Biology subjects

Ichihashi, Y.

Publications and source records attributed to Ichihashi, Y..

At least 19 recordsLinked to original sources

bioRxiv2026

Metabolome genome-wide association study reveals hierarchical and epistatic genetic control of flavonoid metabolism in soybean

Metabolic phenotypes are often governed by complex genetic architectures involving both additive and non-additive effects. However, the extent to which epistatic interactions contribute to the pathway-level regulation of plant metabolism remains unclear. In this study, we investigated the genetic architecture of flavonoid-related metabolites using metabolomic and genomic data from 200 soybean accessions cultivated under multiple environmental conditions. Broad-sense heritability estimates revealed that many metabolites were under strong genetic control, particularly flavonoid-related metabolites. Principal component analysis-based metabolome-wide genome-wide association studies identified four major loci associated with flavonoid metabolic variation, including a locus corresponding to flavonoid 3'-hydroxylase. Conditional analyses based on multilocus genetic backgrounds demonstrated that the effects of downstream loci were highly dependent on upstream genotypes. In particular, single-nucleotide polymorphism effects were frequently detectable only in specific allelic backgrounds defined by the major flavonoid 3'-hydroxylase locus, consistent with strong epistatic interactions among loci. Bayesian network analyses further supported a hierarchical genetic structure consistent with upstream regulation of downstream loci across the flavonoid biosynthetic pathway. These results demonstrate that highly heritable metabolic phenotypes can be controlled by a few loci exhibiting both additive and context-dependent non-additive effects. Our findings provide evidence that pathway-level metabolic diversity in soybean is generated through hierarchical and epistatic genetic control involving a limited set of key loci.

plant biology↗

bioRxiv2026

Chromid-like secondary replicons as key sites of biosynthetic gene clusters in Ktedonobacteria

Soils harbour immense biosynthetic gene cluster (BGC) diversity that can mediate microbial interactions, yet this potential is still mapped unevenly across the tree of life. Ktedonobacteria--a class of actinomycete-like bacteria within phylum Chloroflexota--are widespread in terrestrial environments and repeatedly dominate pioneer communities in extremely oligotrophic volcanic bare-ground soils; however, their secondary metabolism and genome architecture remain poorly characterised. Here, we integrate targeted cultivation using volcanic soils from Mount Zao with genome-resolved metagenomics and public genomes to analyse 183 ktedonobacterial genomes. Using antiSMASH and BiG-SLiCE, we identified 1,546 BGCs comprising 1,162 non-redundant gene-cluster families (GCFs). In our dataset, nearly one quarter of genomes encode [≥]10 distinct GCFs, and several family-level clades show mean GCF counts comparable to those in genus Streptomyces. Most ktedonobacterial BGCs are highly divergent from reference collections and exhibit unusually low intra-genomic redundancy, suggesting broad, underexplored chemotypes. Long-read assemblies from ten strains reveal recurrent 1.6-3.5 Mb chromid-like secondary replicons with chromosome-like composition but distinct maintenance signatures. These replicons are consistently enriched in BGCs and mobility-associated genes, with mobility loci concentrated near BGC boundaries. Collectively, our results expand the current knowledge of the phylogenetic landscape of soil biosynthetic diversity and highlight chromid-like secondary replicons as major genomic reservoirs for specialised metabolism in Ktedonobacteria.

microbiology↗

bioRxiv2025

Horizontal acquisition of nicotine catabolism gene cluster drives the assembly of tobacco root microbiota community

BackgroundPlant roots are hotspots for interactions with soil microbes, where a characteristic bacterial community structure is formed. Plant specialized metabolites often play pivotal roles in this assembly process. However, the molecular basis underlying root microbiota responses to these bioactive compounds, and how such metabolic interactions shape the assembly of host-specific root microbiota, remain largely unknown. Nicotine is a toxic alkaloid predominantly produced by the genus Nicotiana, and the genus Arthrobacter is known as one of the nicotine-degrading bacteria in the tobacco root microbiota. In this study, we used the tobacco-Arthrobacter interaction system as a model and integrated comparative genomics and experimental genetic manipulation assays to uncover the role of bacterial catabolism capacity for host specialized metabolites in shaping host-specific root microbiota. ResultsNicotine catabolism genes are uniquely found in the Arthrobacter strains derived from nicotine-containing environments, and this restricted gene distribution is driven by a plasmid-mediated horizontal gene transfer. To assess the ecological consequences of this genomic adaptation in Arthrobacter fitness in tobacco roots, we conducted adaptation assays under both in vitro and in planta conditions using genetically manipulated Arthrobacter and tobacco mutants, which are impaired in nicotine catabolism and biosynthesis, respectively. Nicotine improves Arthrobacter colonization to the tobacco roots through both catabolism-dependent and catabolism-independent mechanisms. Bacterial community analysis using a synthetic community approach further demonstrated that these metabolic interactions, mediated by tobacco nicotine biosynthesis and its catabolism by Arthrobacter, jointly affect root microbiota composition. ConclusionsOur findings illustrated that bacterial catabolic capacity toward host-derived plant specialized metabolites is key for successful root colonization. This metabolic adaptation is driven by plasmid-mediated horizontal gene transfer and ultimately shapes the structure of the overall root microbiota community.

microbiology↗

bioRxiv2025

Integration of Proxy Intermediate Omics traits into a Nonlinear Two-Step model for accurate phenotypic prediction

Intermediate omics traits, which mediate the effects of genetic variation on phenotypic traits, are increasingly recognised as valuable components of genetic evaluation. In particular, rhizosphere microbiota play a crucial role in plant health and productivity; however, their complex interactions with host genetics remain challenging to model. Although two-step modeling frameworks have been proposed to integrate intermediate omics traits into phenotype prediction, existing approaches do not incorporate nonlinear relationships between different omics layers. To address this, we have proposed a two-step phenotype prediction framework that integrates genomic, rhizosphere microbiome, and metabolome (meta-metabolome) data, while explicitly capturing omicsomics nonlinearities. The first step is to predict meta-metabolome traits from genetic and microbial features, thus effectively isolating them from the environmental noise. In this process, intermediate "proxy" omics traits are generated as general biological information to provide robust models. The second step utilises this "proxy" to enhance the accuracy of the phenotype prediction. We compared the linear model (Best Linear Unbiased Prediction, BLUP) and the nonlinear model (Random Forest, RF) at each step, as demonstrated through simulations and empirical analysis of a multi-omics soybean dataset in which nonlinear modeling captures intricate omics interactions. Notably, our approach enables phenotype prediction without requiring the original meta-metabolome data used in model training, thereby reducing reliance on costly omics measurements. This framework integrates intermediate omics traits into genomic prediction to improve prediction accuracy and provide solutions for deeper insights into plant-microbiome interactions.

bioinformatics↗

bioRxiv2023

The leucine-rich repeat receptor kinase QSK1 is a novel regulator of PRR-RBOHD complex and is employed by the bacterial effector HopF2Pto to modulate plant immunity

Plants detect pathogens using cell-surface pattern recognition receptors (PRRs) like EFR and FLS2, which recognize bacterial EF-Tu and flagellin, respectively. These PRRs, belonging to the leucine-rich repeat receptor kinase (LRR-RK) family, activate the production of reactive oxygen species via the NADPH oxidase RBOHD. The PRR-RBOHD complex is tightly regulated to prevent unwarranted or exaggerated immune responses. However, certain pathogenic effectors can subvert these regulatory mechanisms, thereby suppressing plant immunity. To elucidate the intricate dynamics of the PRR-RBOHD complex, we conducted a comparative co-immunoprecipitation analysis using EFR, FLS2, and RBOHD. We identified QSK1, an LRR-RK, as a novel component of the PRR-RBOHD complex. QSK1 functions as a negative regulator of PRR-triggered immunity (PTI) by downregulating the abundance of FLS2 and EFR. QSK1 is targeted by the bacterial effector HopF2Pto, a mono-ADP ribosyltransferase, resulting in the reduction of FLS2 and EFR levels through both transcriptional and transcription-independent pathways, thereby inhibiting PTI. Furthermore, HopF2Pto reduces transcript levels of PROSCOOP genes encoding important stress-regulated phytocytokines and their receptor MIK2. Importantly, HopF2Pto requires QSK1 for its accumulation and virulence functions within plants. In summary, our results provide novel insights into the mechanism by which HopF2Pto employs QSK1 to desensitize plants to pathogen attack. One Sentence SummaryQSK1, a novel component in the plant immune receptor complex, downregulates these receptors and phytocytokines, and is exploited by bacterial effector HopF2Pto to desensitize plants to pathogen attack.

plant biology↗

bioRxiv2023

Establishing a comprehensive web-based analysis platform for Nicotiana benthamiana genome and transcriptome

Nicotiana benthamiana has long served as a crucial plant material extensively used in plant physiology research, particularly in the field of plant pathology, because of its high susceptibility to plant viruses. Additionally, it serves as a production platform to test vaccines and other valuable substances. Among its approximately 3.1 Gb genome, 57,583 genes have been annotated within a 61 Mb region. We created a comprehensive and easy-to-use platform to use transcriptomes for modern annotation. These tools allow to visualize gene expression profiles, draw molecular evolutionary phylogenetic trees of gene families, perform functional enrichment analyses, and facilitate output downloads. To demonstrate their utility, we analyzed the gene expression profiles of enzymes within the nicotine biosynthesis pathway, a secondary metabolic pathway characteristic of the Nicotiana genus. Using the developed tool, expression profiles of the nicotine biosynthesis pathway genes were generated. The expression patterns of eight gene groups in the pathway were strongly expressed in the roots and weakly expressed in leaves and flowers of N. benthamiana. The results were consistent with the established gene expression profiles in Nicotiana tabacum and provided insights into gene family composition and expression trends. The compilation of this database tool can facilitate genetic analysis of N. benthamiana in the future. Significance statementA tool was developed to visualize gene expression profiles, draw molecular evolutionary phylogenetic trees of gene families, perform functional enrichment analyses, and facilitate output downloads of Nicotiana benthamiana. The database developed using the tool can evolve into a comprehensive all-in-one analysis platform by continuously incorporating transcriptome data released to date, newly released RNA-seq data, and annotations in the future.

plant biology↗

bioRxiv2023

An integrative framework of stochastic variational variable selection for joint analysis of multi-omics microbiome data

High-dimensional multi-omics microbiome data plays an important role in elucidating microbial communities interactions with their hosts and environment in critical diseases and ecological changes. Although Bayesian clustering methods have recently been used for the integrated analysis of multi-omics data, no method designed to analyze multi-omics microbiome data has been proposed. In this study, we propose a novel framework called integrative stochastic variational variable selection (I-SVVS), which is an extension of stochastic variational variable selection for high-dimensional microbiome data. The I-SVVS approach addresses a specific Bayesian mixture model for each type of omics data, such as an infinite Dirichlet multinomial mixture model for microbiome data and an infinite Gaussian mixture model for metabolomic data. This approach is expected to reduce the computational time of the clustering process and improve the accuracy of the clustering results. Additionally, I-SVVS identifies a critical set of representative variables in multi-omics microbiome data. Three datasets from soybean, mice, and humans (each set integrated microbiome and metabolome) were used to demonstrate the potential of I-SVVS. The results indicate that I-SVVS achieved improved accuracy and faster computation compared to existing methods across all test datasets. It effectively identified key microbiome species and metabolites characterizing each cluster. For instance, the computational analysis of soybean dataset, including 377 samples with 16,943 microbiome species and 265 metabolome features, was completed in 2.18 hours using I-SVVS, compared to 2.35 days with Clusternomics and 1.12 days with iClusterPlus. The software for this analysis, written in Python, is freely available at https://github.com/tungtokyo1108/I-SVVS.

bioinformatics↗

bioRxiv2022

Genetic and phosphoproteomic basis of LysM-mediated immune signaling in Marchantia polymorpha highlights conserved elements and new aspect of pattern-triggered immunity in land plants

Pattern-recognition receptor (PRR)-triggered immunity (PTI) wards off a wide range of pathogenic microbes, playing a pivotal role in plant immunity. The model liverwort Marchantia polymorpha is emerging as a popular model for investigating the evolution of plant-microbe interactions. M. polymorpha triggers defense-related gene expression upon sensing components of bacterial and fungal extracts, suggesting the existence of PTI in this plant model. However, the molecular components of the putative PTI in M. polymorpha have not yet been described. We show that, in M. polymorpha, which has four LysM receptor homologs, lysin motif (LysM) receptor-like kinase (LYK) MpLYK1 and LYK-related (LYR) MpLYR are required for sensing chitin and peptidoglycan fragments, triggering a series of characteristic immune responses. Comprehensive phosphoproteomic analysis of M. polymorpha in response to chitin treatment identified regulatory proteins that potentially shape LysM-mediated PTI. The identified proteins included homologs of well-described PTI components in angiosperms as well as proteins whose roles in PTI are not yet determined, including the blue-light receptor phototropin MpPHOT. We revealed that MpPHOT is required for a negative feedback of defense-related gene expression during PTI. Taken together, this study outlines the basic framework of LysM-mediated PTI in M. polymorpha and demonstrates the utility of M. polymorpha as a plant model for discovering novel or fundamental molecular mechanisms underlying PRR-triggered immune signaling in plants.

plant biology↗

bioRxiv2022

A novel genomic DNA library preparation method with low GC bias

The amount of input DNA available to prepare next-generation sequencing (NGS) libraries is often limited, which can lead to GC content bias and enrichment of specific genomic regions with currently available protocols. In this study, we used breath capture technology to incorporate sequencing adapters into DNA to develop a novel cost-effective protocol for the preparation of genomic DNA libraries. We performed a benchmarking experiment comparing our protocol with common commercially available kits for genomic DNA library preparation with input DNA amount in the range of 1 to 50 ng. Our protocol can generate high-quality genomic sequence data with a marked improvement in coverage breadth and low GC bias, in contrast to standard protocols. Further, our protocol reduces sample handling time and reagent costs, and requires comparatively fewer enzymatic steps relative to other protocols, making it suitable for a range of genomics applications.

genomics↗

bioRxiv2021

Stochastic variational variable selection for high-dimensional microbiome data

BackgroundThe rapid and accurate identification of a minimal-size core set of representative microbial species plays an important role in the clustering of microbial community data and interpretation of clustering results. However, the huge dimensionality of microbial metagenomics datasets is a major challenge for the existing methods such as Dirichlet multinomial mixture (DMM) models. In the framework of the existing methods, the computational burden of identifying a small number of representative species from a large number of observed species remains a challenge. ResultsWe proposed a novel framework to improve the performance of the widely used DMM approach by combining three ideas: (i) we extended the finite DMM model to an infinite case by considering Dirichlet process mixtures and estimating the number of clusters as a random variables; (ii) we proposed an indicator variable to identify representative operational taxonomic units that substantially contribute to the differentiation among clusters; and (iii) to address the computational burden of high-dimensional microbiome data, we proposed a stochastic variational inference, which approximates the posterior distribution using a controllable distribution called variational distribution, and stochastic optimization algorithms for fast computation. Using the proposed method, stochastic variational variable selection (SVVS), we analyzed the root microbiome data collected in our soybean field experiment, the human gut microbiome data from three published datasets of large-scale case-control studies and the healthy human microbiome data from the Human Microbiome Project. ConclusionsSVVS demonstrated a better performance and significantly faster computation than those of the existing methods in all cases of testing datasets. In particular, SVVS is the only method that can analyze massive high-dimensional microbial data with more than 50,000 microbial species and 1,000 samples. Furthermore, recent microbiome studies have suggested that selection of the microbial species used as a core set is important.

bioinformatics↗

bioRxiv2021

Phosphorus is a critical factor of the in vitro monoxenic culture method for awide range of arbuscular mycorrhizal fungi culture collections

Establishing an effective way to propagate a wide range of arbuscular mycorrhizal (AM) fungi species is desirable for mycorrhizal research and agricultural applications. Although the success of mycorrhizal formation is required for spore production of AM fungi, the critical factors for its construction in the in vitro monoxenic culture protocol remain to be identified. In this study, we evaluated the growth of hairy roots from carrot, flax, and chicory, and investigated the effects of the phosphorus (P) concentration in the mother plate, as well as the levels of P, sucrose, and macronutrients in a cocultivation plate with a hairy root, amount of medium of the cocultivation plate, and location of spore inoculation, by utilizing the Bayesian information criterion model selection with greater than 800 units of data. We found that the flax hairy root was suitable for in vitro monoxenic culture, and that the concentration of P in the cocultivation plate was a critical factor for mycorrhizal formation. We showed that an extremely low concentration of P (3 M) significantly improved mycorrhizal formation for AM fungi belonging to the Glomerales order, while a high concentration of P (30 M) was suitable for Diversisporales fungi. Therefore, we anticipate that the refining the P concentration will contribute to future culture collections of a wide range of AM fungi.

microbiology↗

bioRxiv2021

GA-mediated spatial control of cell division expounds the leaf size variation between cultivated and wild rice

O_LICellular and genetic understanding of rice leaf size regulation is limited, despite rice being the staple food of more than half of the global population. We investigated the mechanism controlling the rice leaf length using cultivated and wild rice accessions that remarkably differed for leaf size. C_LIO_LIComparative transcriptomics, Gibberellic Acid (GA) quantification, and leaf kinematics of the contrasting accessions suggested the involvement of GA, cell cycle, and Growth-Regulating Factors (GRFs) in the rice leaf size regulation. Zone-specific expression analysis and VIGS established the functions of specific GRFs in the process. C_LIO_LIThe leaf length of the selected accessions was strongly correlated with GA levels. Higher GA content in wild rice accessions with longer leaves and GA-induced increase in the leaf length via an increase in cell division confirmed a GA-mediated regulation of division zone in rice. Downstream to GA, OsGRF7 and OsGRF8 function for controlling cell division to determine the rice leaf length. C_LIO_LISpatial control of cell division to determine the division zone size mediated by GA and downstream OsGRF7 and OsGRF8 explains the leaf length differences between the cultivated and wild rice. This mechanism to control rice leaf length might have contributed to optimizing leaf size during domestication. C_LI

plant biology↗

bioRxiv2021

Simple amplicon sequencing library preparation for plant root microbial community profiling

Microbiota are a major component of agroecosystems. Root microbiota, which inhabit the inside and surface of plant roots, play a significant role in plant growth and health. As next-generation sequencing technology allows the capture of microbial profiles without culturing the microbes, profiling of plant microbiota has become a staple tool in plant science and agriculture. Here, we have developed a novel high-throughput method based on a two-step PCR amplification protocol, involving DNA extraction using magnetic beads and PCR purification using exonuclease, for 16S rRNA gene amplicon sequencing of plant root microbiota. This method reduces sample handling and captures microbial diversity comparable to that obtained by the standard method. We found that using a buffer with magnetic beads enabled efficient extraction of microbial DNA directly from plant roots. In addition, we demonstrated that purification using exonuclease before the second PCR step enabled the capture of higher degrees of microbial diversity, thus allowing for the detection of minor bacteria compared with the purification using magnetic beads in this step. Our method offers a simple and high-throughput solution for maintaining the quality of plant root microbial community profiling.

plant biology↗

bioRxiv2021

Transcriptomic analysis of resistant and susceptible responses in a new model root-knot nematode infection system using Solanum torvum and Meloidogyne arenaria

Root-knot nematodes (RKNs) are among the most devastating pests in agriculture. Solanum torvum Sw. (turkey berry) has been used as a rootstock for eggplant (aubergine) cultivation because of its resistance to RKNs, including Meloidogyne incognita and M. arenaria. We previously found that a pathotype of M. arenaria, A2-J, is able to infect and propagate in S. torvum. In vitro infection assays showed that S. torvum induces the accumulation of brown pigments during avirulent pathotype A2-O infection, but not during virulent A2-J infection. This experimental system is advantageous because resistant and susceptible responses can be distinguished within a few days, and because a single plant genome can yield information about both resistant and susceptible responses. Comparative RNA-sequencing analysis of S. torvum inoculated with A2-J and A2-O at early stages of infection was used to parse the specific resistance and susceptible responses. Infection with A2-J did not induce statistically significant changes in gene expression within one day post-inoculation (DPI), but afterward, A2-J specifically induced the expression of chalcone synthase, spermidine synthase, and genes related to cell wall modification and transmembrane transport. Infection with A2-O rapidly induced the expression of genes encoding class III peroxidases, sesquiterpene synthases, and fatty acid desaturases at 1 DPI, followed by genes involved in defense, hormone signaling, and the biosynthesis of lignin at 3 DPI. Both isolates induced the expression of suberin biosynthetic genes, which may be triggered by wounding during nematode infection. Histochemical analysis revealed that A2-O, but not A2-J, induced lignin accumulation at the root tip, suggesting that physical reinforcement of cell walls with lignin is an important defense response against nematodes. The S. torvum-RKN system can provide a molecular basis for understanding plant-nematode interactions.

plant biology↗

bioRxiv2021

CcLBD25 functions as a key regulator of haustorium development in Cuscuta campestris

Parasitic plants reduce yield of crops worldwide. Cuscuta campestris is a stem parasite that attaches to its host, using haustoria to extract nutrients and water. We analyzed the transcriptome of six C. campestris tissues and identified a key gene, CcLBD25, as highly expressed in prehaustoria and haustoria. Our gene co-expression networks (GCN) from different tissue types and laser-capture microdissection (LCM) RNA-Seq data indicate that CcLBD25 could be essential for regulating cell wall loosening and organogenesis. We employed host-induced gene silencing (HIGS) by generating transgenic tomato hosts that express hairpin RNAs to target and down-regulate CcLBD25 in the parasite. Our results showed that C. campestris growing on CcLBD25 RNAi transgenic tomatoes transited to the flowering stage earlier and had less biomass compared with C. campestris growing on wild type host. This suggests that the parasites growing on the transgenic plants were stressed due to insufficient nutrient acquisition. Anatomy of C. campestris haustoria growing on CcLBD25 RNAi tomatoes showed reduced pectin digestion and lack of searching hyphae, which interfered with haustorium penetration and the formation of vascular connections. We developed an in vitro haustorium (IVH) system to assay the number of prehaustoria produced on strands from C. campestris. When C. campestris was grown on CcLBD25 RNAi tomatoes or wild type tomatoes, the former produce fewer prehaustoria than the latter, indicating that down-regulating CcLBD25 may affect haustorium initiation. The results of this study shed light on the role of CcLBD25 in haustorium development and might help to develop a parasite-resistant system in crops. One-sentence summaryCcLBD25 plays a pivotal role in haustorium initiation, regulating pectin digestion, and searching hyphae development during the haustorium penetration process.

plant biology↗

bioRxiv2020

Oxicam-type NSAIDs enhance Agrobacterium-mediated transformation in plants

Agrobacterium-mediated transformation represents a key innovation for plant breeding and is routinely used in research and applied biology. However, for several species, the efficacy of transformation is limited. In this study, we discovered that oxicam-type nonsteroidal anti-inflammatory drugs (NSAIDs), including tenoxicam (TNX), enhance the efficiency of Agrobacterium-mediated transient transformation in the model species Arabidopsis thaliana via leaf infiltration and can be successfully applied in analyses of the subcellular localisation of fluorescent fusion proteins. TNX acts as an inhibitor of plant immune responses and lacks similar transient transformation efficiency in a dde2/ein2/pad4/sid2 quadruple mutant background, thereby indicating that TNX increases the efficiency of Agrobacterium infection via a transient shutdown of the immune system mediated by jasmonic acid, ethylene, and salicylic acid signalling. In addition, we found that TNX enhances the efficiency of stable transformation in crops of agricultural and economic importance, such as Jatropha and maize, indicating that TNX can enhance the integration of exogenous DNA into the plant genome via an increased introduction of DNA into plant cells. Given that treatment with oxicam compounds is simple, cost effective, and has broad utility, we anticipate that this discovery will contribute to accelerating genome-editing technologies in plants.

plant biology↗

bioRxiv2020

A pair of effectors encoded on a conditionally dispensable chromosome of Fusarium oxysporum suppress host-specific immunity

Many plant pathogenic fungi contain conditionally dispensable (CD) chromosomes that are associated with virulence, but not growth in vitro. Virulence-associated CD chromosomes carry genes encoding effectors and/or host-specific toxin biosynthesis enzymes that may contribute significantly to determining host specificity. Fusarium oxysporum causes devastating diseases of more than 100 plant species. Among a large number of host-specific forms, F. oxysporum f. sp. conglutinans (Focn) can infect Brassicaceae plants including Arabidopsis and cabbage. Here we show that Focn has multiple CD chromosomes involved in virulence but also in vegetative growth, which is an atypical feature of CD chromosomes. We identified specific CD chromosomes that are required for virulence on Arabidopsis, cabbage, or both, and describe a pair of effectors encoded on one of the CD chromosomes that is required for suppression of Arabidopsis-specific phytoalexin-based immunity. The effector pair is highly conserved in F. oxysporum isolates capable of infecting Arabidopsis, but not of other plants. This study provides insight into how host specificity of F. oxysporum may be determined by a pair of effector genes on a transmissible CD chromosome.

microbiology↗

bioRxiv2020

Three-dimensional reconstructions of the internal structures of haustoria in parasitic Orobanchaceae

Parasitic plants infect other plants by forming haustoria, specialized multicellular organs consisting of several cell types each of which has unique morphological features and physiological roles associated with parasitism. Understanding the spatial organization of cell types is, therefore, of great importance in elucidating the functions of haustoria. Here, we report a three-dimensional (3-D) reconstruction of haustoria from two Orobanchaceae species, the obligate parasite Striga hermonthica infecting rice and the facultative parasite Phtheirospermum japonicum infecting Arabidopsis. Our images reveal the spatial arrangements of multiple cell types inside haustoria and their interaction with host roots. The 3-D internal structures of haustoria highlight differences between the two parasites, particularly at the xylem connection site with the host. Our study provides structural insights into how organs interact between hosts and parasitic plants. One-sentence summaryThree-dimensional image reconstruction was used to visualize the spatial organization of cell types in the haustoria of parasitic plants with special reference to their interaction with host roots.

plant biology↗