Insights to plant–microbe interactions provide opportunities to improve resistance breeding against root diseases in grain legumes

Root and foot diseases severely impede grain legume cultivation worldwide. Breeding lines with resistance against individual pathogens exist, but these resistances are often overcome by the interaction of multiple pathogens in field situations. Novel tools allow to decipher plant–microbiome interactions in unprecedented detail and provide insights into resistance mechanisms that consider both simultaneous attacks of various pathogens and the interplay with beneficial microbes. Although it has become clear that plant‐associated microbes play a key role in plant health, a systematic picture of how and to what extent plants can shape their own detrimental or beneficial microbiome remains to be drawn. There is increasing evidence for the existence of genetic variation in the regulation of plant–microbe interactions that can be exploited by plant breeders. We propose to consider the entire plant holobiont in resistance breeding strategies in order to unravel hidden parts of complex defence mechanisms. This review summarizes (a) the current knowledge of resistance against soil‐borne pathogens in grain legumes, (b) evidence for genetic variation for rhizosphere‐related traits, (c) the role of root exudation in microbe‐mediated disease resistance and elaborates (d) how these traits can be incorporated in resistance breeding programmes.     

拟南芥与叶际微生物组的互作遗传机制——基于网络作图理论

叶际微生物组对植物的生长发育至关重要，但植物与其定殖微生物组相互作用机制尚不明确。目前植物与微生物互作研究多集中于根际微生物组，对叶际微生物组的研究较少，且这些研究未能从微生物互作的角度探究植物与微生物的相互作用机理。基于网络作图理论，将拟南芥基因组SNP （Single Nucleotide Polymorphisms）分子标记数据与微生物组网络特征值相关联，挖掘影响叶际微生物组网络结构的枢纽基因，以探究拟南芥塑造叶际微生物组网络结构的遗传机制。通过对188株拟南芥及其叶际微生物组数据的分析，识别出四种关系下的中心节点微生物，筛选到622个显著SNP位点。进一步构建了贝叶斯遗传网络，获得26个枢纽基因，这些基因可能参与了植物抗病、激素分泌和生长发育相关的分子途径。本研究从全基因组角度探究植物调控自身微生物组的遗传机制，揭示植物与微生物组如何互作促进植物健康，将为精准分子育种提供理论基础和遗传资源，并为合成菌群用于创制新型菌剂提供数据支持，具有重要的科学意义和应用价值。     

Microbiome-mediated signal transduction within the plant holobiont

Microorganisms colonizing the plant rhizosphere and phyllosphere play crucial roles in plant growth and health. Recent studies provide new insights into long-distance communication from plant roots to shoots in association with their commensal microbiome. In brief, these recent advances suggest that specific plant-associated microbial taxa can contribute to systemic plant responses associated with the enhancement of plant health and performance in face of a variety of biotic and abiotic stresses. However, most of the mechanisms associated with microbiome-mediated signal transduction in plants remain poorly understood. In this review, we provide an overview of long-distance signaling mechanisms within plants mediated by the commensal plant-associated microbiomes. We advocate the view of plants and microbes as a holobiont and explore key molecules and mechanisms associated with plant–microbe interactions and changes in plant physiology activated by signal transduction.     

Genome wide association study reveals plant loci controlling heritability of the rhizosphere microbiome

Host genetics has recently been shown to be a driver of plant microbiome composition. However, identifying the underlying genetic loci controlling microbial selection remains challenging. Genome-wide association studies (GWAS) represent a potentially powerful, unbiased method to identify microbes sensitive to the host genotype and to connect them with the genetic loci that influence their colonization. Here, we conducted a population-level microbiome analysis of the rhizospheres of 200 sorghum genotypes. Using 16S rRNA amplicon sequencing, we identify rhizosphere-associated bacteria exhibiting heritable associations with plant genotype, and identify significant overlap between these lineages and heritable taxa recently identified in maize. Furthermore, we demonstrate that GWAS can identify host loci that correlate with the abundance of specific subsets of the rhizosphere microbiome. Finally, we demonstrate that these results can be used to predict rhizosphere microbiome structure for an independent panel of sorghum genotypes based solely on knowledge of host genotypic information.Subject terms: Agricultural genetics, Plant ecology, Soil microbiology     

The Sphagnum microbiome supports bog ecosystem functioning under extreme conditions

Sphagnum‐dominated bogs represent a unique yet widely distributed type of terrestrial ecosystem and strongly contribute to global biosphere functioning. Sphagnum is colonized by highly diverse microbial communities, but less is known about their function. We identified a high functional diversity within the Sphagnum microbiome applying an Illumina‐based metagenomic approach followed by de novo assembly and MG‐RAST annotation. An interenvironmental comparison revealed that the Sphagnum microbiome harbours specific genetic features that distinguish it significantly from microbiomes of higher plants and peat soils. The differential traits especially support ecosystem functioning by a symbiotic lifestyle under poikilohydric and ombrotrophic conditions. To realise a plasticity–stability balance, we found abundant subsystems responsible to cope with oxidative and drought stresses, to exchange (mobile) genetic elements, and genes that encode for resistance to detrimental environmental factors, repair and self‐controlling mechanisms. Multiple microbe–microbe and plant–microbe interactions were also found to play a crucial role as indicated by diverse genes necessary for biofilm formation, interaction via quorum sensing and nutrient exchange. A high proportion of genes involved in nitrogen cycle and recycling of organic material supported the role of bacteria for nutrient supply. 16S rDNA analysis indicated a higher structural diversity than that which had been previously detected using PCR‐dependent techniques. Altogether, the diverse Sphagnum microbiome has the ability to support the life of the host plant and the entire ecosystem under changing environmental conditions. Beyond this, the moss microbiome presents a promising bio‐resource for environmental biotechnology – with respect to novel enzymes or stress‐protecting bacteria.     

Understanding and engineering beneficial plant–microbe interactions: plant growth promotion in energy crops

Plant production systems globally must be optimized to produce stable high yields from limited land under changing and variable climates. Demands for food, animal feed, and feedstocks for bioenergy and biorefining applications, are increasing with population growth, urbanization and affluence. Low‐input, sustainable, alternatives to petrochemical‐derived fertilizers and pesticides are required to reduce input costs and maintain or increase yields, with potential biological solutions having an important role to play. In contrast to crops that have been bred for food, many bioenergy crops are largely undomesticated, and so there is an opportunity to harness beneficial plant–microbe relationships which may have been inadvertently lost through intensive crop breeding. Plant–microbe interactions span a wide range of relationships in which one or both of the organisms may have a beneficial, neutral or negative effect on the other partner. A relatively small number of beneficial plant–microbe interactions are well understood and already exploited; however, others remain understudied and represent an untapped reservoir for optimizing plant production. There may be near‐term applications for bacterial strains as microbial biopesticides and biofertilizers to increase biomass yield from energy crops grown on land unsuitable for food production. Longer term aims involve the design of synthetic genetic circuits within and between the host and microbes to optimize plant production. A highly exciting prospect is that endosymbionts comprise a unique resource of reduced complexity microbial genomes with adaptive traits of great interest for a wide variety of applications.     

Crop genome‐wide association study: a harvest of biological relevance

With the advent of rapid genotyping and next‐generation sequencing technologies, genome‐wide association study (GWAS) has become a routine strategy for decoding genotype–phenotype associations in many species. More than 1000 such studies over the last decade have revealed substantial genotype–phenotype associations in crops and provided unparalleled opportunities to probe functional genomics. Beyond the many ‘hits’ obtained, this review summarizes recent efforts to increase our understanding of the genetic architecture of complex traits by focusing on non‐main effects including epistasis, pleiotropy, and phenotypic plasticity. We also discuss how these achievements and the remaining gaps in our knowledge will guide future studies. Synthetic association is highlighted as leading to false causality, which is prevalent but largely underestimated. Furthermore, validation evidence is appealing for future GWAS, especially in the context of emerging genome‐editing technologies.     

Importance of plant‐ and microbe‐driven metabolic pathways for plant defence

Expression of plant phenotypes can depend on both plant genomes and interactions between plants and the microbes living in, on and near their roots. We understand a growing number of the mechanistic links between plant genotypes and phenotypes, such as defence against herbivory (see brief review in Hubbard et al., 2019), yet the links between root microbiomes and the comprehensive swathe of plant phenotypes they affect (Friesen et al., 2011) remain less clear. In this issue of Molecular Ecology, Hubbard et al. (2019) follow microbe‐ and plant‐driven changes in plant defence against hervibory from molecular underpinnings to ecological consequences, contrasting both the metabolites affected and the magnitude of defensive impact. Naively, we might expect plant genomes to drive more variation in phenotype than the root microbiome, but Hubbard et al. (2019) find the opposite, implying profound consequences for plant trait evolution and ecological interactions.     

Metabolic GWAS‐based dissection of genetic bases underlying the diversity of plant metabolism

Plants have served as sources providing humans with metabolites for food and nutrition, biomaterials for living, and treatment for pain and disease. Plants produce a huge array of metabolites, with an immense diversity at both the population and individual levels. Dissection of the genetic bases for metabolic diversity has attracted increasing research attention. The concept of genome‐wide association study (GWAS) was extended to studies on the diversity of plant metabolome that benefitted from the development of mass‐spectrometry‐based analytical systems and genome sequencing technologies. Metabolic genome‐wide association study (mGWAS) is one of the most powerful tools for global identification of genetic determinants for diversity of plant metabolism. Recently, mGWAS has been performed for various species with continuous improvements, providing deeper insights into the genetic bases of metabolic diversity. In this review, we discuss fully the achievements to date and remaining challenges that are associated with both mGWAS and mGWAS‐based multi‐dimensional analysis. We begin with a summary of GWAS and its development based on statistical methods and populations. As variation in targeted traits is essential for GWAS, we review metabolic diversity and its rise at both the population and individual levels. Subsequently, the application of mGWAS for plants and its corresponding achievements are fully discussed. We address the current knowledge on mGWAS‐based multi‐dimensional analysis and emerging insights into the diversity of metabolism.     

Overview of the rules of the microbial engagement in the gut microbiome: a step towards microbiome therapeutics

Human gut microbiome is a diversified, resilient, immuno-stabilized, metabolically active and physiologically essential component of the human body. Scientific explorations have been made to seek in-depth information about human gut microbiome establishment, microbiome functioning, microbiome succession, factors influencing microbial community dynamics and the role of gut microbiome in health and diseases. Extensive investigations have proposed the microbiome therapeutics as a futuristic medicine for various physiological and metabolic disorders. A comprehensive outlook of microbial colonization, host–microbe interactions, microbial adaptation, commensal selection and immuno-survivability is still required to catalogue the essential genetic and physiological features for the commensal engagement. Evolution of a structured human gut microbiome relies on the microbial flexibility towards genetic, immunological and physiological adaptation in the human gut. Key features for commensalism could be utilized in developing tailor-made microbiome-based therapy to overcome various physiological and metabolic disorders. This review describes the key genetics and physiological traits required for host–microbe interaction and successful commensalism to institute a human gut microbiome.     

Extreme‐phenotype genome‐wide association study (XP‐GWAS): a method for identifying trait‐associated variants by sequencing pools of individuals selected from a diversity panel

Although approaches for performing genome‐wide association studies (GWAS) are well developed, conventional GWAS requires high‐density genotyping of large numbers of individuals from a diversity panel. Here we report a method for performing GWAS that does not require genotyping of large numbers of individuals. Instead XP‐GWAS (extreme‐phenotype GWAS) relies on genotyping pools of individuals from a diversity panel that have extreme phenotypes. This analysis measures allele frequencies in the extreme pools, enabling discovery of associations between genetic variants and traits of interest. This method was evaluated in maize (Zea mays) using the well‐characterized kernel row number trait, which was selected to enable comparisons between the results of XP‐GWAS and conventional GWAS. An exome‐sequencing strategy was used to focus sequencing resources on genes and their flanking regions. A total of 0.94 million variants were identified and served as evaluation markers; comparisons among pools showed that 145 of these variants were statistically associated with the kernel row number phenotype. These trait‐associated variants were significantly enriched in regions identified by conventional GWAS. XP‐GWAS was able to resolve several linked QTL and detect trait‐associated variants within a single gene under a QTL peak. XP‐GWAS is expected to be particularly valuable for detecting genes or alleles responsible for quantitative variation in species for which extensive genotyping resources are not available, such as wild progenitors of crops, orphan crops, and other poorly characterized species such as those of ecological interest.     

Genotypic variation in Norway spruce correlates to fungal communities in vegetative buds

The taxonomically diverse phyllosphere fungi inhabit leaves of plants. Thus, apart from the fungi's dispersal capacities and environmental factors, the assembly of the phyllosphere community associated with a given host plant depends on factors encoded by the host's genome. The host genetic factors and their influence on the assembly of phyllosphere communities under natural conditions are poorly understood, especially in trees. Recent work indicates that Norway spruce (Picea abies) vegetative buds harbour active fungal communities, but these are hitherto largely uncharacterized. This study combines internal transcribed spacer sequencing of the fungal communities associated with dormant vegetative buds with a genome‐wide association study (GWAS) in 478 unrelated Norway spruce trees. The aim was to detect host loci associated with variation in the fungal communities across the population, and to identify loci correlating with the presence of specific, latent, pathogens. The fungal communities were dominated by known Norway spruce phyllosphere endophytes and pathogens. We identified six quantitative trait loci (QTLs) associated with the relative abundance of the dominating taxa (i.e., top 1% most abundant taxa). Three additional QTLs associated with colonization by the spruce needle cast pathogen Lirula macrospora or the cherry spruce rust (Thekopsora areolata) in asymptomatic tissues were detected. The identification of the nine QTLs shows that the genetic variation in Norway spruce influences the fungal community in dormant buds and that mechanisms underlying the assembly of the communities and the colonization of latent pathogens in trees may be uncovered by combining molecular identification of fungi with GWAS.     

Optimising the identification of causal variants across varying genetic architectures in crops

Association studies use statistical links between genetic markers and the phenotype variation across many individuals to identify genes controlling variation in the target phenotype. However, this approach, particularly conducted on a genome‐wide scale (GWAS), has limited power to identify the genes responsible for variation in traits controlled by complex genetic architectures. In this study, we employ real‐world genotype datasets from four crop species with distinct minor allele frequency distributions, population structures and linkage disequilibrium patterns. We demonstrate that different GWAS statistical approaches provide favourable trade‐offs between power and accuracy for traits controlled by different types of genetic architectures. FarmCPU provides the most favourable outcomes for moderately complex traits while a Bayesian approach adopted from genomic prediction provides the most favourable outcomes for extremely complex traits. We assert that by estimating the complexity of genetic architectures for target traits and selecting an appropriate statistical approach for the degree of complexity detected, researchers can substantially improve the ability to dissect the genetic factors controlling complex traits such as flowering time, plant height and yield component.     

Host genetic variation strongly influences the microbiome structure and function in fungal fruiting‐bodies

Despite increasing knowledge on host‐associated microbiomes, little is known about mechanisms underlying fungus‐microbiome interactions. This study aimed to examine the relative importance of host genetic, geographic and environmental variations in structuring fungus‐associated microbiomes. We analyzed the taxonomic composition and function of microbiomes inhabiting fungal fruiting‐bodies in relation to host genetic variation, soil pH and geographic distance between samples. For this, we sequenced the metagenomes of 40 fruiting‐bodies collected from six fairy rings (i.e., genets) of a saprotrophic fungus Marasmius oreades. Our analyses revealed that fine genetic variations between host fungi could strongly affect their associated microbiome, explaining, respectively, 25% and 37% of the variation in microbiome structure and function, whereas geographic distance and soil pH remained of secondary importance. These results, together with the smaller genome size of fungi compared to other eukaryotes, suggest that fruiting‐bodies are suitable for further genome‐centric studies on host–microbiome interactions.     

Beneficial microbes going underground of root immunity

Plant roots interact with an enormous diversity of commensal, mutualistic, and pathogenic microbes, which poses a big challenge to roots to distinguish beneficial microbes from harmful ones. Plants can effectively ward off pathogens following immune recognition of conserved microbe‐associated molecular patterns (MAMPs). However, such immune elicitors are essentially not different from those of neutral and beneficial microbes that are abundantly present in the root microbiome. Recent studies indicate that the plant immune system plays an active role in influencing rhizosphere microbiome composition. Moreover, it has become increasingly clear that root‐invading beneficial microbes, including rhizobia and arbuscular mycorrhiza, evade or suppress host immunity to establish a mutualistic relationship with their host. Evidence is accumulating that many free‐living rhizosphere microbiota members can suppress root immune responses, highlighting root immune suppression as an important function of the root microbiome. Thus, the gate keeping functions of the plant immune system are not restricted to warding off root‐invading pathogens but also extend to rhizosphere microbiota, likely to promote colonization by beneficial microbes and prevent growth‐defense tradeoffs triggered by the MAMP‐rich rhizosphere environment.     

Genetic by environment interactions affect plant–soil linkages

The role of plant intraspecific variation in plant–soil linkages is poorly understood, especially in the context of natural environmental variation, but has important implications in evolutionary ecology. We utilized three 18‐ to 21‐year‐old common gardens across an elevational gradient, planted with replicates of five Populus angustifolia genotypes each, to address the hypothesis that tree genotype (G), environment (E), and G × E interactions would affect soil carbon and nitrogen dynamics beneath individual trees. We found that soil nitrogen and carbon varied by over 50% and 62%, respectively, across all common garden environments. We found that plant leaf litter (but not root) traits vary by genotype and environment while soil nutrient pools demonstrated genotype, environment, and sometimes G × E interactions, while process rates (net N mineralization and net nitrification) demonstrated G × E interactions. Plasticity in tree growth and litter chemistry was significantly related to the variation in soil nutrient pools and processes across environments, reflecting tight plant–soil linkages. These data overall suggest that plant genetic variation can have differential affects on carbon storage and nitrogen cycling, with implications for understanding the role of genetic variation in plant–soil feedback as well as management plans for conservation and restoration of forest habitats with a changing climate.     

Pleiotropy informed adaptive association test of multiple traits using genome‐wide association study summary data

Genetic variants associated with disease outcomes can be used to develop personalized treatment. To reach this precision medicine goal, hundreds of large‐scale genome‐wide association studies (GWAS) have been conducted in the past decade to search for promising genetic variants associated with various traits. They have successfully identified tens of thousands of disease‐related variants. However, in total these identified variants explain only part of the variation for most complex traits. There remain many genetic variants with small effect sizes to be discovered, which calls for the development of (a) GWAS with more samples and more comprehensively genotyped variants, for example, the NHLBI Trans‐Omics for Precision Medicine (TOPMed) Program is planning to conduct whole genome sequencing on over 100 000 individuals; and (b) novel and more powerful statistical analysis methods. The current dominating GWAS analysis approach is the “single trait” association test, despite the fact that many GWAS are conducted in deeply phenotyped cohorts including many correlated and well‐characterized outcomes, which can help improve the power to detect novel variants if properly analyzed, as suggested by increasing evidence that pleiotropy, where a genetic variant affects multiple traits, is the norm in genome‐phenome associations. We aim to develop pleiotropy informed powerful association test methods across multiple traits for GWAS. Since it is generally very hard to access individual‐level GWAS phenotype and genotype data for those existing GWAS, due to privacy concerns and various logistical considerations, we develop rigorous statistical methods for pleiotropy informed adaptive multitrait association test methods that need only summary association statistics publicly available from most GWAS. We first develop a pleiotropy test, which has powerful performance for truly pleiotropic variants but is sensitive to the pleiotropy assumption. We then develop a pleiotropy informed adaptive test that has robust and powerful performance under various genetic models. We develop accurate and efficient numerical algorithms to compute the analytical P‐value for the proposed adaptive test without the need of resampling or permutation. We illustrate the performance of proposed methods through application to joint association test of GWAS meta‐analysis summary data for several glycemic traits. Our proposed adaptive test identified several novel loci missed by individual trait based GWAS meta‐analysis. All the proposed methods are implemented in a publicly available R package.     

长白山阔叶红松林优势树种叶际真菌群落结构

森林作为陆地生态系统的主体,其林冠承载了地球上大约40%的现存物种,叶际微生物作为冠层生物多样性的重要组成部分, 在维持植物健康、提高宿主抵御能力和参与全球生物地球化学循环等生态功能中发挥着重要作用,然而相对于根际微生物,目前关于冠层叶际微生物群落组成的研究还比较缺乏。本研究以吉林省长白山自然保护区内阔叶红松林为主要研究对象,使用高通量测序技术分析6种优势树种(红松、紫椴、蒙古栎、色木槭、水曲柳、春榆)的叶际真菌群落特征,并测定宿主的14种叶片功能性状,对比研究了不同优势树种叶际真菌群落组成与功能群异同,探讨真菌群落组成与叶片功能性状的关联性。结果表明:叶际真菌的优势门和纲分别为子囊菌门、担子菌门,座囊菌纲和外囊菌纲;不同树种林冠叶际真菌组成存在明显差异。LEfSe分析表明,除春榆和色木槭外,其余树种都有显著的差异指示种,如红松的圆孢多臂菌属和蒙古栎的柱隔孢属;对比FUNGuild数据库发现,叶际真菌主要功能群为病理寄生型;冗余分析和envfit分析结果表明,与植物养分获取和抵御病虫害相关的性状是影响林冠叶际真菌群落结构的主要因子。     

Herbivore‐induced changes in flower scent and morphology affect the structure of flower–visitor networks but not plant reproduction

Herbivory induces various responses in plants, thus altering the plants’ phenotype in chemical and morphological traits. Herbivore‐induced changes in vegetative plant parts, plant‐physiological mechanisms, and effects on plant‐animal interactions have been intensively studied from species to community level. In contrast, we are just beginning to examine herbivore‐induced effects on reproductive plant parts and flower–visitor interactions, especially in a community context. We investigated the effect of herbivory at different plant developmental stages on plant growth, floral and vegetative phenotype and reproduction in Sinapis arvensis (Brassicaceae). Additionally, we tested how herbivore‐induced plant responses affect flower–visitor interactions and plant reproduction in species‐rich communities. Our results indicate that the timing of herbivory affects the magnitude of changes in plant traits. Herbivory in early but not in late development accelerated the plant's flowering phenology, reduced vegetative growth, increased stem trichome density and altered floral morphology and scent. These findings suggest age‐dependent tradeoffs between growth, defense and reproduction. Herbivore‐induced changes in flower traits also affected flower–visitor interactions in a community context with effects on the structure of flower–visitor networks. However, changes in the network structure had neglectable effects on plant reproduction, i.e. plants were able to compensate altered flower visitor behavior. Thus, herbivory is a source of intraspecific variation in reproductive traits, which can be behaviorally relevant for potential pollinators. However, plants were capable to maintain reproductive success suggesting a tolerance against herbivory. We conclude that in our study system induced direct or indirect defenses that have often been shown to decrease negative effects of herbivores on vegetative plant parts come at no costs for plant reproduction.     

Temperature and soil microorganisms interact to affect <Emphasis Type="Italic">Dodonaea viscosa</Emphasis> growth on mountainsides

There is considerable interest in understanding the drivers of plant growth in the context of climate change. Soil microorganisms play an important role in affecting plant growth and functional traits. However, the role of interaction between soil microbes and temperature in affecting plant growth and functional traits remains unclear. The objective of this research was to investigate the effects of soil microbes, temperature, and their interaction on the growth and functional traits of Dodonaea viscosa in a mountain in Yuanmou county, southwest China. The experiment was conducted in climate chambers with a factorial design of three soil microbial communities (inoculated rhizosphere microbes from high elevation, inoculated rhizosphere microbes from low elevation, and autoclaved control) and two temperature conditions (colder and warmer). D. viscosa planted in inoculated rhizosphere microbes from both high and low elevations produced more total biomass with a lower root–shoot allometric exponent, and accumulated significantly more N and P nutrients than those in an autoclaved control, with no significant differences between the two microbial inoculations. Thus, rhizosphere soil microorganisms had positive effects on D. viscosa growth. However, the effect of the microbes on plant growth strongly depended on temperature. Warming had a positive effect on D. viscosa growth in inoculated rhizosphere microbe treatments, while the positive effect disappeared in the autoclaved control treatment. Our results indicate that temperature and soil microorganisms interact to affect D. viscosa growth. As the climate changes in the future in the studied region, the growth of D. viscosa may be greatly affected both directly and indirectly through the temperature–soil microbe interaction.