Compartmentalized gene regulatory network of the pathogenic fungus Fusarium graminearum

Bayesian networks for network inference in biology

Bayesian networks (BNs) have been used for reconstructing interactions from biological data, in disciplines ranging from molecular biology to ecology and neuroscience. BNs learn conditional dependencies between variables, which best 'explain' the data, represented as a directed graph which approximates the relationships between variables. In the 2000s, BNs were a popular method that promised an approach capable of inferring biological networks from data. Here, we review the use of BNs applied to biological data over the past two decades and evaluate their efficacy. We find that BNs are successful in inferring biological networks, frequently identifying novel interactions or network components missed by previous analyses. We suggest that as false positive results are underreported, it is difficult to assess the accuracy of BNs in inferring biological networks. BN learning appears most successful for small numbers of variables with high-quality datasets that either discretize the data into few states or include perturbative data. We suggest that BNs have failed to live up to the promise of the 2000s but that this is most likely due to experimental constraints on datasets, and the success of BNs at inferring networks in a variety of biological contexts suggests they are a powerful tool for biologists.

Transcription factor-dependent regulatory networks of sexual reproduction in Fusarium graminearum

Transcription factors (TFs) involved in sexual reproduction in filamentous fungi have been characterized. However, we have little understanding of how these TFs synergize within regulatory networks resulting in sexual development. We investigated 13 TFs in Fusarium graminearum, whose knockouts exhibited abortive or arrested phenotypes during sexual development to elucidate the transcriptional regulatory cascade underlying the development of the sexual fruiting bodies. A Bayesian network of the TFs was inferred based on transcriptomic data from key stages of sexual development. We evaluated in silico knockout impacts to the networks of the developmental phenotypes among the TFs and guided knockout transcriptomics experiments to properly assess regulatory roles of genes with same developmental phenotypes. Additional transcriptome data were collected for the TF knockouts guided by the stage at which their phenotypes appeared and by the cognate in silico prediction. Global TF networks revealed that TFs within the mating-type locus (MAT genes) trigger a transcriptional cascade involving TFs that affected early stages of sexual development. Notably, PNA1, whose knockout mutants produced exceptionally small protoperithecia, was shown to be an upstream activator for MAT genes and several TFs essential for ascospore production. In addition, knockout mutants of SUB1 produced excessive numbers of protoperithecia, wherein MAT genes and pheromone-related genes exhibited dysregulated expression. We conclude that PNA1 and SUB1 play central and suppressive roles in initiating sexual reproduction, respectively. This comprehensive investigation contributes to our understanding of the transcriptional framework governing the multicellular body plan during sexual reproduction in F. graminearum.IMPORTANCEUnderstanding transcriptional regulation of sexual development is crucial to the elucidation of the complex reproductive biology in Fusarium graminearum. We performed gene knockouts on 13 transcription factors (TFs), demonstrating knockout phenotypes affecting distinct stages of sexual development. Using transcriptomic data across stages of sexual development, we inferred a Bayesian network of these TFs that guided experiments to assess the robustness of gene interactions using a systems biology approach. We discovered that the mating-type locus (MAT genes) initiates a transcriptional cascade, with PNA1 identified as an upstream activator essential for early sexual development and ascospore production. Conversely, SUB1 was found to play a suppressive role, with knockout mutants exhibiting excessive protoperithecia due to abnormally high expression of MAT and pheromone-related genes. These findings highlight the central roles of PNA1 and SUB1 in regulating other gene activity related to sexual reproduction, contributing to a deeper understanding of the mechanisms of the multiple TFs that regulate sexual development.

A conserved fungal Knr4/Smi1 protein is crucial for maintaining cell wall stress tolerance and host plant pathogenesis

Filamentous plant pathogenic fungi pose significant threats to global food security, particularly through diseases like Fusarium Head Blight (FHB) and Septoria Tritici Blotch (STB) which affects cereals. With mounting challenges in fungal control and increasing restrictions on fungicide use due to environmental concerns, there is an urgent need for innovative control strategies. Here, we present a comprehensive analysis of the stage-specific infection process of Fusarium graminearum in wheat spikes by generating a dual weighted gene co-expression network (WGCN). Notably, the network contained a mycotoxin-enriched fungal module (F12) that exhibited a significant correlation with a detoxification gene-enriched wheat module (W12). This correlation in gene expression was validated through quantitative PCR. By examining a fungal module with genes highly expressed during early symptomless infection that was correlated to a wheat module enriched in oxidative stress genes, we identified a gene encoding FgKnr4, a protein containing a Knr4/Smi1 disordered domain. Through comprehensive analysis, we confirmed the pivotal role of FgKnr4 in various biological processes, including oxidative stress tolerance, cell cycle stress tolerance, morphogenesis, growth, and pathogenicity. Further studies confirmed the observed phenotypes are partially due to the involvement of FgKnr4 in regulating the fungal cell wall integrity pathway by modulating the phosphorylation of the MAP-kinase MGV1. Orthologues of the FgKnr4 gene are widespread across the fungal kingdom but are absent in other Eukaryotes, suggesting the protein has potential as a promising intervention target. Encouragingly, the restricted growth and highly reduced virulence phenotypes observed for ΔFgknr4 were replicated upon deletion of the orthologous gene in the wheat fungal pathogen Zymoseptoria tritici. Overall, this study demonstrates the utility of an integrated network-level analytical approach to pinpoint genes of high interest to pathogenesis and disease control.

Comparative transcriptome analysis of Fusarium graminearum challenged with distinct fungicides and functional analysis of FgICL gene

Fusarium graminearum is an economically important phytopathogenic fungus. Chemical control remains the dominant approach to managing this plant pathogen. In the present study, we performed a comparative transcriptome analysis to understand the effects of four commercially used fungicides on F. graminearum. The results revealed a significant number of differentially expressed genes related to carbohydrate, amino acid, and lipid metabolism, particularly in the carbendazim and phenamacril groups. Central carbon pathways, including the TCA and glyoxylate cycles, were found to play crucial roles across all treatments except tebuconazole. Weighted gene co-expression network analysis reinforced the pivotal role of central carbon pathways based on identified hub genes. Additionally, critical candidates associated with ATP-binding cassette transporters, heat shock proteins, and chitin synthases were identified. The crucial functions of the isocitrate lyase in F. graminearum were also validated. Overall, the study provided comprehensive insights into the mechanisms of how F. graminearum responds to fungicide stress.

Functional Characterization of Aldehyde Dehydrogenase in Fusarium graminearum

Aldehyde dehydrogenase (ALDH), a common oxidoreductase in organisms, is an aldehyde scavenger involved in various metabolic processes. However, its function in different pathogenic fungi remains unknown. Fusarium graminearum causes Fusarium head blight in cereals, which reduces grain yield and quality and is an important global food security problem. To elucidate the pathogenic mechanism of F. graminearum, seven genes encoding ALDH were knocked out and then studied for their function. Single deletions of seven ALDH genes caused a decrease in spore production and weakened the pathogenicity. Furthermore, these deletions altered susceptibility to various abiotic stresses. FGSG_04194 is associated with a number of functions, including mycelial growth and development, stress sensitivity, pathogenicity, toxin production, and energy metabolism. FGSG_00139 and FGSG_11482 are involved in sporulation, pathogenicity, and SDH activity, while the other five genes are multifunctional. Notably, we found that FGSG_04194 has an inhibitory impact on ALDH activity, whereas FGSG_00979 has a positive impact. RNA sequencing and subcellular location analysis revealed that FGSG_04194 is responsible for biological process regulation, including glucose and lipid metabolism. Our results suggest that ALDH contributes to growth, stress responses, pathogenicity, deoxynivalenol synthesis, and mitochondrial energy metabolism in F. graminearum. Finally, ALDH presents a potential target and theoretical basis for fungicide development.

Conservation and Expansion of Transcriptional Factor Repertoire in the Fusarium oxysporum Species Complex

The Fusarium oxysporum species complex (FOSC) includes both plant and human pathogens that cause devastating plant vascular wilt diseases and threaten public health. Each F. oxysporum genome comprises core chromosomes (CCs) for housekeeping functions and accessory chromosomes (ACs) that contribute to host-specific adaptation. This study inspects global transcription factor profiles (TFomes) and their potential roles in coordinating CC and AC functions to accomplish host-specific interactions. Remarkably, we found a clear positive correlation between the sizes of TFomes and the proteomes of an organism. With the acquisition of ACs, the FOSC TFomes were larger than the other fungal genomes included in this study. Among a total of 48 classified TF families, 14 families involved in transcription/translation regulations and cell cycle controls were highly conserved. Among the 30 FOSC expanded families, Zn2-C6 and Znf_C2H2 were most significantly expanded to 671 and 167 genes per family including well-characterized homologs of Ftf1 (Zn2-C6) and PacC (Znf_C2H2) that are involved in host-specific interactions. Manual curation of characterized TFs increased the TFome repertoires by 3% including a disordered protein Ren1. RNA-Seq revealed a steady pattern of expression for conserved TF families and specific activation for AC TFs. Functional characterization of these TFs could enhance our understanding of transcriptional regulation involved in FOSC cross-kingdom interactions, disentangle species-specific adaptation, and identify targets to combat diverse diseases caused by this group of fungal pathogens.

Conservation and Expansion of Transcriptional Factor Repertoire in the Fusarium oxysporum Species Complex

The Fusarium oxysporum species complex (FOSC) includes both plant and human pathogens that cause devastating plant vascular wilt diseases and threaten public health. Each F. oxysporum genome comprises core chromosomes (CCs) for housekeeping functions and accessory chromosomes (ACs) that contribute to host-specific adaptation. This study inspected global transcription factor profiles (TFomes) and their potential roles in coordinating CCs and ACs functions to accomplish host-specific pathogenicity. Remarkably, we found a clear positive correlation between the sizes of TFome and proteome of an organism, and FOSC TFomes are larger due to the acquisition of ACs. Among a total of 48 classified TF families, 14 families involved in transcription/translation regulations and cell cycle controls are highly conserved. Among 30 FOSC expanded families, Zn2-C6 and Znf_C2H2 are most significantly expanded to 671 and 167 genes per family, including well-characterized homologs of Ftf1 (Zn2-C6) and PacC (Znf_C2H2) involved in host-specific interactions. Manual curation of characterized TFs increased the TFome repertoires by 3%, including a disordered protein Ren1. Expression profiles revealed a steady expression of conserved TF families and specific activation of AC TFs. Functional characterization of these TFs could enhance our understanding of transcriptional regulation involved in FOSC cross-kingdom interactions, disentangle species-specific adaptation, and identify targets to combat diverse diseases caused by this group of fungal pathogens.

Genome Sequence Resource of Fusarium graminearum TaB10 and Fusarium avenaceum KA13, Causal Agents of Stored Apple Rot

The filamentous fungus Fusarium graminearum is a well-known cereal pathogen and F. avenaceum is a pathogen with a wide host range. Recently, both species were reported as causal agents of apple rot, raising concerns about postharvest yield losses and mycotoxin contamination. Here, we report genome assemblies of F. avenaceum KA13 and F. graminearum TaB10, both isolated from fruits with symptoms of apple rot. The final F. avenaceum KA13 genome sequence assembly of 41.7 Mb consists of 34 scaffolds, with an N₅₀ value of 2.2 Mb and 15,886 predicted genes. The total size of the final F. graminearum TaB10 assembly is 36.76 Mb, consisting of 54 scaffolds with an N₅₀ value of 1.7 Mb, and it consists of 14,132 predicted genes. These new genomes provide valuable resources to better understand plant-microbe interaction in stored apple rot disease. [Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Construction of a Hierarchical Gene Regulatory Network to Reveal the Drought Tolerance Mechanism of Shanxin Poplar

Drought stress is a common adverse environment that plants encounter, and many drought-tolerant genes have been characterized. The gene regulatory network (GRN) is important in revealing the drought tolerance mechanism. Here, to investigate the regulatory mechanism of Shanxin poplar (Populus davidiana × P. bolleana) responding to drought stress, a three-layered GRN was built, and the regulatory relationship between genes in the GRN were predicted from expression correlation using a partial correlation coefficient-based algorithm. The GRN contains 1869 regulatory relationships, and includes 11 and 19 transcription factors (TFs) in the first and second layers, respectively, and 158 structural genes in the bottom layers involved in eight enriched biological processes. ChIP-PCR and qRT-PCR based on transient transformation were performed to validate the reliability of the GRN. About 88.0% of predicted interactions between the first and second layers, and 82.0% of predicted interactions between the second and third layers were correct, suggesting that the GRN is reliable. Six TFs were randomly selected from the top layer for characterizing their function in drought, and all of these TFs can confer drought tolerance. The important biological processes related to drought tolerance were identified, including "response to jasmonic acid", "response to oxidative stress", and "response to osmotic stress". In this GRN, PdbERF3 is predicted to play an important role in drought tolerance. Our data revealed the key regulators, TF-DNA interactions, and the main biological processes involved in adaption of drought stress in Shanxin poplar.

Functional Identification of Arthrinium phaeospermum Effectors Related to Bambusa pervariabilis × Dendrocalamopsis grandis Shoot Blight

The shoot blight of Bambusa pervariabilis × Dendrocalamopsis grandis caused by Arthrinium phaeospermum made bamboo die in a large area, resulting in serious ecological and economic losses. Dual RNA-seq was used to sequence and analyze the transcriptome data of A. phaeospermum and B. pervariabilis × D. grandis in the four periods after the pathogen infected the host and to screen the candidate effectors of the pathogen related to the infection. After the identification of the effectors by the tobacco transient expression system, the functions of these effectors were verified by gene knockout. Fifty-three differentially expressed candidate effectors were obtained by differential gene expression analysis and effector prediction. Among them, the effectors ApCE12 and ApCE22 can cause programmed cell death in tobacco. The disease index of B. pervariabilis × D. grandis inoculated with mutant ΔApCE12 and mutant ΔApCE22 strains were 52.5% and 47.5%, respectively, which was significantly lower than that of the wild-type strains (80%), the ApCE12 complementary strain (77.5%), and the ApCE22 complementary strain (75%). The tolerance of the mutant ΔApCE12 and mutant ΔApCE22 strains to H₂O₂ and NaCl stress was significantly lower than that of the wild-type strain and the ApCE12 complementary and ApCE22 complementary strains, but there was no difference in their tolerance to Congo red. Therefore, this study shows that the effectors ApCE12 and ApCE22 play an important role in A. phaeospermum virulence and response to H₂O₂ and NaCl stress.

Practical application of a Bayesian network approach to poultry epigenetics and stress

Background

Relationships among genetic or epigenetic features can be explored by learning probabilistic networks and unravelling the dependencies among a set of given genetic/epigenetic features. Bayesian networks (BNs) consist of nodes that represent the variables and arcs that represent the probabilistic relationships between the variables. However, practical guidance on how to make choices among the wide array of possibilities in Bayesian network analysis is limited. Our study aimed to apply a BN approach, while clearly laying out our analysis choices as an example for future researchers, in order to provide further insights into the relationships among epigenetic features and a stressful condition in chickens (Gallus gallus).

Results

Chickens raised under control conditions (n = 22) and chickens exposed to a social isolation protocol (n = 24) were used to identify differentially methylated regions (DMRs). A total of 60 DMRs were selected by a threshold, after bioinformatic pre-processing and analysis. The treatment was included as a binary variable (control = 0; stress = 1). Thereafter, a BN approach was applied: initially, a pre-filtering test was used for identifying pairs of features that must not be included in the process of learning the structure of the network; then, the average probability values for each arc of being part of the network were calculated; and finally, the arcs that were part of the consensus network were selected. The structure of the BN consisted of 47 out of 61 features (60 DMRs and the stressful condition), displaying 43 functional relationships. The stress condition was connected to two DMRs, one of them playing a role in tight and adhesive intracellular junctions in organs such as ovary, intestine, and brain.

Conclusions

We clearly explain our steps in making each analysis choice, from discrete BN models to final generation of a consensus network from multiple model averaging searches. The epigenetic BN unravelled functional relationships among the DMRs, as well as epigenetic features in close association with the stressful condition the chickens were exposed to. The DMRs interacting with the stress condition could be further explored in future studies as possible biomarkers of stress in poultry species.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04800-0.

Hierarchical transcription factor and regulatory network for drought response in Betula platyphylla

Although many genes and biological processes involved in abiotic stress response have been identified, how they are regulated remains largely unclear. Here, to study the regulatory mechanism of birch (Betula platyphylla) responding to drought induced by polyethylene glycol (PEG) 6000 (20%, w/v), a partial correlation coefficient-based algorithm for constructing gene regulatory network (GRN) was proposed, and a three-layer hierarchical GRN was constructed, including 68 transcription factors (TFs), and 252 structural genes. Totally, 1448 predicted regulatory relationships are included, and most of them are novel. The reliability of GRN was verified by ChIP-PCR and qRT-PCR based on transient transformation. About 55% of genes in the bottom layer of GRN could confer drought tolerance. We selected the two TFs, BpMADS11 and BpNAC090, from the up layer and characterized their function in drought tolerance. Overexpression of BpMADS11 and BpNAC090 both reduces electrolyte leakage, ROS and MDA contents, displaying increased drought tolerance than wild-type birch. According to this GRN, the important biological processes involved in drought were identified, including "signaling hormone pathways", "water transport", "regulation of stomatal movement" and "response to oxidative stress". This work indicated that BpERF017, BpAGL61 and BpNAC090 are the key upstream regulators in birch drought tolerance. Our data clearly revealed the upstream regulators and TF-DNA interaction regulate different biological processes to adapt drought stress.

A comprehensive transcription factor and DNA-binding motif resource for the construction of gene regulatory networks in Botrytis cinerea and Trichoderma atroviride

Botrytis cinerea and Trichoderma atroviride are two relevant fungi in agricultural systems. To gain insights into these organisms' transcriptional gene regulatory networks (GRNs), we generated a manually curated transcription factor (TF) dataset for each of them, followed by a GRN inference utilizing available sequence motifs describing DNA-binding specificity and global gene expression data. As a proof of concept of the usefulness of this resource to pinpoint key transcriptional regulators, we employed publicly available transcriptomics data and a newly generated dual RNA-seq dataset to build context-specific Botrytis and Trichoderma GRNs under two different biological paradigms: exposure to continuous light and Botrytis-Trichoderma confrontation assays. Network analysis of fungal responses to constant light revealed striking differences in the transcriptional landscape of both fungi. On the other hand, we found that the confrontation of both microorganisms elicited a distinct set of differentially expressed genes with changes in T. atroviride exceeding those in B. cinerea. Using our regulatory network data, we were able to determine, in both fungi, central TFs involved in this interaction response, including TFs controlling a large set of extracellular peptidases in the biocontrol agent T. atroviride. In summary, our work provides a comprehensive catalog of transcription factors and regulatory interactions for both organisms. This catalog can now serve as a basis for generating novel hypotheses on transcriptional regulatory circuits in different experimental contexts.

Transcriptome Dynamics Underlying Chlamydospore Formation in Trichoderma virens GV29-8

Trichoderma spp. are widely used biocontrol agents which are antagonistic to a variety of plant pathogens. Chlamydospores are a type of propagules produced by many fungi that have thick walls and are highly resistant to adverse environmental conditions. Chlamydospore preparations of Trichoderma spp. can withstand various storage conditions, have a longer shelf life than conidial preparations and have better application potential. However, large-scale production of chlamydospores has proven difficult. To understand the molecular mechanisms governing chlamydospore formation (CF) in Trichoderma fungi, we performed a comprehensive analysis of transcriptome dynamics during CF across 8 different developmental time points, which were divided into 4 stages according to PCA analysis: the mycelium growth stage (S1), early and middle stage of CF (S2), flourishing stage of CF (S3), and late stage of CF and mycelia initial autolysis (S4). 2864, 3206, and 3630 DEGs were screened from S2 vs S1, S3 vs S2, and S4 vs S3, respectively. We then identified the pathways and genes that play important roles in each stage of CF by GO, KEGG, STC and WGCNA analysis. The results showed that DEGs in the S2 vs S1 were mainly enriched in organonitrogen compound metabolism, those in S3 vs S2 were mainly involved in secondary metabolite, cell cycle, and N-glycan biosynthesis, and DEGs in S4 vs S3 were mainly involved in lipid, glycogen, and chitin metabolic processes. We speculated that mycelial assimilation and absorption of exogenous nitrogen in the early growth stage (S1), resulted in subsequent nitrogen deficiency (S2). At the same time, secondary metabolites and active oxygen free radicals released during mycelial growth produced an adverse growth environment. The resulting nitrogen-deficient and toxin enriched medium may stimulate cell differentiation by initiating cell cycle regulation to induce morphological transformation of mycelia into chlamydospores. High expression of genes relating to glycogen, lipid, mannan, and chitin synthetic metabolic pathways during the flourishing (S3) and late stages (S4) of CF may be conducive to energy storage and cell wall construction in chlamydospores. For further verifying the functions of the amino sugar and nucleotide sugar metabolism (tre00520) pathway in the CF of T. virens GV29-8 strain, the chitin synthase gene (TRIVIDRAFT_90152), one key gene of the pathway, was deleted and resulted in the dysplasia of mycelia and an incapability to form normal chlamydospores, which illustrated the pathway affecting the CF of T. virens GV29-8 strain. Our results provide a new perspective for understanding the genetics of biochemical pathways involved in CF of Trichoderma spp.

QTL mapping in Fusarium graminearum identified an allele of FgVe1 involved in reduced aggressiveness

Fusarium graminearum is one of the most frequent causal agents of the Fusarium Head Blight, a cereal disease spread throughout the world, reducing grain production and quality. F. graminearum isolates are genetically and phenotypically highly diverse. Notably, remarkable variations of aggressiveness between isolates have been observed, which could reflect an adaptive potential of this pathogen. In this study, we aimed to characterize the genetic basis of aggressiveness variation observed in an F1 population (n = 94), for which genome sequences of both parental strains are available. Aggressiveness was assessed by a panel of in planta and in vitro proxies during two phenotyping trials including, among others, disease severity and mycotoxin accumulation in wheat spike. One major and single QTL was mapped for all the traits measured, on chromosome I, that explained up to 90% of the variance for disease severity. The confidence interval at the QTL spanned 1.2 Mb and contained 428 genes on the reference genome. Of these, four candidates were selected based on the postulate that a non-synonymous mutation affecting protein function may be responsible for phenotypic differences. Finally, a new mutation was identified and functionally validated in the gene FgVe1, coding for a velvet protein known to be involved in pathogenicity and secondary metabolism production in several fungi.

Divergence and Gene Flow Between Fusarium subglutinans and F. temperatum Isolated from Maize in Argentina

Fusarium subglutinans and F. temperatum are two important fungal pathogens of maize whose distinctness as separate species has been difficult to assess. We isolated strains of these species from commercial and native maize varieties in Argentina and sequenced >28,000 loci to estimate genetic variation in the sample. Our objectives were to measure genetic divergence between the species, infer demographic parameters related to their split, and describe the population structure of the sample. When analyzed together, over 30% of each species' polymorphic sites (>2,500 sites) segregate as polymorphisms in the other. Demographic modeling confirmed the species split predated maize domestication, but subsequent between-species gene flow has occurred, with gene flow from F. subglutinans into F. temperatum greater than gene flow in the reverse direction. In F. subglutinans, little evidence exists for substructure or recent selective sweeps, but there is evidence for limited sexual reproduction. In F. temperatum, there is clear evidence for population substructure and signals of abundant recent selective sweeps, with sexual reproduction probably less common than in F. subglutinans. Both genetic variation and the relative number of polymorphisms shared between species increase near the telomeres of all 12 chromosomes, where genes related to plant-pathogen interactions often are located. Our results suggest that species boundaries between closely related Fusarium species can be semipermeable and merit further study. Such semipermeability could facilitate unanticipated genetic exchange between species and enable quicker permanent responses to changes in the agro-ecosystem, e.g., pathogen-resistant host varieties, new chemical and biological control agents, and agronomic practices.

FgPKS7 is an essential player in mating-type-mediated regulatory pathway required for completing sexual cycle in Fusarium graminearum

Secondary metabolism is intimately linked to developmental processes in filamentous fungi. In a previous study, we revealed that several polyketide synthase (PKS) genes, including FgPKS7, are specifically induced during formation of the sexual fruiting body (perithecium) in the cereal pathogen Fusarium graminearum. The function of PKS7, which is essential for perithecial development and hyphal growth, is interchangeable between two phylogenetically related species, F. graminearum and F. asiaticum, but not conserved in the more distantly related species F. fujikuroi and F. neocosmosporiellum. FgPKS7 is under the control of global or upstream regulators including the mating-type (MAT) locus and regulates numerous downstream genes that are transcriptionally specific to and functionally essential for sexual development, several other PKS genes, and ABC transporter genes for azole resistance in F. graminearum. FgPKS7 is an essential element for proper sexual development and participates in a regulatory network controlled by the MAT locus. Although the chemical identity of FgPKS7 remains unclear, FgPKS7 is likely involved in chemical reaction(s) for synthesis of metabolite(s) that control or promote perithecial maturation in F. graminearum. This study provides in-depth insights into the direct role of secondary metabolites in sexual development of filamentous fungi.

Machine learning in plant-pathogen interactions: empowering biological predictions from field scale to genome scale

Machine learning (ML) encompasses statistical methods that learn to identify patterns in complex datasets. Here, I review application areas in plant-pathogen interactions that have recently benefited from ML, such as disease monitoring, the discovery of gene regulatory networks, genomic selection for disease resistance and prediction of pathogen effectors. However, achieving robust performance from ML is not trivial and requires knowledge of both the methodology and the biology. I discuss common pitfalls and challenges in using ML approaches. Finally, I highlight future opportunities for ML as a tool for dissecting plant-pathogen interactions using high-throughput data, for example, through integration of diverse data sources and the analysis with higher resolution, such as from individual cells or on elaborate spatial and temporal scales.

Accessory Chromosomes in Fusarium oxysporum

Most genomes within the species complex of Fusarium oxysporum are organized into two compartments: the core chromosomes (CCs) and accessory chromosomes (ACs). As opposed to CCs, which are conserved and vertically transmitted to carry out essential housekeeping functions, lineage- or strain-specific ACs are believed to be initially horizontally acquired through unclear mechanisms. These two genomic compartments are different in terms of gene density, the distribution of transposable elements, and epigenetic markers. Although common in eukaryotes, the functional importance of ACs is uniquely emphasized among fungal species, specifically in relationship to fungal pathogenicity and their adaptation to diverse hosts. With a focus on the cross-kingdom fungal pathogen F. oxysporum, this review provides a summary of the differences between CCs and ACs based on current knowledge of gene functions, genome structures, and epigenetic signatures, and explores the transcriptional crosstalk between the core and accessory genomes.

Identifying TF Binding Motifs from a Partial Set of Target Genes and its Application to Regulatory Network Inference

Motif identification has been one of the most widely studied problems in bioinformatics. Many methods have been developed to discover binding motifs from a large set of genes. But when the given genes are only a partial set of target genes, the statistical significance usually contains a bias towards the input. If we can identify the TF binding motif from a partial set of target genes, we can save the labor costs and resources for doing many experiments. In this paper, we propose a method MISA (Motif Identification through Segments Assembly) to identify binding motifs from a subset of target genes. By ranking and assembling the segments, MISA discovers a set of binding motifs with the best length to fit our proposed objective function. We also predict the additional target genes as an application of regulatory network inference. We compare our approach with two widely used methods MEME and AlignACE by analyzing both the quality of the binding motif and network inference. Using two model organisms S. cerevisiae and E. coli, we show that with 20 percent of the target genes (minimum sample size of 20), we can achieve a motif similarity of 82 percent with the known motifs. Our results also show that 73 percent of target genes on average can be correctly predicted without introducing many false target genes.

Use of Dual RNA-seq for Systems Biology Analysis of Zea mays and Aspergillus flavus Interaction

The interaction between Aspergillus flavus and Zea mays is complex, and the identification of plant genes and pathways conferring resistance to the fungus has been challenging. Therefore, the authors undertook a systems biology approach involving dual RNA-seq to determine the simultaneous response from the host and the pathogen. What was dramatically highlighted in the analysis is the uniformity in the development patterns of gene expression of the host and the pathogen during infection. This led to the development of a "stage of infection index" that was subsequently used to categorize the samples before down-stream system biology analysis. Additionally, we were able to ascertain that key maize genes in pathways such as the jasmonate, ethylene and ROS pathways, were up-regulated in the study. The stage of infection index used for the transcriptomic analysis revealed that A. flavus produces a relatively limited number of transcripts during the early stages (0 to 12 h) of infection. At later stages, in A. flavus, transcripts and pathways involved in endosomal transport, aflatoxin production, and carbohydrate metabolism were up-regulated. Multiple WRKY genes targeting the activation of the resistance pathways (i.e., jasmonate, phenylpropanoid, and ethylene) were detected using causal inference analysis. This analysis also revealed, for the first time, the activation of Z. mays resistance genes influencing the expression of specific A. flavus genes. Our results show that A. flavus seems to be reacting to a hostile environment resulting from the activation of resistance pathways in Z. mays. This study revealed the dynamic nature of the interaction between the two organisms.

Dynamic network inference and association computation discover gene modules regulating virulence, mycotoxin and sexual reproduction in Fusarium graminearum

Background

The filamentous fungus Fusarium graminearum causes devastating crop diseases and produces harmful mycotoxins worldwide. Understanding the complex F. graminearum transcriptional regulatory networks (TRNs) is vital for effective disease management. Reconstructing F. graminearum dynamic TRNs, an NP (non-deterministic polynomial) -hard problem, remains unsolved using commonly adopted reductionist or co-expression based approaches. Multi-omic data such as fungal genomic, transcriptomic data and phenomic data are vital to but so far have been largely isolated and untapped for unraveling phenotype-specific TRNs.

Results

Here for the first time, we harnessed these resources to infer global TRNs for F. graminearum using a Bayesian network based algorithm called “Module Networks”. The inferred TRNs contain 49 regulatory modules that show condition-specific gene regulation. Through a thorough validation based on prior biological knowledge including functional annotations and TF binding site enrichment, our network prediction displayed high accuracy and concordance with existing knowledge. One regulatory module was partially validated using network perturbations caused by Tri6 and Tri10 gene disruptions, as well as using Tri6 Chip-seq data. We then developed a novel computational method to calculate the associations between modules and phenotypes, and identified major module groups regulating different phenotypes. As a result, we identified TRN subnetworks responsible for F. graminearum virulence, sexual reproduction and mycotoxin production, pinpointing phenotype-associated modules and key regulators. Finally, we found a clear compartmentalization of TRN modules in core and lineage-specific genomic regions in F. graminearum, reflecting the evolution of the TRNs in fungal speciation.

Conclusions

This system-level reconstruction of filamentous fungal TRNs provides novel insights into the intricate networks of gene regulation that underlie key processes in F. graminearum pathobiology and offers promise for the development of improved disease control strategies.

Integration of Cross Species RNA-seq Meta-Analysis and Machine-Learning Models Identifies the Most Important Salt Stress-Responsive Pathways in Microalga Dunaliella

Photosynthetic microalgae are potentially yielding sources of different high-value secondary metabolites. Salinity is a complex stress that influences various metabolite-related pathways in microalgae. To obtain a clear view of the underlying metabolic pathways and resolve contradictory information concerning the transcriptional regulation of Dunaliella species in salt stress conditions, RNA-seq meta-analysis along with systems levels analysis was conducted. A p-value combination technique with Fisher method was used for cross species meta-analysis on the transcriptomes of two Dunaliella salina and Dunaliellatertiolecta species. The potential functional impacts of core meta-genes were surveyed based on gene ontology and network analysis. In the current study, the integration of supervised machine-learning algorithms with RNA-seq meta-analysis was performed. The analysis shows that the lipid and nitrogen metabolism, structural proteins of photosynthesis apparatus, chaperone-mediated autophagy, and ROS-related genes are the keys and core elements of the Dunaliella salt stress response system. Cross-talk between Ca²⁺ signal transduction, lipid accumulation, and ROS signaling network in salt stress conditions are also proposed. Our novel approach opens new avenues for better understanding of microalgae stress response mechanisms and for selection of candidate gene targets for metabolite production in microalgae.

Fusarium graminearum Trichothecene Mycotoxins: Biosynthesis, Regulation, and Management

Fusarium head blight (FHB) of small grain cereals caused by Fusarium graminearum and other Fusarium species is an economically important plant disease worldwide. Fusarium infections not only result in severe yield losses but also contaminate grain with various mycotoxins, especially deoxynivalenol (DON). With the complete genome sequencing of F. graminearum, tremendous progress has been made during the past two decades toward understanding the basis for DON biosynthesis and its regulation. Here, we summarize the current understanding of DON biosynthesis and the effect of regulators, signal transduction pathways, and epigenetic modifications on DON production and the expression of biosynthetic TRI genes. In addition, strategies for controlling FHB and DON contamination are reviewed. Further studies on these biosynthetic and regulatory systems will provide useful knowledge for developing novel management strategies to prevent FHB incidence and mycotoxin accumulation in cereals.

Modeling the Role of the Microbiome in Evolution

There is undeniable evidence showing that bacteria have strongly influenced the evolution and biological functions of multicellular organisms. It has been hypothesized that many host-microbial interactions have emerged so as to increase the adaptive fitness of the holobiont (the host plus its microbiota). Although this association has been corroborated for many specific cases, general mechanisms explaining the role of the microbiota in the evolution of the host are yet to be understood. Here we present an evolutionary model in which a network representing the host adapts in order to perform a predefined function. During its adaptation, the host network (HN) can interact with other networks representing its microbiota. We show that this interaction greatly accelerates and improves the adaptability of the HN without decreasing the adaptation of the microbial networks. Furthermore, the adaptation of the HN to perform several functions is possible only when it interacts with many different bacterial networks in a specialized way (each bacterial network participating in the adaptation of one function). Disrupting these interactions often leads to non-adaptive states, reminiscent of dysbiosis, where none of the networks the holobiont consists of can perform their respective functions. By considering the holobiont as a unit of selection and focusing on the adaptation of the host to predefined but arbitrary functions, our model predicts the need for specialized diversity in the microbiota. This structural and dynamical complexity in the holobiont facilitates its adaptation, whereas a homogeneous (non-specialized) microbiota is inconsequential or even detrimental to the holobiont's evolution. To our knowledge, this is the first model in which symbiotic interactions, diversity, specialization and dysbiosis in an ecosystem emerge as a result of coevolution. It also helps us understand the emergence of complex organisms, as they adapt more easily to perform multiple tasks than non-complex ones.

Comparison of gene co-networks analysis provide a systems view of rice (Oryza sativa L.) response to Tilletia horrida infection

The biotrophic soil-borne fungus Tilletia horrida causes rice kernel smut, an important disease affecting the production of rice male sterile lines in most hybrid rice growing regions of the world. There are no successful ways of controlling this disease and there has been little study of mechanisms of resistance to T. horrida. Based on transcriptional data of different infection time points, we found 23, 782 and 23, 718 differentially expressed genes (fragments per kilobase of transcript sequence per million, FPKM >1) in Jiangcheng 3A (resistant to T. horrida) and 9311A (susceptible to T. horrida), respectively. In order to illuminate the differential responses of the two rice male sterile lines to T. horrida, we identified gene co-expression modules using the method of weighted gene co-expression network analysis (WGCNA) and compared the different biological functions of gene co-expression networks in key modules at different infection time points. The results indicated that gene co-expression networks in the two rice genotypes were different and that genes contained in some modules of the two groups may play important roles in resistance to T. horrida, such as DTH8 and OsHop/Sti1a. Furthermore, these results provide a global view of the responses of two different phenotypes to T. horrida, and assist our understanding of the regulation of expression changes after T. horrida infection.

Comparison of gene co-networks reveals the molecular mechanisms of the rice (Oryza sativa L.) response to Rhizoctonia solani AG1 IA infection

Rhizoctonia solani causes rice sheath blight, an important disease affecting the growth of rice (Oryza sativa L.). Attempts to control the disease have met with little success. Based on transcriptional profiling, we previously identified more than 11,947 common differentially expressed genes (TPM > 10) between the rice genotypes TeQing and Lemont. In the current study, we extended these findings by focusing on an analysis of gene co-expression in response to R. solani AG1 IA and identified gene modules within the networks through weighted gene co-expression network analysis (WGCNA). We compared the different genes assigned to each module and the biological interpretations of gene co-expression networks at early and later modules in the two rice genotypes to reveal differential responses to AG1 IA. Our results show that different changes occurred in the two rice genotypes and that the modules in the two groups contain a number of candidate genes possibly involved in pathogenesis, such as the VQ protein. Furthermore, these gene co-expression networks provide comprehensive transcriptional information regarding gene expression in rice in response to AG1 IA. The co-expression networks derived from our data offer ideas for follow-up experimentation that will help advance our understanding of the translational regulation of rice gene expression changes in response to AG1 IA.

Expression of a Structural Protein of the Mycovirus FgV-ch9 Negatively Affects the Transcript Level of a Novel Symptom Alleviation Factor and Causes Virus Infection-Like Symptoms in Fusarium graminearum

Infections of fungi by mycoviruses are often symptomless but sometimes also fatal, as they perturb sporulation, growth, and, if applicable, virulence of the fungal host. Hypovirulence-inducing mycoviruses, therefore, represent a powerful means to defeat fungal epidemics on crop plants. Infection with Fusarium graminearum virus China 9 (FgV-ch9), a double-stranded RNA (dsRNA) chrysovirus-like mycovirus, debilitates Fusarium graminearum, the causal agent of fusarium head blight. In search for potential symptom alleviation or aggravation factors in F. graminearum, we consecutively infected a custom-made F. graminearum mutant collection with FgV-ch9 and found a mutant with constantly elevated expression of a gene coding for a putative mRNA-binding protein that did not show any disease symptoms despite harboring large amounts of virus. Deletion of this gene, named virus response 1 (vr1), resulted in phenotypes identical to those observed in the virus-infected wild type with respect to growth, reproduction, and virulence. Similarly, the viral structural protein coded on segment 3 (P3) caused virus infection-like symptoms when expressed in the wild type but not in the vr1 overexpression mutant. Gene expression analysis revealed a drastic downregulation of vr1 in the presence of virus and in mutants expressing P3. We conclude that symptom development and severity correlate with gene expression levels of vr1 This was confirmed by comparative transcriptome analysis, showing a large transcriptional overlap between the virus-infected wild type, the vr1 deletion mutant, and the P3-expressing mutant. Hence, vr1 represents a fundamental host factor for the expression of virus-related symptoms and helps us understand the underlying mechanism of hypovirulence.IMPORTANCE Virus infections of phytopathogenic fungi occasionally impair growth, reproduction, and virulence, a phenomenon referred to as hypovirulence. Hypovirulence-inducing mycoviruses, therefore, represent a powerful means to defeat fungal epidemics on crop plants. However, the poor understanding of the molecular basis of hypovirulence induction limits their application. Using the devastating fungal pathogen on cereal crops, Fusarium graminearum, we identified an mRNA binding protein (named virus response 1, vr1) which is involved in symptom expression. Downregulation of vr1 in the virus-infected fungus and vr1 deletion evoke virus infection-like symptoms, while constitutive expression overrules the cytopathic effects of the virus infection. Intriguingly, the presence of a specific viral structural protein is sufficient to trigger the fungal response, i.e., vr1 downregulation, and symptom development similar to virus infection. The advancements in understanding fungal infection and response may aid biological pest control approaches using mycoviruses or viral proteins to prevent future Fusarium epidemics.

Identification of Antifungal Targets Based on Computer Modeling

Aspergillus fumigatus is a saprophytic, cosmopolitan fungus that attacks patients with a weak immune system. A rational solution against fungal infection aims to manipulate fungal metabolism or to block enzymes essential for Aspergillus survival. Here we discuss and compare different bioinformatics approaches to analyze possible targeting strategies on fungal-unique pathways. For instance, phylogenetic analysis reveals fungal targets, while domain analysis allows us to spot minor differences in protein composition between the host and fungi. Moreover, protein networks between host and fungi can be systematically compared by looking at orthologs and exploiting information from host⁻pathogen interaction databases. Further data—such as knowledge of a three-dimensional structure, gene expression data, or information from calculated metabolic fluxes—refine the search and rapidly put a focus on the best targets for antimycotics. We analyzed several of the best targets for application to structure-based drug design. Finally, we discuss general advantages and limitations in identification of unique fungal pathways and protein targets when applying bioinformatics tools.

Transcriptomics of cereal-Fusarium graminearum interactions: what we have learned so far

The ascomycete fungal pathogen Fusarium graminearum causes the globally important Fusarium head blight (FHB) disease on cereal hosts, such as wheat and barley. In addition to reducing grain yield, infection by this pathogen causes major quality losses. In particular, the contamination of food and feed with the F. graminearum trichothecene toxin deoxynivalenol (DON) can have many adverse short- and long-term effects on human and animal health. During the last decade, the interaction between F. graminearum and both cereal and model hosts has been extensively studied through transcriptomic analyses. In this review, we present an overview of how such analyses have advanced our understanding of this economically important plant-microbe interaction. From a host point of view, the transcriptomes of FHB-resistant and FHB-susceptible cereal genotypes, including near-isogenic lines (NILs) that differ by the presence or absence of quantitative trait loci (QTLs), have been studied to understand the mechanisms of disease resistance afforded by such QTLs. Transcriptomic analyses employed to dissect host responses to DON have facilitated the identification of the genes involved in toxin detoxification and disease resistance. From the pathogen point of view, the transcriptome of F. graminearum during pathogenic vs. saprophytic growth, or when infecting different cereal hosts or different tissues of the same host, have been studied. In addition, comparative transcriptomic analyses of F. graminearum knock-out mutants with altered virulence have provided new insights into pathogenicity-related processes. The F. graminearum transcriptomic data generated over the years are now being exploited to build a systems level understanding of the biology of this pathogen, with an ultimate aim of developing effective and sustainable disease prevention strategies.

Statistical and Machine Learning Approaches to Predict Gene Regulatory Networks From Transcriptome Datasets

Statistical and machine learning (ML)-based methods have recently advanced in construction of gene regulatory network (GRNs) based on high-throughput biological datasets. GRNs underlie almost all cellular phenomena; hence, comprehensive GRN maps are essential tools to elucidate gene function, thereby facilitating the identification and prioritization of candidate genes for functional analysis. High-throughput gene expression datasets have yielded various statistical and ML-based algorithms to infer causal relationship between genes and decipher GRNs. This review summarizes the recent advancements in the computational inference of GRNs, based on large-scale transcriptome sequencing datasets of model plants and crops. We highlight strategies to select contextual genes for GRN inference, and statistical and ML-based methods for inferring GRNs based on transcriptome datasets from plants. Furthermore, we discuss the challenges and opportunities for the elucidation of GRNs based on large-scale datasets obtained from emerging transcriptomic applications, such as from population-scale, single-cell level, and life-course transcriptome analyses.

Deciphering Pathogenicity of Fusarium oxysporum From a Phylogenomics Perspective

Fusarium oxysporum is a large species complex of both plant and human pathogens that attack a diverse array of species in a host-specific manner. Comparative genomic studies have revealed that the host-specific pathogenicity of the F. oxysporum species complex (FOSC) was determined by distinct sets of supernumerary (SP) chromosomes. In contrast to common vertical transfer, where genetic materials are transmitted via cell division, SP chromosomes can be transmitted horizontally between phylogenetic lineages, explaining the polyphyletic nature of the host-specific pathogenicity of the FOSC. The existence of a diverse array of SP chromosomes determines the broad host range of this species complex, while the conserved core genome maintains essential house-keeping functions. Recognition of these SP chromosomes enables the functional and structural compartmentalization of F. oxysporum genomes. In this review, we examine the impact of this group of cross-kingdom pathogens on agricultural productivity and human health. Focusing on the pathogenicity of F. oxysporum in the phylogenomic framework of the genus Fusarium, we elucidate the evolution of pathogenicity within the FOSC. We conclude that a population genomics approach within a clearly defined phylogenomic framework is essential not only for understanding the evolution of the pathogenicity mechanism but also for identifying informative candidates associated with pathogenicity that can be developed as targets in disease management programs.

Connecting virulence pathways to cell-cycle progression in the fungal pathogen Cryptococcus neoformans

Proliferation and host evasion are critical processes to understand at a basic biological level for improving infectious disease treatment options. The human fungal pathogen Cryptococcus neoformans causes fungal meningitis in immunocompromised individuals by proliferating in cerebrospinal fluid. Current antifungal drugs target "virulence factors" for disease, such as components of the cell wall and polysaccharide capsule in C. neoformans. However, mechanistic links between virulence pathways and the cell cycle are not as well studied. Recently, cell-cycle synchronized C. neoformans cells were profiled over time to identify gene expression dynamics (Kelliher et al., PLoS Genet 12(12):e1006453, 2016). Almost 20% of all genes in the C. neoformans genome were periodically activated during the cell cycle in rich media, including 40 genes that have previously been implicated in virulence pathways. Here, we review important findings about cell-cycle-regulated genes in C. neoformans and provide two examples of virulence pathways-chitin synthesis and G-protein coupled receptor signaling-with their putative connections to cell division. We propose that a "comparative functional genomics" approach, leveraging gene expression timing during the cell cycle, orthology to genes in other fungal species, and previous experimental findings, can lead to mechanistic hypotheses connecting the cell cycle to fungal virulence.

Transcription Factors Encoded on Core and Accessory Chromosomes of Fusarium oxysporum Induce Expression of Effector Genes

Proteins secreted by pathogens during host colonization largely determine the outcome of pathogen-host interactions and are commonly called 'effectors'. In fungal plant pathogens, coordinated transcriptional up-regulation of effector genes is a key feature of pathogenesis and effectors are often encoded in genomic regions with distinct repeat content, histone code and rate of evolution. In the tomato pathogen Fusarium oxysporum f. sp. lycopersici (Fol), effector genes reside on one of four accessory chromosomes, known as the 'pathogenicity' chromosome, which can be exchanged between strains through horizontal transfer. The three other accessory chromosomes in the Fol reference strain may also be important for virulence towards tomato. Expression of effector genes in Fol is highly up-regulated upon infection and requires Sge1, a transcription factor encoded on the core genome. Interestingly, the pathogenicity chromosome itself contains 13 predicted transcription factor genes and for all except one, there is a homolog on the core genome. We determined DNA binding specificity for nine transcription factors using oligonucleotide arrays. The binding sites for homologous transcription factors were highly similar, suggesting that extensive neofunctionalization of DNA binding specificity has not occurred. Several DNA binding sites are enriched on accessory chromosomes, and expression of FTF1, its core homolog FTF2 and SGE1 from a constitutive promoter can induce expression of effector genes. The DNA binding sites of only these three transcription factors are enriched among genes up-regulated during infection. We further show that Ftf1, Ftf2 and Sge1 can activate transcription from their binding sites in yeast. RNAseq analysis revealed that in strains with constitutive expression of FTF1, FTF2 or SGE1, expression of a similar set of plant-responsive genes on the pathogenicity chromosome is induced, including most effector genes. We conclude that the Fol pathogenicity chromosome may be partially transcriptionally autonomous, but there are also extensive transcriptional connections between core and accessory chromosomes.