microbial communities of four cucumber varieties [85]. A comparison of different genotypes of soybean [5], winter wheat [86], and maize [4] also revealed that the bacterial community structure differed among cultivars.
All of this evidence suggests that microbial communities change in response to changes in hosts, so a hypothesis has been proposed that plants will recruit different microorganisms by releasing different root secretions based on their own demand recruitment to relieve stress on their own growth or when they encounter stressful environments. Specifically, a mechanism employed by plants is the ‘cry for help’ strategy [87], a phenomenon whereby plants experiencing abiotic, pest-induced, or pathogen-induced stresses recruit helpful microbes/traits from the environment by employing a range of chemical stimuli to boost their capacity to combat stresses [88,89]. For example, some soils conditioned by take-all disease-infected wheat may lead to less take-all in future generations [43]. By studying the composition and metabolic potential of inter-root bacterial communities of different common bean (Phaseolus vulgaris) cultivars with different levels of resistance to the fungal root pathogen Fusarium (Fox), differences in microbial composition between susceptible and nonsusceptible cultivars and higher network complexity of resistant cultivars were found. Pseudomonadaceae and Bacillaceae had a high abundance in the rhizosphere of the Fox-resistant cultivar. Breeding for Fox resistance in common bean could have co-selected other unknown plant traits that support the next abundance of specific helpful microorganism families in the rhizosphere with functional traits that reinforce the primary line of defence [90]. Microbiome structures differed between the two tomato cultivars and transplantation of rhizosphere microbiota from resistant plants suppressed disease symptoms in susceptible plants. Comparative analyses of rhizosphere metagenomes from resistant and susceptible plants enabled the identification and assembly of a flavobacterial genome that was much more abundant in the resistant plant, which could suppress R. solanacearum-disease development in a susceptible plant [45]. Thus, on the far side of classical ‘adapt or migrate’ strategies, accumulating evidence suggests that plants use the ‘cry for help’ strategy as a full-of-life method that enables them to learn from microorganism associations under stresses. The host is the subject, and it is unclear in what way they recruit microorganisms; therefore, mining the mechanism of plant–microbe interactions will be an important part of future plant breeding. However, this theory still needs more evidence to prove it.

2.4. Emerging Factors That Are Responsible for Microbe Recruitment

It is not surprising that various active genes of the soil microbiota play important roles in competition or cooperation with other microbes. Microorganisms synthesize completely different products that affect microbe–microbe interactions. Distinct and numerous gene clusters for biosynthesis of natural products have been identified in plant-associated microorganisms [91,92]. Additionally, the organic chemistry diversity of root exudates was analysed for alterations within the presence or concentrations of metabolites (metabolomics) to determine how root exudation drives stress-induced microbiome assembly. The key metabolic compounds are isolated from the rhizosphere for potential and tested in vitro for interactions with plant microorganism symbionts and pathogens and, in turn, plant health. The addition of various exudate mixtures to plant monocultures increased microorganism diversity. Some studies also found that higher plant diversity was associated with higher microbial diversity. Major challenges remain, such as analysis of root exudation in natural settings, mostly due to the chemical quality of various soil types. A few plant products that affect the rhizosphere microbiome are known. For example, 2,4-diacetylphloroglucinol [50], peroxidases and oxylipins [93], benzoxazinoids [94], phenylpropanoids [95], flavonoids [93], coumarins [96], triterpenes, mucilage [97], and aromatic compounds [98] are reported to attract microbes that benefit plant defence and nutrition. However, how these compounds are synthesized and how they regulate the microbe interplay, along with their underlying biochemical mechanisms, remains to be explored. Although each plant produces exudates, the number and composition of root exudates vary. First, exudation is outlined by the genotype of the host. Nineteen Arabidopsis root metabolic patterns and their variability between plants and naturally occurring germplasm were analysed, and for some secondary metabolites, the ratio of total plant-to-plant variability was high and significant [99]. Exudation is modulated by abiotic stresses: the amounts of exuded amino acids, sugars, and organic acids modified in maize fully grown in phosphate-, iron-, nitrogen-, or potassium-deficient conditions [100]. Additionally, phosphate-deficient Arabidopsis plants exhibit hyperbolic coumarin and oligolignol exudation [101], and coumarin exudation is significantly reduced in ABCG37-deficient plants [102], serious metal-treated poplar (Populus tremula) iatrogenic organic acid exudation, and zinc-deficient wheat hyperbolic phytosiderophore exudation [103]. Differential exudation could be a plausible mechanism that plants might modulate their interaction with microbes. All of this evidence suggests that under different stresses the root secretions of plants are altered, and it is not difficult to speculate that the microbial community is altered accordingly. However, research on the secretion mechanism of plant inter-root secretions and the discovery of key loci for the recruitment of microorganisms remains a challenge.

3. Ecotype-Prone Splicing Events Are Good Candidates to Study Plant-Microbe Interactions

3.1. Pre-mRNA Alternative Splicing and Splicing Regulators of Plant Immunity

Most eukaryotic genes are interrupted by introns. Therefore, an important step in gene expression is the removal of introns through the splicing of precursor mRNA transcripts (premRNAs). Emerging evidence has indicated that plant-associated microbiomes are engaged with plant health and the helpful features of plant-associated microbes will boost the immune responses in plants against biotic/abiotic environmental constraints. Recent progress in high outturn sequencing of ribonucleic acid and bioinformatics tools to research AS events [104,105,106,107] at a genome-wide scale have shown that AS is a vital part of host transcriptome reprogramming in response to microorganism and viral infection in several plant species. In plants, varied reports have primarily focused on AS analysis in model plant species or nonwoody plants, resulting in a notable lack of research on AS in woody plants [108]. Alternative splicing (AS) enhances transcriptome malleability and proteome diversity in response to various growth and stress cues, which places AS at the crossroads of adaptation and environmental stress response [109,110]. However, some people are also working on different ways to improve these bottlenecks regarding AS. For example, Chen et al. presented the plant splicing-related protein expression and annotation database PlantSPEAD, introducing the information on their annotations, sequence information, functional domains, protein interaction partners, and expression patterns in response to abiotic stresses, from a dozen existing databases and the literature [111]. Furthermore, the SWATH-MS approach is characterized by a data-independent acquisition (DIA) method followed by a unique targeted information extraction approach [112]. SWATH-MS proteomics is applied for a range of large-scale profiling studies in plants, moving from model plant species to various plants without reference ordination annotation [113]. Within the field of discovery proteomics, alternative splicing is an emerging research area associated with posttranscriptional regulation. SWATH-MS could be applied to specifically establish peptides translated from splicing junctions [114]. This is also a direction worthy of further study in the future.
Plant immune receptors belonging to the receptor-like kinase (RLK) family play important roles in the recognition of microbial pathogens and activation of downstream defence responses. The function of RLKs in plant immune responses involves specific phosphorylation events within and outside the structural domain of the kinase, which leads to altered kinase activity and consequently to immune signalling. The function of several RLKs in pathogen resistance has been extensively studied in model plants with simpler genomes (e.g., rice and Arabidopsis). Examples include XA21 from rice [115,116] and PR5K from Arabidopsis [117]. The contribution of resistance to powdery mildew infection in durum wheat has been found by studying the expression and role of TtdLRK10 L-1 in wheat defence against powdery mildew infection and by identifying the intron putative MYB binding site (MYB-BS) in the positive role in the expression and function of TtdLRK10 L-1. Nucleotide binding site/leucine-rich repeat (NBS-LRR) and serine/threonine kinase (STK) genes are unit two of the known categories of resistance (R-) genes in plants and occur in massive multigene families. Some receptor-like kinases (RLKs) with serine/threonine were similar to both cytoplasmic RLKs, such as Pto, and RLKs with LRR, S-locus, lectin-like, and thaumatin-like extracellular binding-domains [118]. By analysing kinase domain-targeted isolation of defence-related receptor-like kinases (RLK/Pelle) in Platanus × acerifolia: phyletic and structural, we see that some RLKs have indeed been involved in the expression of phenotypic plasticity and are therefore a decent candidate for investigations into pathogen resistance [119].
PremRNA splicing plays an important role in the regulation of plant immunity mediated by the RLKs SNC4 and CERK1. Plant surface pattern receptors are variably spliced to produce different transcripts that respond to pathogen infestation by influencing downstream signalling. Bacterial flagellin 2 (FLS2) is a classical PRR receptor protein that detects conserved bacterial flagellin 2 (FLS2) in plants, sensing external bacterial infestation. Flagellin perception in Arabidopsis works through recognition of its extremely conserved N-terminal epitope (flg22) by flagellin-sensitive 2 (FLS2) to initiate a series of immune responses. In nine families of dicotyledons, FLS2 was shown to undergo AS of its first exon. Point mutations and gene swaps indicated that the position and potency of exitron splicing primarily relied on the nucleotide sequences of FLS2 genes. The position and efficiency of splicing depend mainly on the FLS2 nucleotide sequence of FLS2; exon of FLS2 is spliced via an intron-mediated enhancement (IME), which regulates the accumulation of transcriptional products. Some ATs have the potential to encode suppressors for the FLS2 pathway, and transformed transcripts can encode FLS2 pathway repressors that affect FLS2-mediated reactive oxygen species production. This study reveals that alternative splicing finely regulates the pattern of receptor recognition and thus influences the downstream disease resistance response [120]. The receptor-like cytoplasmic kinase BIK1, a component of the FLS2 immune receptor advanced, not solely positively regulates flg22-triggered calcium influx; it conjointly directly phosphorylates the NADPH oxidase RbohD at specific sites in an exceedingly calcium-independent manner to enhance ROS generation. However, at present, the relationship between some cytoplasmic kinases such as BIK1 and AS is unknown [121].
The Arabidopsis thaliana NPR1 loss-of-function mutant PR gene expression is reduced, and the ability to develop SAR loses the capacity to develop SAR. The backfill npr1 mutant to obtain the SNC (suppressor of npr1-1, constitutional) series of mutants can restore both abilities to some extent [122]. The Arabidopsis thaliana mutant SNC4 1D contains an RLK SNC4 (the NPR1-1 suppressor, CONSTITUTIVE4) gain-of-function mutation, which leads to constitutive activation of the defence response. Identification of two conserved shearing factors, SUA (ABI3-5 repressor gene) and RSN2 (SNC4-1D essential gene), are necessary to construct a defence response by mutating the snc4 1D mutant.
In SUA and RSN2 mutants, SNC4 shearing is altered, and further analysis showed that SUA and RSN2 are important receptors for shearing CERK1 (an essential receptor for PAMP, titin inducible receptor kinase 1). The precursor mRNA is sheared in the receptor-like kinase protein kinase SNC4 and CERK1-mediated regulation of plant immunity [123]. All these directly or indirectly express the key role played by alternative splicing in plant defence. Alternatively, spliced transcripts in plants result in profound changes in their gene expression patterns throughout developmental growth.
Interestingly, we found that AS events seem to have specificity across various plant species or in response to a variety of stressful environments. For resistance to different pathogenic bacteria, independent splice variants are also formed. IR was the most common AS pattern observed in Paulownia tomentosa [124]. Exon skipping was the primary AS pattern in Populus throughout salt stress, suggesting a completely different tree species produce different AS types to cope with constant stress. Apparently, an alternative acceptor is the major AS pattern when camellia sinensis is treated with drought and heat stress [125].
Arabidopsis RPS4 senses and is resistant to the Avr Rps4-expressing strain Pst.DC3000, and RPS4 undergoes variable splicing to produce six different transcripts. After infestation, RPS4 expression was upregulated in intact transcripts, whereas clonally incomplete transcripts could not backfill the resistance of the deficient RPS4 plants to Pst. DC3000, suggesting that only intact RPS4 transcripts are resistant to Pst [126]. In tobacco, the N gene specifically recognizes a 50 kD decapping enzyme protein (p50) of Tobaccomosaic virus (TMV) and selectively shears the N gene [127,128]. Different tree species manufacture completely different AS varieties to cope with a similar stresses. Curiously, an alternate acceptor is the major AS pattern when C. sinensis is treated with drought and heat stress [125]. Comparisons of gene structures from 67 plant species, protein domains, promoter regions, and conserved splicing patterns indicated that plant U1-70Ks are unable to preserve their preserved molecular function across plant lineages and play a very important practical role in response to environmental stresses [129]. A total of 4388 unique proteins were identified and quantified, among which 542 proteins showed vital abundance changes upon Pb(II) exposure, and differentially expressed proteins (DEPs) that were primarily distributed in the lignin and flavonoid synthesis pathways were powerfully activated upon Pb exposure, indicating their potential roles in Pb detoxification in poplar [130].
There are fewer reports related to alternative splicing, but it is easy to see that conserved AS events seem to be consistently present, including the feature that alternative splicing is specific under different stresses as well as under different species. We have also previously summarized the changes in microbial communities under different plants and different stresses, and it is unclear how the release of phytohormones relates to AS, including the recruitment of their preferred microbes by plants, so we speculate that AS may have its own unique splicing.

3.2. Genome-Wide Association Analyses of Splicing Quantitative Trait Loci (sQTLs) in Plants

Although AS is pervasive, the genetic basis for differential isoform usage in plants is increasing, widespread natural variation in AS has been observed in plants, and how AS is regulated and contributes to phenotypic variation is poorly understood. One study performed genome-wide analysis in 666 geographically distributed diverse ecotypes of Arabidopsis thaliana to spot genomic regions (splicing quantitative trait loci (sQTLs)) that regulated differential AS, and observed enrichment for trans-sQTLs (trans-sQTL hotspots) on chromosome regions. Many sQTLs were enriched, including the circadian clock, flowering, and stress-responsive genes, suggesting the potential role of differential isoform usage in controlling these necessary processes among diverse ecotypes of Arabidopsis [15]. The presence of widespread variation in diverse ecotypes of Arabidopsis at genetic level has been widely reported. For example, epithiospecifier protein (ESP) is responsible for diverting glucosinolate hydrolysis from the generation of isothiocyanates to that of epithionitriles or nitriles and thereby negatively affecting the capacity of the plant to defend itself against certain insects. Some studies have shown that ESP expression is regulated differently between the two A. thaliana ecotypes [131]. Comparison of AS in three phenotypic variants of maize revealed the importance of AS in diversifying gene function and regulating phenotypic variation as well [132] (Table 1).

3.3. Crosstalk between Plant Ecotype-Specific Splicing and Their Commensal Microbiome

Increasing evidence has suggested that the splice sites were also differentially selected among various plant ecotypes. Although the effect of genotypic variation on splice site determination among plant ecotypes is less reported, the sQTLs identified in several studies provide fundamental evidence to support this finding. Subsequently, an intriguing hypothesis has been proposed that the splicing variation among plant ecotypes may further influence the recruitment of the plant commensal microbiome by affecting crucial factors involved in secondary metabolism, root exudate secretion, and plant immune responses, etc. However, the role of these differential splice sites present among various plant ecotypes during the interaction of plants and their microbiomes remains unclear (Figure 1).

4. Conclusions and Future Perspective

In recent years, the study of plant microbiome interactions has become a hotspot in scientific research. Increasing evidence suggested that alternative splicing plays a pivotal role in plant–microbiome interactions, a dynamic process controlled by both factors generated by plants and microorganisms. Specifically, in this review article, we discussed the recruitment mechanism of commensal microbiome by plant hosts and proposed that the differential recruitment of the microbiome observed among plant ecotypes is closely linked to their splicing quantitative trait loci (sQTLs) identified from these plant ecotypes. For instance, a deep understanding of the genetic linkage between AS and secretion of root exudates for microbiome recruitment will be the key to mastering changes in plant ecology and plant breeding. However, further investigations are required to validate this hypothesis and proof of its value to form the new research direction in this field.
To this end, studies of both host and microbiome aspects are necessary to unravel the underlying mechanism between plant–microbiome interactions. In the host aspect particularly, the propensity for AS varies under different stress conditions, and unique splice variants are developed to fight against different pathogens. AS triggers intracellular defence signals and mass expression of defence genes, yet the interactions between different plant-associated symbionts and the plant immune system are unknown. Plants recruit microbes in a ‘call for help’ strategy, with different species recruiting different microbes and susceptible versus resistant species recruiting different microbial communities. One major challenge is going to be to research root exudation in natural settings. Due to the chemical complexity of soil, exudation is historically analysed in aquacultural culture, an environment distant from many natural settings of plant microbiome studies. In addition, new technologies are needed for high-throughput screening of functional microorganisms that can be targeted to reveal the impact of core microorganisms on the inter-root biota and, in turn, on plant health. With further understanding of root morphology and secretions, the core strains involved may alter the engineering or breeding of plants with altered talent to act against pathogens. This must be complemented with an improved understanding of the substrate preferences of plant-associated microbes, their interactions, and also the mechanisms which profit the plant. Although research on alternative splicing in plant disease resistance has been ongoing, there are still many unanswered questions about the role of alternative splicing in plant immunity.
Regarding commensal microbes, with the evolution of host–microbe interactions, microorganisms have evolved evolutionary strategies for manipulating host AS machinery to disrupt host immunity, and alternative splicing is involved in the mechanism of R-Avr interactions. Whether this mechanism is widespread in multiple species and in disease-resistance systems in which different microorganisms interact with plants has not been fully explained. The mechanism of alternative splicing in the R–Avr interaction, and whether it is widespread in multiple species and in different microbe–plant interactions in the disease resistance system, is also not fully understood; nor are the functional mechanisms of R proteins and subcellular localization. In the future, we need to investigate the functional mechanism, subcellular localization, and interaction with the target protein Avr to further expand our understanding of the molecular mechanism of plant resistance.

Author Contributions

Conceptualization, Z.C. and Z.-G.W.; writing original draft preparation, Y.-H.L. and Y.-Y.Y.; writing review and editing, Z.C. and Z.-G.W.; funding, Z.C.; The version of the manuscript was agreed by all authors. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by National Key Research Development Program of China (2017YFD0200308) and Post-subsidy project of National Key Research Development Program of China (2018-5262), the National Natural Science Foundation of China (numbers 31860515 and 21977023), Program of Introducing Talents to Chinese Universities (111 Program, D20023) and the China Agriculture Research System (CARS-23-D09).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Köberl, M.; Schmidt, R.; Ramadan, E.M.; Bauer, R.; Berg, G. The microbiome of medicinal plants: Diversity and importance for plant growth, quality and health. Front. Microbiol. 2013, 4, 400. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Bouffaud, M.; Poirier, M.; Muller, D.; Moënne-Loccoz, Y. Root microbiome relates to plant host evolution in maize and other Poaceae. Environ. Microbiol. 2014, 16, 2804–2814. [Google Scholar] [CrossRef] [PubMed]
  3. Fitzpatrick, C.R.; Salas-González, I.; Conway, J.M.; Finkel, O.M.; Gilbert, S.; Russ, D.; Teixeira, P.; Dangl, J.L. The Plant Microbiome: From Ecology to Reductionism and Beyond. Annu. Rev. Microbiol. 2020, 74, 81–100. [Google Scholar] [CrossRef] [PubMed]
  4. Kong, X.; Han, Z.; Tai, X.; Jin, D.; Ai, S.; Zheng, X.; Bai, Z. Maize (Zea mays L. Sp.) varieties significantly influence bacterial and fungal community in bulk soil, rhizosphere soil and phyllosphere. FEMS Microbiol. Ecol. 2020, 96, fiaa020. [Google Scholar] [CrossRef]
  5. Sohn, S.I.; Ahn, J.H.; Pandian, S.; Oh, Y.J.; Shin, E.K.; Kang, H.J.; Cho, W.S.; Cho, Y.S.; Shin, K.S. Dynamics of Bacterial Community Structure in the Rhizosphere and Root Nodule of Soybean: Impacts of Growth Stages and Varieties. Int. J. Mol. Sci. 2021, 22, 5577. [Google Scholar] [CrossRef]
  6. Zipfel, C.; Oldroyd, G.E. Plant signalling in symbiosis and immunity. Nature 2017, 543, 328–336. [Google Scholar] [CrossRef]
  7. Suwabe, K.; Suzuki, G.; Watanabe, M. Achievement of genetics in plant reproduction research: The past decade for the coming decade. Genes Genet. Syst. 2010, 85, 297–310. [Google Scholar] [CrossRef] [Green Version]
  8. Huang, X.F.; Chaparro, J.; Reardon, F.; Zhang, R.; Shen, Q.; Vivanco, J. Rhizosphere interactions: Root exudates, microbes and microbial communities. Botany 2014, 92, 4. [Google Scholar] [CrossRef]
  9. Saleem, M.; Law, A.D.; Sahib, M.R.; Pervaiz, Z.H.; Zhang, Q. Impact of root system architecture on rhizosphere and root microbiome. Rhizosphere 2018, 6, 47–51. [Google Scholar] [CrossRef]
  10. Rigo, R.; Bazin, J.R.M.; Crespi, M.; Charon, C.L. Alternative Splicing in the Regulation of Plant-Microbe Interactions. Plant Cell Physiol. 2019, 60, 1906–1916. [Google Scholar] [CrossRef]
  11. Kornblihtt, A.R.; Schor, I.E.; Alló, M.; Dujardin, G.; Petrillo, E.; Muñoz, M.J. Alternative splicing: A pivotal step between eukaryotic transcription and translation. Nat. Rev. Mol. Cell Biol. 2013, 14, 153–165. [Google Scholar] [CrossRef] [PubMed]
  12. Wang, E.T.; Sandberg, R.; Luo, S.; Khrebtukova, I.; Zhang, L.; Mayr, C.; Kingsmore, S.F.; Schroth, G.P.; Burge, C.B. Alternative isoform regulation in human tissue transcriptomes. Nature 2008, 456, 470–476. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Takata, A.; Matsumoto, N.; Kato, T. Genome-wide identification of splicing QTLs in the human brain and their enrichment among schizophrenia-associated loci. Nat. Commun. 2017, 8, 14519. [Google Scholar] [CrossRef] [PubMed]
  14. Reddy, A.; Marquez, Y.; Kalyna, M.; Barta, A. Complexity of the Alternative Splicing Landscape in Plants. Plant Cell 2013, 25, 3657–3683. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Khokhar, W.; Hassan, M.A.; Reddy, A.; Chaudhary, S.; Jabre, I.; Byrne, L.J.; Syed, N.H. Genome-Wide Identification of Splicing Quantitative Trait Loci (sQTLs) in Diverse Ecotypes of Arabidopsis thaliana. ISO4 2019, 10, 1160. [Google Scholar] [CrossRef] [Green Version]
  16. Iida, K.; Go, M. Survey of Conserved Alternative Splicing Events of mRNAs Encoding SR Proteins in Land Plants. Mol. Biol. Evol. 2006, 23, 1085–1094. [Google Scholar] [CrossRef] [Green Version]
  17. Feng, J.; Li, J.; Gao, Z.; Lu, Y.; Yu, J.; Zheng, Q.; Yan, S.; Zhang, W.; He, H.; Ma, L. SKIP Confers Osmotic Tolerance during Salt Stress by Controlling Alternative Gene Splicing in Arabidopsis. Mol. Plant 2015, 8, 1038–1052. [Google Scholar] [CrossRef] [Green Version]
  18. Jie, H.; Gu, L.; Ying, Z.; Yan, T.; Kong, G.; Liang, K.; Guo, B.; Min, Q.; Yang, W.; Jing, M. An oomycete plant pathogen reprograms host pre-mRNA splicing to subvert immunity. Nat. Commun. 2017, 8, 2051. [Google Scholar]
  19. Delmont, T.O.; Robe, P.; Cecillon, S.; Clark, I.M.; Constancias, F.; Simonet, P.; Hirsch, P.R.; Vogel, T.M. Accessing the soil metagenome for studies of microbial diversity. Appl. Environ. Microbiol. 2011, 77, 1315–1324. [Google Scholar] [CrossRef] [Green Version]
  20. Vivanco, L.; Rascovan, N.; Austin, A.T. Plant, fungal, bacterial, and nitrogen interactions in the litter layer of a native Patagonian forest. PeerJ 2018, 6, e4754. [Google Scholar] [CrossRef] [Green Version]
  21. Teste, F.P.; Kardol, P.; Turner, B.L.; Wardle, D.A.; Zemunik, G.; Renton, M.; Laliberté, E. Plant-soil feedback and the maintenance of diversity in Mediterranean-climate shrublands. Science 2017, 355, 173–176. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Hamonts, K.; Trivedi, P.; Garg, A.; Janitz, C.; Grinyer, J.; Holford, P.; Botha, F.C.; Anderson, I.C.; Singh, B.K. Field study reveals core plant microbiota and relative importance of their drivers. Environ. Microbiol. 2018, 20, 124–140. [Google Scholar] [CrossRef] [PubMed]
  23. Xu, J.; Zhang, Y.; Zhang, P.; Trivedi, P.; Riera, N.; Wang, Y.; Liu, X.; Fan, G.; Tang, J.; Coletta-Filho, H.D.; et al. The structure and function of the global citrus rhizosphere microbiome. Nat. Commun. 2018, 9, 4894. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Borrel, G.; Brugère, J.F.; Gribaldo, S.; Schmitz, R.A.; Moissl-Eichinger, C. The host-associated archaeome. Nat. Rev. Microbiol. 2020, 18, 622–636. [Google Scholar] [CrossRef]
  25. Cordovez, V.; Dini-Andreote, F.; Carrión, V.; Raaijmakers, J.M. Ecology and Evolution of Plant Microbiomes. Annu. Rev. Microbiol. 2019, 73, 69. [Google Scholar] [CrossRef]
  26. Van der Heijden, M.G.; Hartmann, M. Networking in the Plant Microbiome. PLoS Biol. 2016, 14, e1002378. [Google Scholar] [CrossRef]
  27. Ashrafuzzaman; Hossen; Fa; Ismail; Mr; Hoque; Ma; Islam; Mz; Shahidullah, Efficiency of plant growth-promoting rhizobacteria (PGPR) for the enhancement of rice growth. Afr. J. Biotechnol. 2009, 8, 1247–1252.
  28. Wei, G.; Li, M.; Shi, W.; Tian, R.; Gao, Z. Similar drivers but different effects lead to distinct ecological patterns of soil bacterial and archaeal communities. Soil Biol. Biochem. 2020, 144, 107759. [Google Scholar] [CrossRef]
  29. Anna, K.; Pijl, A.S.; Van, V.J.A.; Kowalchuk, G.A. Differences in vegetation composition and plant species identity lead to only minor changes in soil-borne microbial communities in a former arable field. FEMS Microbiol. Ecol. 2010, 63, 372–382. [Google Scholar]
  30. Hartmann, A.; Fischer, D.; Kinzel, L.; Chowdhury, S.P.; Hofmann, A.; Baldani, J.I.; Rothballer, M. Assessment of the structural and functional diversities of plant microbiota: Achievements and challenges—A review. J. Adv. Res. 2019, 19, 3–13. [Google Scholar] [CrossRef]
  31. Pétriacq, P.; Williams, A.; Cotton, A.; McFarlane, A.E.; Rolfe, S.A.; Ton, J. Metabolite profiling of non-sterile rhizosphere soil. Plant J. 2017, 92, 147–162. [Google Scholar] [CrossRef] [PubMed]
  32. Thomas, P.; Franco, C.M.M. Intracellular Bacteria in Plants: Elucidation of Abundant and Diverse Cytoplasmic Bacteria in Healthy Plant Cells Using In Vitro Cell and Callus Cultures. Microorganisms 2021, 9, 269. [Google Scholar] [CrossRef] [PubMed]
  33. Armada, E.; Portela, G.; Roldán, A.; Azcón, R. Combined use of beneficial soil microorganism and agrowaste residue to cope with plant water limitation under semiarid conditions. Geoderma 2014, 232–234, 640–648. [Google Scholar] [CrossRef]
  34. Calvo, P.; Nelson, L.; Kloepper, J.W. Agricultural uses of plant biostimulants. Plant Soil 2014, 383, 3–41. [Google Scholar] [CrossRef] [Green Version]
  35. Bukhat, S.; Imran, A.; Javaid, S.; Shahid, M.; Majeed, A.; Naqqash, T. Communication of plants with microbial world: Exploring the regulatory networks for PGPR mediated defense signaling. Microbiol. Res. 2020, 238, 126486. [Google Scholar] [CrossRef]
  36. Compant, S.; Duffy, B.; Nowak, J.; Clément, C.; Barka, E.A. Use of plant growth-promoting bacteria for biocontrol of plant diseases: Principles, mechanisms of action, and future prospects. Appl. Environ. Microbiol. 2005, 71, 4951–4959. [Google Scholar] [CrossRef] [Green Version]
  37. Barea, J.M.; Pozo, M.J.; Azcón, R.; Azcón-Aguilar, C. Microbial co-operation in the rhizosphere. J. Exp. Bot. 2005, 56, 1761–1778. [Google Scholar] [CrossRef] [Green Version]
  38. Yi; Zhou; Yong-Lark; Choi; Ming; SunZiniu; Yu, Novel roles of Bacillus thuringiensis to control plant diseases. Appl. Microbiol. Biotechnol. 2008, 80, 563–572. [CrossRef]
  39. Lau, J.A.; Lennon, J.T. Rapid responses of soil microorganisms improve plant fitness in novel environments. Proc. Natl. Acad. Sci. USA 2012, 109, 14058–14062. [Google Scholar] [CrossRef] [Green Version]
  40. Lee, B.; Lee, S.; Ryu, C.M. Foliar aphid feeding recruits rhizosphere bacteria and primes plant immunity against pathogenic and non-pathogenic bacteria in pepper. Ann. Bot. 2012, 110, 281–290. [Google Scholar] [CrossRef]
  41. Chen, Y.; Wang, J.; Yang, N.; Wen, Z.; Sun, X.; Chai, Y.; Ma, Z. Wheat microbiome bacteria can reduce virulence of a plant pathogenic fungus by altering histone acetylation. Nat. Commun. 2018, 9, 3429. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Berendsen, R.L.; Vismans, G.; Yu, K.; Song, Y.; de Jonge, R.; Burgman, W.P.; Burmølle, M.; Herschend, J.; Bakker, P.; Pieterse, C.M.J. Disease-induced assemblage of a plant-beneficial bacterial consortium. ISME J. 2018, 12, 1496–1507. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Raaijmakers, J.M.; Bonsall, R.F.; Weller, D.M. Effect of Population Density of Pseudomonas fluorescens on Production of 2,4-Diacetylphloroglucinol in the Rhizosphere of Wheat. Phytopathology 1999, 89, 470–475. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Yin, C.; Casa Vargas, J.M.; Schlatter, D.C.; Hagerty, C.H.; Hulbert, S.H.; Paulitz, T.C. Rhizosphere community selection reveals bacteria associated with reduced root disease. Microbiome 2021, 9, 86. [Google Scholar] [CrossRef]
  45. Kwak, M.J.; Kong, H.G.; Choi, K.; Kwon, S.K.; Song, J.Y.; Lee, J.; Lee, P.A.; Choi, S.Y.; Seo, M.; Lee, H.J.; et al. Rhizosphere microbiome structure alters to enable wilt resistance in tomato. Nat. Biotechnol. 2018, 36, 1100. [Google Scholar] [CrossRef]
  46. Dudenhffer, J.H.; Scheu, S.; Jousset, A. Systemic enrichment of antifungal traits in the rhizosphere microbiome after pathogen attack. J. Ecol. 2016, 104, 1566–1575. [Google Scholar] [CrossRef]
  47. Timm, C.M.; Carter, K.R.; Carrell, A.A.; Jun, S.R.; Weston, D.J. Abiotic Stresses Shift Belowground Populus -Associated Bacteria Toward a Core Stress Microbiome. mSystems 2018, 3, e00070-17. [Google Scholar] [CrossRef] [Green Version]
  48. Santos-Medellín, C.; Edwards, J.; Liechty, Z.; Bao, N.; Sundaresan, V. Drought Stress Results in a Compartment-Specific Restructuring of the Rice Root-Associated Microbiomes. mBio 2017, 8, e00764-17. [Google Scholar] [CrossRef] [Green Version]
  49. Lucía, F.; Ana, F.S. Strong shift in the diazotrophic endophytic bacterial community inhabiting rice (Oryza sativa) plants after flooding. FEMS Microbiol. Ecol. 2015, 91, fiv104. [Google Scholar]
  50. Gardener, M.S.; Weller, D.M. Changes in Populations of Rhizosphere Bacteria Associated with Take-All Disease of Wheat. Appl. Environ. Microbiol. 2001, 67, 4414–4425. [Google Scholar] [CrossRef] [Green Version]
  51. Durán, P.; Thiergart, T.; Garrido-Oter, R.; Agler, M.; Kemen, E.; Schulze-Lefert, P.; Hacquard, S. Microbial Interkingdom Interactions in Roots Promote Arabidopsis Survival. Cell 2018, 175, 973–983. [Google Scholar] [CrossRef] [PubMed]
  52. Finkel, O.M.; Castrillo, G.; Paredes, S.H.; González, I.; Dangl, J.L. Understanding and exploiting plant beneficial microbes—ScienceDirect. Curr. Opin. Plant Biol. 2017, 38, 155–163. [Google Scholar] [CrossRef] [PubMed]
  53. Castrillo, G.; Teixeira, P.J.; Paredes, S.H.; Law, T.F.; de Lorenzo, L.; Feltcher, M.E.; Finkel, O.M.; Breakfield, N.W.; Mieczkowski, P.; Jones, C.D.; et al. Root microbiota drive direct integration of phosphate stress and immunity. Nature 2017, 543, 513–518. [Google Scholar] [CrossRef] [PubMed]
  54. Maureen, B.; Britt, K. Nutrient- and Dose-Dependent Microbiome-Mediated Protection against a Plant Pathogen. Curr. Biol. 2018, 28, 2487. [Google Scholar]
  55. Pieterse, C.M.; Zamioudis, C.; Berendsen, R.L.; Weller, D.M.; Van Wees, S.C.; Bakker, P.A. Induced systemic resistance by beneficial microbes. Annu. Rev. Phytopathol. 2014, 52, 347–375. [Google Scholar] [CrossRef] [Green Version]
  56. Balmer, D.; Planchamp, C.; Mauch-Mani, B. On the move: Induced resistance in monocots. J. Exp. Bot. 2013, 64, 1249–1261. [Google Scholar] [CrossRef]
  57. Gill, S.S.; Gill, R.; Trivedi, D.K.; Anjum, N.A.; Sharma, K.K.; Ansari, M.W.; Ansari, A.A.; Johri, A.K.; Prasad, R.; Pereira, E.; et al. Piriformospora indica: Potential and Significance in Plant Stress Tolerance. Front. Microbiol. 2016, 7, 332. [Google Scholar] [CrossRef] [Green Version]
  58. Newitt, J.T.; Prudence, S.M.M.; Hutchings, M.I.; Worsley, S.F. Biocontrol of Cereal Crop Diseases Using Streptomycetes. Pathogens 2019, 8, 78. [Google Scholar] [CrossRef] [Green Version]
  59. Aloo, B.N.; Makumba, B.A.; Mbega, E.R. The potential of Bacilli rhizobacteria for sustainable crop production and environmental sustainability. Microbiol. Res. 2019, 219, 26–39. [Google Scholar] [CrossRef]
  60. Helfrich, E.J.N.; Vogel, C.M.; Ueoka, R.; Schäfer, M.; Ryffel, F.; Müller, D.B.; Probst, S.; Kreuzer, M.; Piel, J.; Vorholt, J.A. Bipartite interactions, antibiotic production and biosynthetic potential of the Arabidopsis leaf microbiome. Nat. Microbiol. 2018, 3, 909–919. [Google Scholar] [CrossRef]
  61. Syed Ab Rahman, S.F.; Singh, E.; Pieterse, C.M.J.; Schenk, P.M. Emerging microbial biocontrol strategies for plant pathogens. Plant Sci. 2018, 267, 102–111. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  62. Chhabra, R.; Kaur, S.; Vij, L.; Gaur, K. Exploring Physiological and Biochemical Factors Governing Plant Pathogen Interaction: A Review. Int. J. Curr. Microbiol. Appl. Sci. 2020, 9, 1650–1666. [Google Scholar] [CrossRef]
  63. Boyd, L.A.; Ridout, C.; O’Sullivan, D.M.; Leach, J.E.; Leung, H. Plant–pathogen interactions: Disease resistance in modern agriculture—ScienceDirect. Trends Genet. 2013, 29, 233–240. [Google Scholar] [CrossRef] [PubMed]
  64. Jones, J.; Dangl, J.L. The plant immune system. Nature 2006, 444, 323–329. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  65. Spoel, S.H.; Dong, X. How do plants achieve immunity? Defence without specialized immune cells. Nat. Rev. Immunol. 2012, 12, 89–100. [Google Scholar] [CrossRef]
  66. Vlot, A.C.; Dempsey, D.A.; Klessig, D.F. Salicylic Acid, a multifaceted hormone to combat disease. Annu. Rev. Phytopathol. 2009, 47, 177–206. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  67. Conrath, U.; Beckers, G.J.; Langenbach, C.J.; Jaskiewicz, M.R. Priming for enhanced defense. Annu. Rev. Phytopathol. 2015, 53, 97–119. [Google Scholar] [CrossRef] [PubMed]
  68. Luna, E.; Bruce, T.J.; Roberts, M.R.; Flors, V.; Ton, J. Next-generation systemic acquired resistance. Plant Physiol. 2012, 158, 844–853. [Google Scholar] [CrossRef] [Green Version]
  69. Carvalhais, L.C.; Dennis, P.G.; Badri, D.V.; Kidd, B.N.; Schenk, P.M. Linking Jasmonic Acid Signaling, Root Exudates, and Rhizosphere Microbiomes. Mol. Plant-Microbe Interact. 2015, 28, 1049. [Google Scholar] [CrossRef] [Green Version]
  70. Lebeis, S.L.; Paredes, S.H.; Lundberg, D.S.; Breakfield, N.; Gehring, J.; McDonald, M.; Malfatti, S.; Glavina del Rio, T.; Jones, C.D.; Tringe, S.G.; et al. Salicylic acid modulates colonization of the root microbiome by specific bacterial taxa. Science 2015, 349, 860–864. [Google Scholar] [CrossRef] [Green Version]
  71. Donn, S.; Kirkegaard, J.A.; Perera, G.; Richardson, A.E.; Watt, M. Evolution of bacterial communities in the wheat crop rhizosphere. Environ. Microbiol. 2014, 17, 610–621. [Google Scholar] [CrossRef] [PubMed]
  72. Yin, C.; Schlatter, D.; Schroeder, K.; Mueth, N.; Paulitz, T.C. Bacterial Communities on Wheat Grown Under Long-Term Conventional Tillage and No-Till in the Pacific Northwest of the United States. Phytobiomes J. 2017, 1, 83–90. [Google Scholar] [CrossRef]
  73. Hartman, K.; van der Heijden, M.G.; Wittwer, R.L.A.; Banerjee, S.; Walser, J.C.; Schlaeppi, K. Cropping practices manipulate abundance patterns of root and soil microbiome members paving the way to smart farming. Microbiome 2018, 6, 14. [Google Scholar] [CrossRef] [PubMed]
  74. Mavrodi, D.V.; Mavrodi, O.V.; Elbourne, L.; Sasha, T.; Bonsall, R.F.; James, P.; Yang, M.; Paulsen, I.T.; Weller, D.M.; Thomashow, L.S. Long-Term Irrigation Affects the Dynamics and Activity of the Wheat Rhizosphere Microbiome. Front. Plant Sci. 2018, 9, 345. [Google Scholar] [CrossRef] [PubMed]
  75. Lundberg, D.S.; Lebeis, S.L.; Paredes, S.H.; Yourstone, S.; Gehring, J.; Malfatti, S.; Tremblay, J.; Engelbrektson, A.; Kunin, V.; Del Rio, T.G.; et al. Defining the core Arabidopsis thaliana root microbiome. Nature 2012, 488, 86–90. [Google Scholar] [CrossRef] [Green Version]
  76. Marie, S.; Cindy, D.; Valeria, T.; Ngonkeu, E.; Diégane, D.; Aboubacry, K.; Gilles, B.; Lionel, M. Influence of plant genotype and soil on the wheat rhizosphere microbiome: Evidences for a core microbiome across eight African and European soils. FEMS Microbiol. Ecol. 2020, 96, fiaa067. [Google Scholar]
  77. Aira, M.; Gómez-Brandón, M.; Lazcano, C.; BaaTh, E.; Domínguez, J. Plant genotype strongly modifies the structure and growth of maize rhizosphere microbial communities. Soil Biol. Biochem. 2010, 42, 2276–2281. [Google Scholar] [CrossRef]
  78. Lamit, L.J. COS 42-3: Different cottonwood genotypes support different aboveground fungal communities: A genetic basis to community structure. In Proceedings of the The ESA/SER Joint Meeting, San Jose, CA, USA, 5–10 August 2007. [Google Scholar]
  79. Jiang, Y.; Li, S.; Li, R.; Zhang, J.; Liu, Y.; Lv, L.; Zhu, H.; Wu, W.; Li, W. Plant cultivars imprint the rhizosphere bacterial community composition and association networks. Soil Biol. Biochem. 2017, 109, 145–155. [Google Scholar] [CrossRef]
  80. Macdonald, L.M.; Paterson, E.; Dawson, L.A.; Mcdonald, A. Defoliation and fertiliser influences on the soil microbial community associated with two contrasting Lolium perenne cultivars. Soil Biol. Biochem. 2006, 38, 674–682. [Google Scholar] [CrossRef]
  81. Hou, D.; Wang, R.; Gao, X.; Wang, K.; Lin, Z.; Ge, J.; Liu, T.; Wei, S.; Chen, W.; Xie, R. Cultivar-specific response of bacterial community to cadmium contamination in the rhizosphere of rice (Oryza sativa L.). Environ. Pollut. 2018, 241, 63–73. [Google Scholar] [CrossRef]
  82. Edwards, J.; Johnson, C.; Santos-Medellín, C.; Lurie, E.; Sundaresan, V. Structure, variation, and assembly of the root-associated microbiomes of rice. Proc. Natl. Acad. Sci. USA 2015, 112, E911–E920. [Google Scholar] [CrossRef] [Green Version]
  83. Huang, X.P.; Mo, C.H.; Yu, J.; Zhao, H.M.; Meng, C.; Li, Y.W.; Li, H.; Cai, Q.Y.; Wong, M.H. Variations in microbial community and ciprofloxacin removal in rhizospheric soils between two cultivars of Brassica parachinensis L. Sci. Total Environ. 2017, 603–604, 66–76. [Google Scholar] [CrossRef] [PubMed]
  84. Xue; Huang; Xd, Changes in soil microbial community structure with planting years and cultivars of tree peony (Paeonia suffruticosa). World J. Microb. Biot. 2014, 30, 389–397. [CrossRef] [PubMed]
  85. Zhou, X.; Guan, S.; Wu, F. Composition of soil microbial communities in the rhizosphere of cucumber cultivars with differing nitrogen acquisition efficiency. Appl. Soil Ecol. 2015, 95, 90–98. [Google Scholar] [CrossRef]
  86. Mahoney, A.K.; Yin, C.; Hulbert, S.H. Community Structure, Species Variation, and Potential Functions of Rhizosphere-Associated Bacteria of Different Winter Wheat (Triticum aestivum) Cultivars. Front. Plant Sci. 2017, 8, 132. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  87. Liu, H.; Brettell, L.E. Plant Defense by VOC-Induced Microbial Priming—ScienceDirect. Trends Plant Sci. 2019, 24, 187–189. [Google Scholar] [CrossRef]
  88. Bakker, P.; Pieterse, C.; Jonge, R.D.; Berendsen, R.L. The Soil-Borne Legacy. Cell 2018, 172, 1178–1180. [Google Scholar] [CrossRef] [Green Version]
  89. Carrión, V.; Perez-Jaramillo, J.; Cordovez, V.; Tracanna, V.; Raaijmakers, J.M. Pathogen-induced activation of disease-suppressive functions in the endophytic root microbiome. Science 2019, 366, 606–612. [Google Scholar] [CrossRef]
  90. Mendes, L.W.; Raaijmakers, J.M.; de Hollander, M.; Mendes, R.; Tsai, S.M. Influence of resistance breeding in common bean on rhizosphere microbiome composition and function. ISME J. 2018, 12, 212–224. [Google Scholar] [CrossRef]
  91. Chiang, Y.M.; Chang, S.L.; Oakley, B.R.; Wang, C.C. Recent advances in awakening silent biosynthetic gene clusters and linking orphan clusters to natural products in microorganisms. Curr. Opin. Chem. Biol. 2011, 15, 137–143. [Google Scholar] [CrossRef] [Green Version]
  92. Fil, M.; Velasco-Rodríguez, Ó.; García-Calvo, L.; Sola-Landa, A.; Barreiro, C. Screening of Antibiotic Gene Clusters in Microorganisms Isolated from Wood. Methods Mol. Biol. 2021, 2296, 151–165. [Google Scholar] [PubMed]
  93. Mathesius, H.U. The role of flavonoids in root-rhizosphere signalling: Opportunities and challenges for improving plant-microbe interactions. J. Exp. Bot. 2012, 63, 3429–3444. [Google Scholar]
  94. Kudjordjie, E.N.; Sapkota, R.; Steffensen, S.K.; Fomsgaard, I.S.; Nicolaisen, M. Maize synthesized benzoxazinoids affect the host associated microbiome. Microbiome 2019, 7, 59. [Google Scholar] [CrossRef] [PubMed]
  95. Lanoue, A.; Burlat, V.; Henkes, G.J.; Koch, I.; Schurr, U.; Röse, U.S. De novo biosynthesis of defense root exudates in response to Fusarium attack in barley. New Phytol. 2010, 185, 577–588. [Google Scholar] [CrossRef] [PubMed]
  96. Huang, A.C.; Jiang, T.; Liu, Y.X.; Bai, Y.C.; Reed, J.; Qu, B.; Goossens, A.; Nützmann, H.W.; Bai, Y.; Osbourn, A. A specialized metabolic network selectively modulates Arabidopsis root microbiota. Science 2019, 364, 546. [Google Scholar] [CrossRef]
  97. Van Deynze, A.; Zamora, P.; Delaux, P.M.; Heitmann, C.; Jayaraman, D.; Rajasekar, S.; Graham, D.; Maeda, J.; Gibson, D.; Schwartz, K.D.; et al. Nitrogen fixation in a landrace of maize is supported by a mucilage-associated diazotrophic microbiota. PLoS Biol. 2018, 16, e2006352. [Google Scholar] [CrossRef] [Green Version]
  98. Schulz-Bohm, K.; Gerards, S.; Hundscheid, M.; Melenhorst, J.; de Boer, W.; Garbeva, P. Calling from distance: Attraction of soil bacteria by plant root volatiles. ISME J. 2018, 12, 1252–1262. [Google Scholar] [CrossRef] [Green Version]
  99. Nchgesang, S.M.; Strehmel, N.; Schmidt, S.; Westphal, L.; Taruttis, F.; Müller, E.; Herklotz, S.; Neumann, S.; Scheel, D. Natural variation of root exudates in Arabidopsis thaliana-linking metabolomic and genomic data. Sci. Rep. 2016, 6, 29033. [Google Scholar] [CrossRef]
  100. Carvalhais, L.C.; Dennis, P.G.; Fan, B.; Fedoseyenko, D.; Borriss, R. Linking Plant Nutritional Status to Plant-Microbe Interactions. PLoS ONE 2013, 8, e68555. [Google Scholar]
  101. Jrg, Z.; Stephan, S.; Ranju, C.; Jens, M.; Christoph, B.; Nadine, S.; Dierk, S.; Steffen, A. Non-targeted profiling of semi-polar metabolites in Arabidopsis root exudates uncovers a role for coumarin secretion and lignification during the local response to phosphate limitation. J. Exp. Bot. 2016, 67, 1421–1432. [Google Scholar]
  102. Ziegler, J.; Schmidt, S.; Strehmel, N.; Scheel, D.; Abel, S. Arabidopsis Transporter ABCG37/PDR9 contributes primarily highly oxygenated Coumarins to Root Exudation. Sci. Rep. 2017, 7, 3704. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  103. Brunner, H.I. Exudation of organic acid anions from poplar roots after exposure to Al, Cu and Zn. Tree Physiol. 2007, 27, 313. [Google Scholar]
  104. Howard, B.E.; Hu, Q.; Babaoglu, A.C.; Chandra, M.; Borghi, M.; Tan, X.; He, L.; Winter-Sederoff, H.; Gassmann, W.; Veronese, P.; et al. High-Throughput RNA Sequencing of Pseudomonas-Infected Arabidopsis Reveals Hidden Transcriptome Complexity and Novel Splice Variants. PLoS ONE 2013, 8, e74183. [Google Scholar]
  105. Mandadi, K.K.; Scholthof, K.B.G. Genome-Wide Analysis of Alternative Splicing Landscapes Modulated during Plant-Virus Interactions in Brachypodium distachyon. Plant Cell 2015, 27, 71–85. [Google Scholar] [CrossRef] [Green Version]
  106. Juan, S.; Hui, L.; Huifu, Z.; Chunxia, Z.; Yuxing, X.; Shibo, W.; Jinfeng, Q.; Jing, L.; Christian, H.; Jianqiang, W. Transcriptomics and Alternative Splicing Analyses Reveal Large Differences between Maize Lines B73 and Mo17 in Response to Aphid Rhopalosiphum padi Infestation. Front. Plant Sci. 2017, 8, 1738. [Google Scholar]
  107. Zheng, Y.; Wang, Y.; Ding, B.; Fei, Z. Comprehensive Transcriptome Analyses Reveal that Potato Spindle Tuber Viroid Triggers Genome-Wide Changes in Alternative Splicing, Inducible trans-Acting Activity of Phased Secondary Small Interfering RNAs, and Immune Responses. J. Virol. 2017, 91, e00247-17. [Google Scholar] [CrossRef] [Green Version]
  108. Chen, M.X.; Zhang, K.L.; Zhang, M.; Das, D.; Zhu, F.Y. Alternative splicing and its regulatory role in woody plants. Tree Physiol. 2020, 40, 1475–1486. [Google Scholar] [CrossRef]
  109. Chen, M.X.; Zhu, F.Y.; Gao, B.; Ma, K.L.; Zhang, Y.; Fernie, A.R.; Chen, X.; Dai, L.; Ye, N.H.; Zhang, X.; et al. Full-Length Transcript-Based Proteogenomics of Rice Improves Its Genome and Proteome Annotation. Plant Physiol. 2020, 182, 1510–1526. [Google Scholar] [CrossRef]
  110. Kuang, Z.; Boeke, J.D.; Canzar, S. The dynamic landscape of fission yeast meiosis alternative-splice isoforms. Genome Res. 2017, 27, 145–156. [Google Scholar] [CrossRef] [Green Version]
  111. Chen, M.X.; Mei, L.C.; Wang, F.; Boyagane Dewayalage, I.K.W.; Yang, J.F.; Dai, L.; Yang, G.F.; Gao, B.; Cheng, C.L.; Liu, Y.G.; et al. PlantSPEAD: A web resource towards comparatively analysing stress-responsive expression of splicing-related proteins in plant. Plant Biotechnol. J. 2021, 19, 227–229. [Google Scholar] [CrossRef]
  112. Gillet, L.C.; Navarro, P.; Tate, S.; Röst, H.; Selevsek, N.; Reiter, L.; Bonner, R.; Aebersold, R. Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: A new concept for consistent and accurate proteome analysis. Mol. Cell. Proteom. 2012, 11, O111.016717. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  113. Chen, M.X.; Zhang, Y.; Fernie, A.R.; Liu, Y.G.; Zhu, F.Y. SWATH-MS-Based Proteomics: Strategies and Applications in Plants. Trends Biotechnol. 2021, 39, 433–437. [Google Scholar] [CrossRef] [PubMed]
  114. Zhu, F.Y.; Chen, M.X.; Ye, N.H.; Shi, L.; Ma, K.L.; Yang, J.F.; Cao, Y.Y.; Zhang, Y.; Yoshida, T.; Fernie, A.R.; et al. Proteogenomic analysis reveals alternative splicing and translation as part of the abscisic acid response in Arabidopsis seedlings. Plant J. 2017, 91, 518–533. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  115. Park, C.J.; Han, S.W.; Chen, X.; Ronald, P.C. Elucidation of XA21-mediated innate immunity. Cell Microbiol. 2010, 12, 1017–1025. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  116. Thomas, N.C.; Schwessinger, B.; Liu, F.; Chen, H.; Wei, T.; Nguyen, Y.P.; Shaker, I.W.F.; Ronald, P.C. XA21-specific induction of stress-related genes following Xanthomonas infection of detached rice leaves. PeerJ 2016, 4, e2446. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  117. Wang, X.; Zafian, P.; Choudhary, M.; Lawton, M. The PR5K receptor protein kinase from Arabidopsis thaliana is structurally related to a family of plant defense proteins. Proc. Natl. Acad. Sci. USA 1996, 93, 2598–2602. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  118. Di Gaspero, G.; Cipriani, G. Nucleotide binding site/leucine-rich repeats, Pto-like and receptor-like kinases related to disease resistance in grapevine. Mol. Genet. Genom. 2003, 269, 612–623. [Google Scholar] [CrossRef]
  119. Pilotti, M.; Brunetti, A.; Uva, P.; Lumia, V.; Tizzani, L.; Gervasi, F.; Iacono, M.; Pindo, M. Kinase domain-targeted isolation of defense-related receptor-like kinases (RLK/Pelle) in Platanus×acerifolia: Phylogenetic and structural analysis. BMC Res. Notes 2014, 7, 884. [Google Scholar] [CrossRef] [Green Version]
  120. Cheng, Q.; Xiao, H.; Xiong, Q. Conserved exitrons of FLAGELLIN-SENSING 2 (FLS2) across dicot plants and their functions. Plant Sci. 2020, 296, 110507. [Google Scholar] [CrossRef]
  121. Li, L.; Li, M.; Yu, L.; Zhou, Z.; Liang, X.; Liu, Z.; Cai, G.; Gao, L.; Zhang, X.; Wang, Y.; et al. The FLS2-associated kinase BIK1 directly phosphorylates the NADPH oxidase RbohD to control plant immunity. Cell Host Microbe 2014, 15, 329–338. [Google Scholar] [CrossRef] [Green Version]
  122. Zhanga, Y.; Li, X. A Putative Nucleoporin 96 Is Required for Both Basal Defense and Constitutive Resistance Responses Mediated by suppressor of npr1-1, constitutive 1. Plant Cell 2005, 17, 1306–1316. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  123. Zhang, Z.; Liu, Y.; Ding, P.; Yan, L.; Kong, Q.; Zhang, Y. Splicing of Receptor-Like Kinase-Encoding SNC4 and CERK1 is Regulated by Two Conserved Splicing Factors that Are Required for Plant Immunity. Mol. Plant 2014, 7, 1766–1775. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  124. Zhao, Z.; Li, Y.; Liu, H.; Zhai, X.; Deng, M.; Dong, Y.; Fan, G. Genome-wide expression analysis of salt-stressed diploid and autotetraploid Paulownia tomentosa. PLoS ONE 2017, 12, e0185455. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  125. Ding, Y.; Wang, Y.; Qiu, C.; Qian, W.; Xie, H.; Ding, Z. Alternative splicing in tea plants was extensively triggered by drought, heat and their combined stresses. PeerJ 2020, 8, e8258. [Google Scholar] [CrossRef]
  126. Zhang, X.C.; Gassmann, W. RPS4-mediated disease resistance requires the combined presence of RPS4 transcripts with full-length and truncated open reading frames. Plant Cell 2003, 15, 2333–2342. [Google Scholar] [CrossRef]
  127. Whitham, S.; Dinesh-Kumar, S.P.; Choi, D.; Hehl, R.; Corr, C.; Baker, B. The product of the tobacco mosaic virus resistance gene N: Similarity to toll and the interleukin-1 receptor. Cell 1994, 1, S163–S164. [Google Scholar] [CrossRef]
  128. Erickson, F.L.; Holzberg, S.; Calderon-Urrea, A.; Handley, V.; Baker, B. The helicase domain of the TMV replicase proteins induces the N-mediated defence response in tobacco. Plant J. 2010, 18, 67–75. [Google Scholar] [CrossRef]
  129. Chen, M.X.; Zhang, K.L.; Gao, B.; Yang, J.F.; Tian, Y.; Das, D.; Fan, T.; Dai, L.; Hao, G.F.; Yang, G.F.; et al. Phylogenetic comparison of 5’ splice site determination in central spliceosomal proteins of the U1-70K gene family, in response to developmental cues and stress conditions. Plant J. 2020, 103, 357–378. [Google Scholar] [CrossRef]
  130. Shen, C.C.; Chen, M.X.; Xiao, T.; Zhang, C.; Shang, J.; Zhang, K.L.; Zhu, F.Y. Global proteome response to Pb(II) toxicity in poplar using SWATH-MS-based quantitative proteomics investigation. Ecotoxicol. Environ. Saf. 2021, 220, 112410. [Google Scholar] [CrossRef]
  131. Kissen, R.; Hyldbakk, E.; Wang, C.W.V.; Sørmo, C.G.; Rossiter, J.T.; Bones, A.M. Ecotype dependent expression and alternative splicing of epithiospecifier protein (ESP) in Arabidopsis thaliana. Plant Mol. Biol. 2012, 78, 361–375. [Google Scholar] [CrossRef]
  132. Chen, Q.; Han, Y.; Liu, H.; Wang, X.; Sun, J.; Zhao, B.; Li, W.; Tian, J.; Liang, Y.; Yan, J.; et al. Genome-Wide Association Analyses Reveal the Importance of Alternative Splicing in Diversifying Gene Function and Regulating Phenotypic Variation in Maize. Plant Cell 2018, 30, 1404–1423. [Google Scholar] [CrossRef] [PubMed] [Green Version]
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Figure 1. Summary model and research gaps among plant ecotypes, commensal microbiota, and alternative splicing-associated quantitative trait loci. Ecotype-specific microbial recruitment, and hypothesized relationship between plant induced alternatively spliced genes. Different plants, different genotypes, and different stresses will all release different root secretions and recruit microorganisms according to their needs to build their own unique communities in response to certain biotic or abiotic stresses. There is much evidence that PRRs in many plants are associated with AS. However, with different stresses, different plants have different preferences for AS, and different ecotypes of plants have differences in sQTLs that are enriched in flowering and stress response genes. Therefore, we speculate that alternative splicing is somehow associated with expression shape regulation and microbial recruitment, and plant-induced gene expression.
Figure 1. Summary model and research gaps among plant ecotypes, commensal microbiota, and alternative splicing-associated quantitative trait loci. Ecotype-specific microbial recruitment, and hypothesized relationship between plant induced alternatively spliced genes. Different plants, different genotypes, and different stresses will all release different root secretions and recruit microorganisms according to their needs to build their own unique communities in response to certain biotic or abiotic stresses. There is much evidence that PRRs in many plants are associated with AS. However, with different stresses, different plants have different preferences for AS, and different ecotypes of plants have differences in sQTLs that are enriched in flowering and stress response genes. Therefore, we speculate that alternative splicing is somehow associated with expression shape regulation and microbial recruitment, and plant-induced gene expression.
Ijms 23 04860 g001
Table
Table 1. A comparison of some representative microbial communities of different genotypes and a comparison of alternative splicing of plants of different ecotypes is summarized.
Table 1. A comparison of some representative microbial communities of different genotypes and a comparison of alternative splicing of plants of different ecotypes is summarized.
Plant VarietiesGenotype VarietiesRegionReproductive StagesResult
WheatApache (AP), Bermude (BM), Carstens (CT), Champlein (CH), Cheyenne (CY), Rubisko (RB), Soissons (SS), Terminillo ™Senegal, Cameroon, France, and ItalyHarvest seasonPlant genotypes and soil have specific effects on the wheat rhizosphere microbial community.
RiceZhefu No. 7, hereafter: HA, Xiangzaoxian No. 45, hereafter: LAZhejiang Province, ChinaHarvest seasonSignificant differences in the composition of inter-root bacterial communities of different rice varieties.
SoybeanKwangan (KA), Poongsannamul (PS), Poongwon (PW),
and Taekwang (TK)		Jeonju, South KoreaR1, R3, R5, and R7Influenced by the variety and growth stage.
Winter WheatEltan, Finch, Hill81,Lewjain, Madsen,
PI561722, PI561725,
PI561726 and PI561727		Pullman,
WA, USA.		Late May to early June, 2010 and 2014Wheat cultivars are involved in shaping the rhizosphere
by differentially altering the bacterial OTUs consistently across different sites.
MaizeZhengdan 958 (ZD), Gaoneng 1(G1), and Gaoneng 2 (G2)Hebei province, China18 September 2017The bacterial community structure in bulk soil of different cultivars was significantly different.
Rabbiteye
blueberry		Clearly clustered into three groups (BRI, BRII, and RBIII).Lishui, Nanjing province, ChinaHarvest SeasonThe rhizosphere from the plant
cultivars exerted substantial effects on bacterial association networks and putative keystone species.
TomatoResistant varieties and non-resistant varietiesSeoul, Republic of Korea.Harvest seasonMore abundant in the resistant plant rhizosphere microbiome than in that of the susceptible plant.
BeanResistant varieties and non-resistant varietiesAnhembi municipality, Sao Paulo, BrazilHarvest seasonDifferent levels of resistance to the fungal root pathogen Fusarium (Fox), differences in microbial composition.
Plant VarietiesGenotype VarietiesUnique Splicing
quantitative trait
loci (sQTL)		Reproductive StagesResult
Arabidopsis thaliana666 geographically distributed
diverse ecotypes		6406/A role for differential isoform usage in regulating these important processes in diverse ecotypes of Arabidopsis.
MaizeMaize kernels from
368 inbred lines		19,554/The importance of AS in diversifying gene function and regulating phenotypic variation.
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Li, Y.-H.; Yang, Y.-Y.; Wang, Z.-G.; Chen, Z. Emerging Function of Ecotype-Specific Splicing in the Recruitment of Commensal Microbiome. Int. J. Mol. Sci. 2022, 23, 4860. https://doi.org/10.3390/ijms23094860

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Li Y-H, Yang Y-Y, Wang Z-G, Chen Z. Emerging Function of Ecotype-Specific Splicing in the Recruitment of Commensal Microbiome. International Journal of Molecular Sciences. 2022; 23(9):4860. https://doi.org/10.3390/ijms23094860

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Li, Yue-Han, Yuan-You Yang, Zhi-Gang Wang, and Zhuo Chen. 2022. "Emerging Function of Ecotype-Specific Splicing in the Recruitment of Commensal Microbiome" International Journal of Molecular Sciences 23, no. 9: 4860. https://doi.org/10.3390/ijms23094860

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