Next Article in Journal
Detection of Porcine Circovirus 3 in Wildlife Species in Spain
Next Article in Special Issue
Occurrence, Pathogenicity, and Mycotoxin Production of Fusarium temperatum in Relation to Other Fusarium Species on Maize in Germany
Previous Article in Journal
Tripartite Interactions among Ixodiphagus hookeri, Ixodes ricinus and Deer: Differential Interference with Transmission Cycles of Tick-Borne Pathogens
Previous Article in Special Issue
Three-Locus Sequence Identification and Differential Tebuconazole Sensitivity Suggest Novel Fusarium equiseti Haplotype from Trinidad
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Pathogens
Volume 9
Issue 5
10.3390/pathogens9050340
pathogens-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Pathogenomics and Management of Fusarium Diseases in Plants

by
Sephra N. Rampersad
Department of Life Sciences, Faculty of Science and Technology, The University of the West Indies, St. Augustine, Trinidad and Tobago-West Indies
Pathogens 2020, 9(5), 340; https://doi.org/10.3390/pathogens9050340
Submission received: 3 April 2020 / Revised: 25 April 2020 / Accepted: 28 April 2020 / Published: 1 May 2020
(This article belongs to the Special Issue Fusarium: Pathogenomics and Inherent Resistance)
Browse Figure
Versions Notes

Abstract

:
There is an urgency to supplant the heavy reliance on chemical control of Fusarium diseases in different economically important, staple food crops due to development of resistance in the pathogen population, the high cost of production to the risk-averse grower, and the concomitant environmental impacts. Pathogenomics has enabled (i) the creation of genetic inventories which identify those putative genes, regulators, and effectors that are associated with virulence, pathogenicity, and primary and secondary metabolism; (ii) comparison of such genes among related pathogens; (iii) identification of potential genetic targets for chemical control; and (iv) better characterization of the complex dynamics of host–microbe interactions that lead to disease. This type of genomic data serves to inform host-induced gene silencing (HIGS) technology for targeted disruption of transcription of select genes for the control of Fusarium diseases. This review discusses the various repositories and browser access points for comparison of genomic data, the strategies for identification and selection of pathogenicity- and virulence-associated genes and effectors in different Fusarium species, HIGS and successful Fusarium disease control trials with a consideration of loss of RNAi, off-target effects, and future challenges in applying HIGS for management of Fusarium diseases.

Graphical Abstract

1. Introduction

Early in the genomic era, the scientific community relied on a single “reference” genome for a given species due to the prohibitive cost associated with sequencing an entire genome. The genomic features to be studied included gene sequences, gene order, gene clusters, regulatory sequences, and other genomic organizational landmarks. In light of the pace of genomic research, a significant reduction in whole genome sequencing cost (depending on country, size of the genome, and technology used) enabled genomes to be sequenced faster, at greater depth, and with increased sensitivity [1]. A single reference genome is inadequate. Comparative sequence analysis of an assorted collection of genomes belonging to a number of individuals within a given species is preferred as the assemblage of a “pan-genome” offers more advantages [2]. Genomic data must be understood in the context of biological function and the complex, nonlinear relationship between genotype and phenotype [3].
Pathogenomics is a high-resolution approach that refers to the generation and analysis of whole genome sequences of oomycete, fungal, bacterial, and viral pathogens in order (i) to identify genes and their regulators that are associated with virulence, pathogenicity, and primary and secondary metabolism; (ii) to compare such genes among related pathogens; (iii) to reveal potential genetic targets for chemical control; and (iv) ultimately, to better understand the complex dynamics of host–microbe interactions that lead to disease [4].

2. Fusarium as Plant Pathogens

Fusarium is among the most economically important genera of fungi in the world and is one of the most studied [5]; there were 25,704 publications on Fusarium in PubMed Central at the time of writing this review. The genus comprises at least 300 phylogenetically distinct species; 20 species complexes and nine monotypic lineages have been identified to date [6]. Although the majority of Fusarium species are soil-inhabiting fungi, Fusarium conidia can be dispersed by water in rain splash and via irrigation systems but become airborne when dried, which makes them well-suited for atmospheric dispersal over long distances and which contributes to their worldwide distribution [7,8,9,10]. Far less common is insect dispersal, but it nevertheless plays a critical role in the dispersal of F. verticillioides [11,12]. Although Fusarium utilizes multiple infection strategies, these fungi are considered to be hemibiotrophs capable of transitioning to necrotrophs depending on specific environmental and metabolic cues [13]. As plant pathogens, they cause root and stem rot, vascular wilt, and/or fruit rot in a number of economically crop species resulting in major yield losses (MT ha-1) and in economic losses that value over $1B [14,15,16]. Additionally, in clinical settings, several species are considered to be opportunistic pathogens in immunocompromised humans [17,18].

3. The Urgency to Develop Non-chemical Control Strategies

Sustainable management of plant diseases is challenged by the complexity of meeting the world’s demand for safe and diversified food. Food production must cope with a reduction in production potential in exhausted soil and land competition in fertile areas, loss of biodiversity in agroecosystems, increased risk of disease emergence and epidemics due to agricultural intensification, a lack of disease-resistant cultivars, monoculture cropping practices favoured by high-value crops, net disease-related costs impacted by fungicide resistance, and fungicide cost plus disease-induced yield loss as well as global climate change [19,20].
Virtually all fungicides produced since the 1980s pose a risk of resistance development [21]. Deconstructing a pathogen’s modes of developing resistance is important to assisting in designing integrated approaches to circumvent or manage the development of resistance and in identifying pathogens with a high to medium to low risk of developing resistance to a specific fungicide or class of fungicides [22,23]. Some of the mechanisms of resistance commonly include (i) mutations that lead to conformational changes to the target site, (ii) mutations of the promoter sequence that lead to upregulation of the gene target, and (iii) reduction of intracellular fungicide accumulation by upregulation of efflux pumps (e.g., adenosine triphosphate-binding cassette (ABC) transporters or major facilitators) [24,25].
Among Fusarium species, reduced sensitivity to single-site fungicides (e.g., methyl benzimidazole carbamates, demethylation inhibitors, quinone outside inhibitors, and succinate dehydrogenase inhibitors) represents indiscriminate, long-term use of these different chemical classes by risk-averse growers [26]. Understanding the mechanisms that drive the evolution and emergence of genotypes bearing reduced fungicide sensitivity will aid resistance risk assessment and management [27]. The switch between hemi-biotrophic and necrotrophic lifestyles, fungicide targets, and history of exposure to a given single-target fungicide influence the selection of resistant genotypes in the pathogen population [26]. Importantly, there are parallel drivers of fungicide resistance in clinical settings and in the field with cases of cross resistance [28].
De novo mutations and standing genetic variation affect the likelihood and rate of emergence of resistant genotypes over evolutionary time [29,30]. Selection from standing variation as well as identification of additional, non-target-site resistance mechanism(s) can be inferred by tracing the history of the selected target gene through comparative genomics [30,31] for example, comparison of amino acid mutations in CYP51 paralogues and their corresponding azole resistance phenotypes among Fusarium species [32,33,34,35]. The potential to use complete genome sequences for gene target identification is theoretically unlimited; however, validation of genome information requires the integration of chemical-genetic and genetic interaction data [36,37].
Innovation in fungicide development is warranted [21]. Phenamacril, a cyanoacrylate compound (JS399-19), was identified as a new type of fungicide with a mode of action that was different to any other known class of fungicides [38,39,40]. Phenamacril exhibits reversible and noncompetitive inhibition of ATP turnover, specifically “actin-binding during ATP-turnover and motor activity” of F. graminearum and F. avenaceum but not F. solani [41]. Zheng et al. [42] used whole-genome sequencing to determine the basis of resistance of F. graminearum to phenamacril in in vitro experiments. The study concluded that single nucleotide polymorphisms in the mycosin-5 gene, mainly A > G and T > C transitions which are translated to non-synonymous amino acid mutations, were the cause of phenamacril resistance in F. graminearum. Zhou et al. [43] recently explained that reduced sensitivity to phenamacril was due to a single amino acid substitution (M375K) located in the phenamacril-binding pocket and which was found in the myosin I motor domains of phenamacril-sensitive Fusarium species based on first-time analysis of the structure of FgMyoI (1–736). Fungicide resistance and the lack of resistant cultivars of economically important food crops have prompted the Fusarium research community to explore alternate crop protection strategies.

4. Fusarium Genomics

The highest proportion of genome sequences that are available in public repositories belong to pathogenic fungi and fungi of medical importance, with plant pathogenic fungi being the most predominant in this group [44]. The majority of plant pathogens are fungi [45], and these sequenced genomes belong to fungal species that infect at least one food crop including cereals, fruit, vegetables, and legumes, some of which constitute staple food crops in several countries worldwide whether for human consumption, livestock, and/or biofuels [46]. Fungal plant pathogens are well represented in genome sequencing efforts, and this emphasis may be driven, in part, by those fungal species that destabilize global food security and pose a biosecurity threat [44,47]. Plant pathogenic fungi are among the best-studied models of pathogen evolution based on genome sequence analysis [48]. The value of Fusarium genome data to disease management lies in an improved understanding of (i) pathogenicity-related factors (structure and function), (ii) stimulus-based shifts in trophic lifestyles, (iii) infection strategies, (iv) genome organization and evolution, (v) prediction of risk of emergence of new strains and future disease outbreaks, (vi) species complex genetic diversity as dictated by specific genomic regions, (vii) origin and acquisition of pathogenicity-related genes, (viii) the transfer of entire pathogenicity-related chromosomes, and (ix) the risk of developing fungicide resistance [49,50,51,52,53,54,55].
Pathogenomics (systematic analysis of genome sequences of pathogenic microbes) is hinged on the development of several complementary multispecies databases that provide gene function annotation. There are 69 Fusarium genome reports, 116 species and 558 genome assemblies are available, and 19 complete Fusarium genomes have been published according to NCBI Genomes. However, not all the genomes are annotated. Functional gene annotations are fundamental to selecting potential gene targets for gene silencing studies [56]. New pathogen–host interaction mechanisms can be revealed by integrating mutant phenotype data with genetic information. Each database specializes in particular species/pathogen groups and/or uses only automated approaches to knowledge acquisition (Table 1).

5. Host-induced Gene Silencing (HIGS)

In plant–microbe interactions, plants recognize conserved molecular patterns on the surface of microbes (microbe- or pathogen-associated molecular patterns (MAMPs and PAMPs)) using pattern recognition receptors (PRRs), which activate innate immunity against these microbes [67,68,69]. In fungal infections, the polysaccharide component of fungal cell walls (e.g., chitin) is recognized by the plant host [70]. Pathogens produce small proteins which are secreted into the plant cell to suppress this immune response and to allow colonisation [71,72,73,74,75,76]. However, some fungi (e.g., Botrytis cinerea) are capable of producing non-protein, fungus-derived sRNAs (short RNAs) that are transmitted into the host plant cell during infection and which serve as “RNA effectors” to disrupt immune signaling and to suppress host immunity [77]. Interestingly, host-derived sRNAs were detected in Verticillium dahliae, where they functioned to target the fungal pathogen’s virulence genes to inhibit fungal invasion in a “trans-kingdom RNAi” phenomenon [78]. Although several proposed translocation approaches have been hypothesized [79], very little empirical evidence has been described to explain the mechanism(s) of sRNA transfer from plant cells into fungal cells [80]. One exception was reported for F. graminearum infecting barley, where DICER-LIKE (DCL) gene expression was not required for natural infection but is required for fungal gene silencing by artificial dsRNA transfer [80]. This data suggests that fungal DCL enzymes may be involved in processing mobile plant-derived sRNA based on this specific pathogen–host interaction. Host adaptation by fungal pathogens can be facilitated by chromosomal reshuffling and horizontal gene transfer in addition to uptake of trans-kingdom sRNA [73,81].
Neurospora crassa was the model fungus for studying RNAi pathways and the core RNAi machinery involved, i.e., Dicer, Argonaute, and RNA-dependent RNA-polymerases (RdRps) in eukaryotes [82]. Gene silencing at the posttranscriptional level is activated through recognition of intracellular, long double-stranded (dsRNA), or RNAs containing secondary structures (e.g., hairpin and/or stem-loop). Such RNA molecules are cleaved into small RNAs (sRNAs; typically 19 to 25 nt in length) by Dicer enzymes or DICER-LIKE (DCL1) enzymes (RNase III endonucleases) in plants [78]. The resulting small dsRNAs (small interfering RNA (siRNA)) are assembled onto ARGONAUTE (AGO) proteins to produce a ribonucleoprotein complex called the RNA-induced silencing complex (RISC) [83,84]. The double strands dissociate into single strands of sRNA. This activates RISC which is then directed to a sequence-specific transcript located in the cytoplasm. Hybridization of these sRNA molecules with target mRNA sequence, through complementary base-pairing, results in interference of the translation machinery, translational repression of the target sequence, or mRNA decay [85]. The RNAi machinery in F. graminearum includes two Dicer proteins (FgDicer1 and FgDicer2), two ARGONAUTE proteins (FgAgo1 and FgAgo2), and five RNA-dependent RNA polymerases (RdRps) (FgRdRp1–5) [86]. The silencing mechanism requires RdRPs to generate dsRNA from single-stranded RNA (ssRNA) [85].
Plants can export both exogenous artificial siRNAs (small interfering RNAs) and endogenously produced miRNAs (micro-RNAs) into infecting fungal cells to target fungal transcripts [87]. Host-induced gene silencing (HIGS) technology capitalizes on this innate protection mechanism of plants, where siRNA molecules of the plant host are used to downregulate the expression of target genes of pathogens in a sequence-specific manner. Baldwin et al. [88] determined that the silencing efficacy of RNAi vectors varied according to the size and location of the targeted regions of the TRI6 gene of the trichothecene biosynthetic gene cluster. This understanding has enabled HIGS to be successfully used to protect plants against fungal pathogens including Fusarium [68,80,87,89,90]. HIGS requires a transgene carrier system including either a virus-based system (e.g., BSMV (Barley stripe mosaic virus)) or agrobacterium-mediated (AGT (agrobacterium transformation)) transgenic system for introduction of the artificial dsRNA construct into the plant. Certain fungi (e.g., B. cinerea and F. graminearum) have the ability to take up exogenous dsRNAs from the environment [90]. dsRNAs can also be translocated through the vascular system of the plant [80]. This capability facilitated the development of spray-induced gene silencing (SIGS) technology for crop protection against Fusarium where artificial dsRNAs targeting pathogen virulence-related genes are sprayed onto the infected host plant [89,90,91,92,93]. Table 2 outlines research carried out using HIGS and specific target genes for management of Fusarium diseases in different crop hosts from 2010 to present.

6. Selection of Gene Targets

Sequenced genomes of fungal phytopathogens represent the genetic blueprint from which putative pathogenic and virulence factors can be identified; resolution of these factors into different roles played in various infection strategies can also be inferred [44]. Fungal pathogenomics facilitated the identification of fungal genes associated with pathogenesis and virulence and provided the rationale behind selection of gene targets for HIGS technology for management of Fusarium diseases. For most target genes, a function in pathogenicity and virulence has been investigated experimentally by gene disruption, gene knockdown, gene complementation, or overexpression assays (PHI-base; http://www.phi-base.org/).
The intersection of genomics and plant pathology has blurred some of the basic concepts in plant pathology. It is, therefore, worth clarifying the often interchangeable use of “Pathogenicity” vs. “Virulence”. Pathogenicity refers to the capability of a pathogen to cause disease; virulence refers to the severity of disease caused by the pathogen, i.e., the measurable degree of damage caused by a pathogen to the host plant [107]. In PHI-base, these pathogenicity- and virulence-associated genes are classified according to mutant phenotypes, i.e., loss of pathogenicity, unaffected pathogenicity, increased virulence, and reduced virulence. Examples of these genes are given in Table 3 and Table 4. F. graminearum was omitted from Table 3 because there were >500 genes associated with “reduced virulence” mutant phenotype in PHI-base. Other reviews summarized similar data for F. graminearum, the most recent being Rauwane et al. 2020 [108]. Note that genes related to pathogenicity are not the same genes related to virulence in most cases. The largest number of genes collectively associated with a “loss of pathogenicity” mutant phenotype was recorded for F. graminearum; the number of genes associated with a “reduced virulence” mutant phenotype was highest for F. oxysporum, according to PHI-base.

6.1. Pathogen Effectors

Genome-based effector characterization has strongly supported the study of pathogenic determinants [57,58]. An effector protein selectively binds to a target protein and regulates its biological function. Phytopathogenic fungi produce a range of effectors that can (i) alter the structure and function of the host cell; (ii) activate effector-triggered immunity (ETI) based on effector perception by R proteins in the host plant; and/or (iii) accumulate mutations and, as such, develop novel effectors that are no longer recognized by R proteins, which enables the fungus to avoid or suppress ETI in the host plant [71,72]. Pathogen effectors are usually small proteins that contain N-terminal signal peptides, are cysteine-rich, and are highly expressed by the pathogen in planta [56,109]. Fungal effectors may be secreted into the extracellular space of the host tissues or they can enter host cells [110,111]. Intracellularly located effectors can disrupt plant immune responses and can facilitate colonization of the plant host [112]. Diversifying selection is most prominent for positive selection of genes that encode effector proteins [113]. The F. graminearum genome has 1250 putative genes that encode small, secreted proteins, a substantial number of which are suspected to be effectors (reviewed by Schmidt and Panstruga [4]). Not all effector candidates are necessary for pathogenic fungus–plant interactions; the reason is a large percentage of these putative effectors share homologs in other Fusarium species and in a broad range of filamentous fungi [114]. “True effector genes” have a relatively rapid rate of evolution and generally lack homologs in closely related species [115]; they are preferentially located in “repeat-rich and gene-poor regions” of the genome (Dong et al. [116]). Furthermore, transcription of effector genes is highly regulated and synchronized with host colonization, which is important to activating the switch from hemibiotrophic and necrotrophic phases in Fusarium species [48].
However, because these effector inventories are curated from bioinformatics analyses of genomic and transcriptomic data, most small secreted proteins identified by this approach are assumed to be effectors even though there may not be evidence of direct association with disease and they may also be found in mutualistic fungi [56]. Studies have revealed that many fungal genes considered to be associated with disease progression are also involved in general fungal growth and development, referred to as “functional redundancy” [113]. For these reasons, functional analysis of candidate pathogenicity genes is important to improve the accuracy of these effector inventories.

6.2. Pathogenicity Genes

van de Wouw and Howlett [56] described pathogenicity genes as genes that encode host-specific proteins which demonstrate an “inverse” gene-for-gene relationship with the host such that the host–pathogen interaction results in disease. Pathogenicity genes are generalized into two classes: basic pathogenicity genes, which are shared by Fusarium and other pathogenic fungi, and specialized pathogenicity genes, which in most cases are specific to individual Fusarium species on specific hosts. Over 100 genes were found to alter virulence specifically in F. graminearum based on experimental evidence (PHI-base). It is important to describe the biological context of these genes, and one approach involves prediction of function using integrated networks that compares amino acid sequence similarity and maps known or predicted protein–protein interactions [82,117].

6.2.1. Basic Pathogenicity Genes

Functional characterization of putative genes indicated that those involved in the production of cell wall-degrading enzymes; transcriptional regulators for carbon, nitrogen, amino acid, and lipid metabolism; factors involved in host cell wall remodeling; protein translocation and degradation; and interruption of phyto-hormone pathways are all important for pathogenicity [118,119,120,121], reporting over 100 putative pathogenicity genes in F. oxysporum f. sp. lycopersici (FOL). Mitogen-activated protein kinase (MAPK) and cyclic AMP-protein kinase A (cAMP-PKA) were also found to be important regulators of virulence in F. oxysporum [120,121,122,123,124,125]. Genes encoding modulators of host immune responses are often organized in distinct genomic compartments [116].
Proteins involved in primary metabolism are common in Fusarium and other pathogenic fungi because they catalyze conserved biochemical pathways [126]. Shang et al. [127] reported on the relationship between pathogenicity and protein families involved in the hydrolysis of host cell constituents, e.g., carbohydrate-active enzymes (CAZymes), proteases, cellulolytic enzymes, cutinases, and lipases. Metalloprotease subfamilies M14 and M28, serine peptidases S09 and S26, O-glycosyl hydrolases, glycosyl transferases, polysaccharide lyases, carbohydrate-binding domain proteins, cutin polymers, pectin lyases (PL1 and PL3) as well as the UDP (uridine 5’-diphosphate)-glucuronosyl transferase (GT1), and acetyl xylan esterase (CE1) were significantly associated with pathogen lifestyle adaptation. The Fgl1 gene, which encodes a secreted lipase, has been shown to be directly involved in virulence of F. graminearum of barley, maize, and wheat [128,129]. Further, if this Fgl1 gene is overexpressed, the virulence of nonpathogenic MAPK mutant on wheat is restored [130].

6.2.2. Specialized Effectors and Pathogenicity Genes in Fusarium

Several specialized Fusarium genes are involved in host–pathogen interactions [110,114]. Comparative studies of the genomes of F. oxysporum f. sp. lycopersici (FOL) identified lineage-specific mobile pathogenicity chromosomes which contain pathogenicity-associated genes [40]. These include Secreted In Xylem (SIX) genes that encode small effector proteins which are secreted by FOL during infection of tomato plants [50]. These SIX genes as well as Fusarium transcription factor (FTF)-encoded genes (FTF1 and FTF2), which are involved in transcription of these SIX genes, are located on an accessory chromosome that can be transferred horizontally between strains [131]. There are two identified genes of the FTF gene family: FTF2, which is present as a single copy in all the filamentous ascomycetes analysed, and FTF1, which is present in multiple copies and is exclusive to F. oxysporum [132]. PHI-base describes SIX genes-associated transcription factors (Fusarium Transcription Factor, FTF1/2) with “reduced virulence” mutant phenotype in F. oxysporum in Phaseolus vulgaris (kidney bean) host plants.

6.2.3. Pathogenicity Chromosomes

Ma et al. [50] experimentally demonstrated the transfer of entire chromosomes from a pathogenic FOL strain to a nonpathogenic FOL strain of F. oxysporum f. sp. lycopersici. Transfer of an entire complement of genes required for host compatibility to a new genetic background is via horizontal transfer mechanisms [47,131]. Horizontal transfer of supernumerary or lineage-specific (LS) chromosomes is not new in a number of plant pathogenic filamentous fungi; however, Vlaardingerbroek et al. [133] described the transfer of portions of core chromosomes in addition to accessory chromosomes of F. oxysporum f. sp. lycopersici. These mobile chromosomes are referred to as supernumerary or lineage-specific (LS) chromosomes or conditionally dispensable (CD) chromosomes [134]. F. solani is a species complex of >50 closely related species and is the anamorph of Nectria haematococca [109]. Experimental data on fungal supernumerary chromosome function was primarily collected from Cochliobolus carbonum and N. haematococca MP VI in the early to mid-1990s. Five supernumerary chromosomes were found in N. haematococca MP IV and early experimental evidence implicated their involvement in pathogenicity in pea plants [135]. For example, it was found that these CD chromosomes contained PDA and PEP genes responsible for detoxifying phytoalexins and for restoring pathogenicity in chromosome-deficient strains, respectively [109]. The hypothesized model of the “two-speed” genome described compartmentalization of the genome identified by distinct sets of chromosomes, i.e., core and accessory chromosomes, each with different rates of evolution [136].

6.3. Trichothecene Mycotoxins as Specialized Virulence Factors

Trichothecene mycotoxins are proven virulence factors of Fusarium in wheat hosts [51,137,138,139]. Trichothecenes inhibit protein synthesis in eukaryotes, activate host plant defence systems, and promote plant cell death [140]. Comparative genome analyses indicated that the Fusarium genome is compartmentalized into specialty chromosomes and that different biosynthetic gene clusters may be influenced by related gene clusters [114,139]. Individual isolates of Fusarium species can have different trichothecene profiles [141,142,143,144]. Mycotoxins produced by certain Fusarium species can lead to differential virulence toward wheat (Triticum spp.) and maize (Zea mays) [128,137,138] but not barley (Hordeum vulgare) [145]. Table 5 summarizes the trichothecene (TRI) genes recorded as associated with “reduced virulence” according to PHI-base; there were no records of “loss of pathogenicity” for any TRI genes of Fusarium species curated in PHI-base.

6.4. CYP51 Paralogues in Fusarium

CYP51 genes encode sterol 14α-demethylase, and three CYP51 paralogues (CYP51A, CYP51B, and CYP51C) have been described for Fusarium species, of which CYP51C was thought to be unique to this genus [146]. However, UniProt also presents CYP51C references for clinical strains of Aspergillus flavus with reported amino acid substitutions that are associated with azole resistance (entry: [147]; entry: [148]). Constructs for HIGS of F. graminearum causing Fusarium head blight (FHB) included all three CYP51 paralogues based on the rationale that the degree of nucleotide similarity among CYP51 genes from different species is comparatively low (25–30%) for a gene that is present in most eukaryotic organisms [149]. Villafana and Rampersad [35] indicated that CYP51C sequences may have species-specific signatures based on phylogenetic analyses of CYP51C nucleotide sequences of isolates belonging to the F. incarnatum-equiseti species complex from Trinidad. PHI-base describes the mutant phenotypes for F. graminearum as “reduced virulence” and “unaffected pathogenicity” for CYP51A, CYP51B, and CYP51C in four host species; “loss of pathogenicity”, however, was not described as the mutant phenotype for any of the CYP51 genes for any Fusarium species.

7. Redundancy of Function

Although many fungi-derived genes are involved in host–pathogen interactions, direct evidence of association with pathogenicity and virulence is difficult to ascertain depending on the putative target gene. Rauwane et al. [108] reviewed the currently known multitude of putative pathogenicity and virulence factors of F. graminearum (> 100 factors), which is arguably the most studied Fusarium species worldwide. Furthermore, because combinations of effectors are generally employed in the infection process, targeting one would not have an effect on preventing infection.
Genetic redundancy refers to two or more genes that perform the same function and for which inactivation of one of these genes will have little or no effect on the fitness of the organism. Redundancy also facilitates extreme flexibility in gene regulation [113]. All Fusarium genomes encode a wide range of cell wall-degrading enzymes and generalized hydrolytic enzymes with broad substrate-binding affinities. Redundancy of these enzymes increases the adaptability of these pathogens to utilize different nutrient sources depending on availability, and as a result, very few genes involved in such metabolic function have been directly connected to pathogenicity [128,150].

8. Broad Spectrum Activity and Off-target Effects

HIGS can be used to target the same essential gene in different fungal species, allowing broad spectrum control of fungal pathogens [151]. However, broad-spectrum application of HIGS increases the risk of silencing off-target genes in host plants and/or silencing off-target genes of beneficial plant-associated fungi, e.g., mycorrhizal fungi [152,153,154,155] and fungal biocontrol agents (e.g., Trichoderma species) [156]. A single mismatched base pair in a 19-base sequence can prevent duplex formation and can enable cross-hybridization to off-target sequences [157]. For these reasons, candidate siRNAs must be evaluated for homology to potential off-target sequences.

9. Loss of RNAi Gene Silencing in Fungi

Comparative genomic analysis revealed that the protein machinery of RNAi and the dual defensive and regulatory roles played by small RNAs generated within the cell are conserved in all major eukaryotic lineages [158]. The inactivation of RNAi pathways through loss of function of dicer or ARGONAUTE proteins would produce an RNAi-deficient species [159]. This raises the question of how such RNAi-deficient species can survive without a functioning RNAi system. Soybean-infecting oomycete Phytophthora sojae was recently found to produce Phytophthora-encoded suppressors of RNA silencing (PSRs) [160]. The arsenal of pathogenicity-associated effector proteins produced by pathogenic fungi is supported by a high rate of evolution and mutation accumulation. Selection pressures to overcome R protein recognition in host plant defense may explain the low level of homology among effector proteins and their different host specificities [71]. Conversely, HIGS-mediated resistance may be less likely to develop where a combination of multiple, conserved, and essential pathogen biochemistries is targeted [161].

10. Future Challenges

Several of the world’s staple food crops are vulnerable to fungal plant pathogens. Currently used disease management strategies often fail due to development of chemical resistance in the pathogen population and the unavailability of disease-resistant cultivars. Selection pressures attributed to the host, chemical control agents, climate, as well as inter- and intra-specific competition drive the evolution of fungal genomes. The emergence and introduction of pathogens with novel combinations of pathogenicity and virulence factors challenge food security. The rapid generation and release of fungal genomic data contribute important datasets that are relevant to the field of plant pathology. However, the quality of these assemblies can vary, which hampers utility for comparisons and meaningful interpretation. Curated databases of genome sequences and genome browsers must be accessed to ensure quality and completeness of genomic data and to enable comparisons of genome sequences from several individuals within a given species or across species boundaries. Data-mining with subsequent identification of putative pathogenicity- and virulence-related genes must be supported with evidence of function by an integrated protein network analysis as a computational means of understanding metabolic function and/or functional assays. Such data is fundamental to designing transgenic and non-transgenic approaches to disease management. Refinement of the genetic inventory of factors responsible for effecting disease is, therefore, ongoing. Host-induced gene silencing capitalizes on a conserved, RNAi-based mechanism where small RNAs produced in the plant prevent expression of select genes belonging to pathogens as part of an innate plant defense response. It is one approach with demonstrated potential to control Fusarium diseases in some economically important crop hosts. Control has been defined in terms of reduced virulence and/or loss of pathogenicity of the Fusarium pathogen, and these phenotypes can vary according to the host plant species for a given Fusarium species. Management of Fusarium diseases by gene silencing can be potentially achieved without the cost and hazards of chemical protection.

Funding

This research was funded by The University of the West Indies, St. Augustine, Campus Research and Publication Grant #CRP.3.MAR16.12.

Acknowledgments

There are many reviews on Fusarium and the approaches to disease control, some specifically for F. graminearum and FHB management. However, it was impossible to include them all. I thank those researchers whose work could not be cited here for their understanding. I also wish to thank the reviewers for their contributions.

Conflicts of Interest

The author declares no conflict of interest.

References

  1. Schwarze, K.; Buchanan, J.; Taylor, J.C.; Wordsworth, S. Are Whole-Exome and Whole-Genome Sequencing Approaches Cost-Effective? A Systematic Review of the Literature. Genet. Med. 2018, 20, 1122–1130. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Sherman, R.M.; Salzberg, S.L. Pan-Genomics in the Human Genome Era. Nat. Rev. Genet. 2020. [Google Scholar] [CrossRef] [PubMed]
  3. Ahnert, S.E. Structural Properties of Genotype–Phenotype Maps. J. R. Soc. Interface 2017, 14, 20170275. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Schmidt, S.M.; Panstruga, R. Pathogenomics of Fungal Plant Parasites: What Have We Learnt about Pathogenesis? Curr. Opin. Plant Biol. 2011, 14, 392–399. [Google Scholar] [CrossRef]
  5. Dean, R.; Van Kan, J.A.L.; Pretorius, Z.A.; Hammond-Kosack, K.E.; Di Pietro, A.; Spanu, P.D.; Rudd, J.J.; Dickman, M.; Kahmann, R.; Ellis, J.; et al. The Top 10 Fungal Pathogens in Molecular Plant Pathology: Top 10 Fungal Pathogens. Mol. Plant. Pathol. 2012, 13, 414–430. [Google Scholar] [CrossRef] [Green Version]
  6. O’Donnell, K.; Ward, T.J.; Robert, V.A.R.G.; Crous, P.W.; Geiser, D.M.; Kang, S. DNA Sequence-Based Identification of Fusarium: Current Status and Future Directions. Phytoparasitica 2015, 43, 583–595. [Google Scholar] [CrossRef] [Green Version]
  7. Fernando, W.G.D.; Miller, J.D.; Seaman, W.L.; Seifert, K.; Paulitz, T.C. Daily and Seasonal Dynamics of Airborne Spores of Fusarium graminearum and Other Fusarium Species Sampled over Wheat Plots. Can. J. Bot. 2000, 78, 497–505. [Google Scholar] [CrossRef]
  8. Smith, S.N. An Overview of Ecological and Habitat Aspects in the Genus Fusarium with Special Emphasis on the Soil-Borne Pathogenic Forms. Plant. Pathol. Bull. 2007, 16, 97–120. [Google Scholar]
  9. Schmale, D.G.; Ross, S.D.; Fetters, T.L.; Tallapragada, P.; Wood-Jones, A.K.; Dingus, B. Isolates of Fusarium graminearum Collected 40–320 Meters above Ground Level Cause Fusarium Head Blight in Wheat and Produce Trichothecene Mycotoxins. Aerobiologia 2012, 28, 1–11. [Google Scholar] [CrossRef]
  10. Lin, B.; Bozorgmagham, A.; Ross, S.D.; Schmale, D.G., III. Small Fluctuations in the Recovery of Fusaria across Consecutive Sampling Intervals with Unmanned Aircraft 100 m above Ground Level. Aerobiologia 2013, 29, 45–54. [Google Scholar] [CrossRef]
  11. Munkvold, G.P. Epidemiology of Fusarium Diseases and Their Mycotoxins in Maize Ears. Eur. J. Plant Pathol. 2003, 109, 705–713. [Google Scholar] [CrossRef]
  12. Opoku, J.; Kleczewski, N.M.; Hamby, K.A.; Herbert, D.A.; Malone, S.; Mehl, H.L. Relationship Between Invasive Brown Marmorated Stink Bug (Halyomorpha halys) and Fumonisin Contamination of Field Corn in the Mid-Atlantic US. Plant Dis. 2019, 103, 1189–1195. [Google Scholar] [CrossRef] [PubMed]
  13. Perfect, S.E.; Green, J.R. Infection Structures of Biotrophic and Hemibiotrophic Fungal Plant Pathogens. Mol. Plant. Pathol. 2001, 2, 101–108. [Google Scholar] [CrossRef] [PubMed]
  14. Nganje, W.E.; Bangsund, D.A.; Leistritz, F.L.; Wilson, W.W.; Tiapo, N.M. Regional Economic Impacts of Fusarium Head Blight in Wheat and Barley. Appl. Econ. Perspect. Policy 2004, 26, 332–347. [Google Scholar] [CrossRef]
  15. Salgado, J.D.; Madden, L.V.; Paul, P.A. Quantifying the Effects of Fusarium Head Blight on Grain Yield and Test Weight in Soft Red Winter Wheat. Phytopathology 2015, 105, 295–306. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Xia, R.; Schaafsma, A.W.; Wu, F.; Hooker, D.C. Impact of the Improvements in Fusarium Head Blight and Agronomic Management on Economics of Winter Wheat. World Mycotoxin J. 2020, 1–18. [Google Scholar] [CrossRef]
  17. Desjardins, A.E. Fusarium Mycotoxins: Chemistry, Genetics, and Biology; APS Press, American Phytopathological Society: St. Paul, MN, USA, 2006. [Google Scholar]
  18. Guarro, J. Fusariosis, a Complex Infection Caused by a High Diversity of Fungal Species Refractory to Treatment. Eur. J. Clin. Microbiol. Infect. Dis. 2013, 32, 1491–1500. [Google Scholar] [CrossRef]
  19. Jørgensen, L.N.; van den Bosch, F.; Oliver, R.P.; Heick, T.M.; Paveley, N.D. Targeting Fungicide Inputs According to Need. Annu. Rev. Phytopathol. 2017, 55, 181–203. [Google Scholar] [CrossRef]
  20. Spadaro, D.; Gullino, M.L. State of the Art and Future Prospects of the Biological Control of Postharvest Fruit Diseases. Int. J. Food Microbiol. 2004, 91, 185–194. [Google Scholar] [CrossRef]
  21. Russell, P.E. The Development of Commercial Disease Control. Plant Pathol. 2006, 55, 585–594. [Google Scholar] [CrossRef]
  22. The FRAC Pathogen Risk List®. 2019. Available online: https://www.frac.info/home/news/2019/09/09/the-frac-pathogen-risk-list-was-reviewed-and-updated-in-2019 (accessed on 15 March 2020).
  23. FRAC. Available online: https://www.frac.info/ (accessed on 15 March 2020).
  24. Cools, H.J.; Hawkins, N.J.; Fraaije, B.A. Constraints on the Evolution of Azole Resistance in Plant Pathogenic Fungi. Plant Pathol. 2013, 62, 36–42. [Google Scholar] [CrossRef] [Green Version]
  25. Robbins, N.; Caplan, T.; Cowen, L.E. Molecular Evolution of Antifungal Drug Resistance. Annu. Rev. Microbiol. 2017, 71, 753–775. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Lucas, J.A.; Hawkins, N.J.; Fraaije, B.A. The Evolution of Fungicide Resistance. In Advances in Applied Microbiology; Sariaslani, S., Gadd, G.M., Eds.; Elsevier: Amsterdam, The Netherlands, 2015; Volume 90, pp. 29–92. [Google Scholar]
  27. MacLean, R.C.; Hall, A.R.; Perron, G.G.; Buckling, A. The Population Genetics of Antibiotic Resistance: Integrating Molecular Mechanisms and Treatment Contexts. Nat. Rev. Genet. 2010, 11, 405–414. [Google Scholar] [CrossRef] [PubMed]
  28. Fisher, M.C.; Hawkins, N.J.; Sanglard, D.; Gurr, S.J. Worldwide Emergence of Resistance to Antifungal Drugs Challenges Human Health and Food Security. Science 2018, 360, 739–742. [Google Scholar] [CrossRef] [Green Version]
  29. Hermisson, J.; Pennings, P.S. Soft Sweeps: Molecular Population Genetics of Adaptation from Standing Genetic Variation. Genetics 2005, 169, 2335–2352. [Google Scholar] [CrossRef] [Green Version]
  30. Hawkins, N.J.; Cools, H.J.; Sierotzki, H.; Shaw, M.W.; Knogge, W.; Kelly, S.L.; Kelly, D.E.; Fraaije, B.A. Paralog Re-Emergence: A Novel, Historically Contingent Mechanism in the Evolution of Antimicrobial Resistance. Mol. Biol. Evol. 2014, 31, 1793–1802. [Google Scholar] [CrossRef] [Green Version]
  31. Hawkins, N.J.; Fraaije, B.A. Fitness Penalties in the Evolution of Fungicide Resistance. Annu. Rev. Phytopathol. 2018, 56, 339–360. [Google Scholar] [CrossRef] [Green Version]
  32. Yin, Y.; Liu, X.; Li, B.; Ma, Z. Characterization of Sterol Demethylation Inhibitor-Resistant Isolates of Fusarium asiaticum and F. graminearum Collected from Wheat in China. Phytopathology 2009, 99, 487–497. [Google Scholar] [CrossRef] [Green Version]
  33. Liu, X.; Yu, F.; Schnabel, G.; Wu, J.; Wang, Z.; Ma, Z. Paralogous Cyp51 Genes in Fusarium graminearum Mediate Differential Sensitivity to Sterol Demethylation Inhibitors. Fungal Genet. Biol. 2011, 48, 113–123. [Google Scholar] [CrossRef]
  34. Fan, J.; Urban, M.; Parker, J.E.; Brewer, H.C.; Kelly, S.L.; Hammond-Kosack, K.E.; Fraaije, B.A.; Liu, X.; Cools, H.J. Characterization of the Sterol 14α-Demethylases of Fusarium graminearum Identifies a Novel Genus-Specific CYP51 Function. New Phytol. 2013, 198, 821–835. [Google Scholar] [CrossRef] [Green Version]
  35. Villafana, R.T.; Rampersad, S.N. Three-Locus Sequence Identification and Differential Tebuconazole Sensitivity Suggest Novel Fusarium equiseti Haplotype from Trinidad. Pathogens 2020, 9, 175. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  36. Parsons, A.B.; Brost, R.L.; Ding, H.; Li, Z.; Zhang, C.; Sheikh, B.; Brown, G.W.; Kane, P.M.; Hughes, T.R.; Boone, C. Integration of Chemical-Genetic and Genetic Interaction Data Links Bioactive Compounds to Cellular Target Pathways. Nat. Biotechnol. 2004, 22, 62–69. [Google Scholar] [CrossRef] [PubMed]
  37. Wuster, A.; Madan Babu, M. Chemogenomics and Biotechnology. Trend. Biotechnol. 2008, 26, 252–258. [Google Scholar] [CrossRef] [PubMed]
  38. Li, H.; Diao, Y.; Wang, J.; Chen, C.; Ni, J.; Zhou, M. JS399-19, a New Fungicide against Wheat Scab. J. Crop Prot. 2008, 27, 90–95. [Google Scholar] [CrossRef]
  39. Chen, Y.; Zhou, M.-G. Characterization of Fusarium graminearum Isolates Resistant to Both Carbendazim and a New Fungicide JS399-19. Phytopathology 2009, 99, 441–446. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  40. Chen, Y.; Chen, C.J.; Zhou, M.G.; Wang, J.X.; Zhang, W.Z. Monogenic Resistance to a New Fungicide, JS399-19, in Gibberella zeae. Plant Pathol. 2009, 58, 565–570. [Google Scholar] [CrossRef]
  41. Wollenberg, R.D.; Taft, M.H.; Giese, S.; Thiel, C.; Balázs, Z.; Giese, H.; Manstein, D.J.; Sondergaard, T.E. Phenamacril Is a Reversible and Noncompetitive Inhibitor of Fusarium Class I Myosin. J. Biol. Chem. 2019, 294, 1328–1337. [Google Scholar] [CrossRef] [Green Version]
  42. Zheng, Z.; Hou, Y.; Cai, Y.; Zhang, Y.; Li, Y.; Zhou, M. Whole-Genome Sequencing Reveals That Mutations in Myosin-5 Confer Resistance to the Fungicide Phenamacril in Fusarium graminearum. Sci. Rep. 2015, 5, 8248. [Google Scholar] [CrossRef]
  43. Zhou, Y.; Zhou, X.E.; Gong, Y.; Zhu, Y.; Cao, X.; Brunzelle, J.S.; Xu, H.E.; Zhou, M.; Melcher, K.; Zhang, F. Structural Basis of Fusarium Myosin I Inhibition by Phenamacril. PLoS Pathog. 2020, 16, e1008323. [Google Scholar] [CrossRef]
  44. Aylward, J.; Steenkamp, E.T.; Dreyer, L.L.; Roets, F.; Wingfield, B.D.; Wingfield, M.J. A Plant Pathology Perspective of Fungal Genome Sequencing. IMA Fungus 2017, 8, 1–15. [Google Scholar] [CrossRef] [Green Version]
  45. Carris, L.M.; Little, C.R.; Stiles, C.M. Introduction to Fungi. The Plant Health Instructor. 2012. Available online: https://pdfs.semanticscholar.org/a84c/3b059d7964f4f169120e095375b8da041755.pdf?_ga=2.141742960.333574752.1588303658-1550432755.1582723921 (accessed on 1 April 2020).
  46. Food and Agriculture Organization of the United Nations. World Food and Agriculture: Statistical Pocketbook; FAO: Rome, Italy, 2018. [Google Scholar]
  47. McTaggart, A.R.; van der Nest, M.A.; Steenkamp, E.T.; Roux, J.; Slippers, B.; Shuey, L.S.; Wingfield, M.J.; Drenth, A. Fungal Genomics Challenges the Dogma of Name-Based Biosecurity. PLoS Pathog. 2016, 12, e1005475. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  48. Plissonneau, C.; Benevenuto, J.; Mohd-Assaad, N.; Fouché, S.; Hartmann, F.E.; Croll, D. Using Population and Comparative Genomics to Understand the Genetic Basis of Effector-Driven Fungal Pathogen Evolution. Front. Plant Sci. 2017, 8. [Google Scholar] [CrossRef] [Green Version]
  49. Cuomo, C.A.; Guldener, U.; Xu, J.-R.; Trail, F.; Turgeon, B.G.; Di Pietro, A.; Walton, J.D.; Ma, L.-J.; Baker, S.E.; Rep, M.; et al. The Fusarium graminearum Genome Reveals a Link between Localized Polymorphism and Pathogen Specialization. Science 2007, 317, 1400–1402. [Google Scholar] [CrossRef] [Green Version]
  50. Ma, L.-J.; van der Does, H.C.; Borkovich, K.A.; Coleman, J.J.; Daboussi, M.-J.; Di Pietro, A.; Dufresne, M.; Freitag, M.; Grabherr, M.; Henrissat, B.; et al. Comparative Genomics Reveals Mobile Pathogenicity Chromosomes in Fusarium. Nature 2010, 464, 367–373. [Google Scholar] [CrossRef]
  51. Gardiner, D.M.; Kazan, K.; Praud, S.; Torney, F.J.; Rusu, A.; Manners, J.M. Early Activation of Wheat Polyamine Biosynthesis during Fusarium Head Blight Implicates Putrescine as an Inducer of Trichothecene Mycotoxin Production. BMC Plant Biol. 2010, 10, 289. [Google Scholar] [CrossRef] [Green Version]
  52. Sperschneider, J.; Gardiner, D.M.; Thatcher, L.F.; Lyons, R.; Singh, K.B.; Manners, J.M.; Taylor, J.M. Genome-Wide Analysis in Three Fusarium Pathogens Identifies Rapidly Evolving Chromosomes and Genes Associated with Pathogenicity. Genome Biol. Evol. 2015, 7, 1613–1627. [Google Scholar] [CrossRef]
  53. Taylor, A.; Vágány, V.; Jackson, A.C.; Harrison, R.J.; Rainoni, A.; Clarkson, J.P. Identification of Pathogenicity-Related Genes in Fusarium oxysporum f. sp. cepae: Pathogenicity in Fusarium oxysporum f. sp. cepae. Mol. Plant. Pathol. 2016, 17, 1032–1047. [Google Scholar] [CrossRef] [Green Version]
  54. van Dam, P.; de Sain, M.; ter Horst, A.; van der Gragt, M.; Rep, M. Use of Comparative Genomics-Based Markers for Discrimination of Host Specificity in Fusarium oxysporum. Appl. Environ. Microbiol. 2017, 84, e01868-17. [Google Scholar] [CrossRef] [Green Version]
  55. van Dam, P.; Fokkens, L.; Ayukawa, Y.; van der Gragt, M.; ter Horst, A.; Brankovics, B.; Houterman, P.M.; Arie, T.; Rep, M. A Mobile Pathogenicity Chromosome in Fusarium oxysporum for Infection of Multiple Cucurbit Species. Sci. Rep. 2017, 7, 9042. [Google Scholar] [CrossRef]
  56. van De Wouw, A.P.; Howlett, B.J. Fungal Pathogenicity Genes in the Age of ‘Omics’. Mol. Plant Pathol. 2011, 12, 507–514. [Google Scholar] [CrossRef] [PubMed]
  57. Urban, M.; Pant, R.; Raghunath, A.; Irvine, A.G.; Pedro, H.; Hammond-Kosack, K.E. The Pathogen-Host Interactions Database (PHI-Base): Additions and Future Developments. Nuc. Acids Res. 2015, 43, D645–D655. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  58. Urban, M.; Irvine, A.G.; Cuzick, A.; Hammond-Kosack, K.E. Using the Pathogen-Host Interactions Database (PHI-Base) to Investigate Plant Pathogen Genomes and Genes Implicated in Virulence. Front. Plant Sci. 2015, 6. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  59. Lu, T.; Yao, B.; Zhang, C. DFVF: Database of Fungal Virulence Factors. Database 2012, bas032. [Google Scholar] [CrossRef] [PubMed]
  60. Kersey, P.J.; Lawson, D.; Birney, E.; Derwent, P.S.; Haimel, M.; Herrero, J.; Keenan, S.; Kerhornou, A.; Koscielny, G.; Kähäri, A.; et al. Ensembl Genomes: Extending Ensembl Across the Taxonomic Space. Nucl. Acid Res 2010, 38, D563–D569. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  61. Stajich, J.E.; Harris, T.; Brunk, B.P.; Brestelli, J.; Fischer, S.; Harb, O.S.; Kissinger, J.C.; Li, W.; Nayak, V.; Pinney, D.F.; et al. FungiDB: An Integrated Functional Genomics Database for Fungi. Nucl. Acids Res. 2012, 40, D675–D681. [Google Scholar] [CrossRef]
  62. Basenko, E.; Pulman, J.; Shanmugasundram, A.; Harb, O.; Crouch, K.; Starns, D.; Warrenfeltz, S.; Aurrecoechea, C.; Stoeckert, C.; Kissinger, J.; et al. FungiDB: An Integrated Bioinformatic Resource for Fungi and Oomycetes. JoF 2018, 4, 39. [Google Scholar] [CrossRef] [Green Version]
  63. Grigoriev, I.V.; Nikitin, R.; Haridas, S.; Kuo, A.; Ohm, R.; Otillar, R.; Riley, R.; Salamov, A.; Zhao, X.; Korzeniewski, F.; et al. MycoCosm Portal: Gearing up for 1000 Fungal Genomes. Nuc. Acids Res. 2014, 42, D699–D704. [Google Scholar] [CrossRef]
  64. Grigoriev, I.V.; Cullen, D.; Goodwin, S.B.; Hibbett, D.; Jeffries, T.W.; Kubicek, C.P.; Kuske, C.; Magnuson, J.K.; Martin, F.; Spatafora, J.W.; et al. Fueling the Future with Fungal Genomics. Mycology 2011, 2, 192–209. [Google Scholar] [CrossRef]
  65. Mukherjee, S.; Stamatis, D.; Bertsch, J.; Ovchinnikova, G.; Verezemska, O.; Isbandi, M.; Thomas, A.D.; Ali, R.; Sharma, K.; Kyrpides, N.C.; et al. Genomes OnLine Database (GOLD) v.6: Data Updates and Feature Enhancements. Nucl. Acids Res. 2017, 45, D446–D456. [Google Scholar] [CrossRef]
  66. Choi, J.; Cheong, K.; Jung, K.; Jeon, J.; Lee, G.-W.; Kang, S.; Kim, S.; Lee, Y.-W.; Lee, Y.-H. CFGP 2.0: A Versatile Web-Based Platform for Supporting Comparative and Evolutionary Genomics of Fungi and Oomycetes. Nuc. Acids Res. 2013, 41, D714–D719. [Google Scholar] [CrossRef] [PubMed]
  67. Nurnberger, T.; Brunner, F.; Kemmerling, B.; Piater, L. Innate Immunity in Plants and Animals: Striking Similarities and Obvious Differences. Immunol. Rev. 2004, 198, 249–266. [Google Scholar] [CrossRef] [PubMed]
  68. Zhang, L.; Kars, I.; Essenstam, B.; Liebrand, T.W.H.; Wagemakers, L.; Elberse, J.; Tagkalaki, P.; Tjoitang, D.; van den Ackerveken, G.; van Kan, J.A.L. Fungal Endopolygalacturonases Are Recognized as Microbe-Associated Molecular Patterns by the Arabidopsis Receptor-Like Protein Responsiveness to Botrytis polygalacturonase 1. Plant Physiol. 2014, 164, 352–364. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  69. Yu, X.; Feng, B.; He, P.; Shan, L. From Chaos to Harmony: Responses and Signaling upon Microbial Pattern Recognition. Annu. Rev. Phytopathol. 2017, 55, 109–137. [Google Scholar] [CrossRef]
  70. Zipfel, C. Early Molecular Events in PAMP-Triggered Immunity. Curr. Opin. Plant Biol. 2009, 12, 414–420. [Google Scholar] [CrossRef]
  71. Stergiopoulos, I.; de Wit, P.J.G.M. Fungal Effector Proteins. Annu. Rev. Phytopathol. 2009, 47, 233–263. [Google Scholar] [CrossRef] [Green Version]
  72. De Wit, P.J.G.M.; Mehrabi, R.; Van Den Burg, H.A.; Stergiopoulos, I. Fungal Effector Proteins: Past, Present and Future. Mol. Plant. Pathol. 2009, 10, 735–747. [Google Scholar] [CrossRef]
  73. de Jonge, R.; Bolton, M.D.; Kombrink, A.; van den Berg, G.C.M.; Yadeta, K.A.; Thomma, B.P.H.J. Extensive Chromosomal Reshuffling Drives Evolution of Virulence in an Asexual Pathogen. Genome Res. 2013, 23, 1271–1282. [Google Scholar] [CrossRef] [Green Version]
  74. Thomma, B.P.H.J.; Nürnberger, T.; Joosten, M.H.A.J. Of PAMPs and Effectors: The Blurred PTI-ETI Dichotomy. Plant Cell 2011, 23, 4–15. [Google Scholar] [CrossRef] [Green Version]
  75. Rafiqi, M.; Ellis, J.G.; Ludowici, V.A.; Hardham, A.R.; Dodds, P.N. Challenges and Progress towards Understanding the Role of Effectors in Plant–Fungal Interactions. Curr. Opin. Plant Biol. 2012, 15, 477–482. [Google Scholar] [CrossRef]
  76. Fouché, S.; Plissonneau, C.; Croll, D. The Birth and Death of Effectors in Rapidly Evolving Filamentous Pathogen Genomes. Curr. Opin. Microbiol. 2018, 46, 34–42. [Google Scholar] [CrossRef] [PubMed]
  77. Weiberg, A.; Wang, M.; Lin, F.-M.; Zhao, H.; Zhang, Z.; Kaloshian, I.; Huang, H.-D.; Jin, H. Fungal Small RNAs Suppress Plant Immunity by Hijacking Host RNA Interference Pathways. Science 2013, 342, 118–123. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  78. Fang, X.; Qi, Y. RNAi in Plants: An Argonaute-Centered View. Plant Cell 2016, 28, 272–285. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  79. Zhu, C.; Liu, T.; Chang, Y.-N.; Duan, C.-G. Small RNA Functions as a Trafficking Effector in Plant Immunity. IJMS 2019, 20, 2816. [Google Scholar] [CrossRef] [Green Version]
  80. Koch, A.; Kogel, K.-H. New Wind in the Sails: Improving the Agronomic Value of Crop Plants through RNAi-Mediated Gene Silencing. Plant Biotechnol. J. 2014, 12, 821–831. [Google Scholar] [CrossRef]
  81. Castel, S.E.; Martienssen, R.A. RNA Interference in the Nucleus: Roles for Small RNAs in Transcription, Epigenetics and Beyond. Nat. Rev. Genet. 2013, 14, 100–112. [Google Scholar] [CrossRef]
  82. Liu, X.; Tang, W.-H.; Zhao, X.-M.; Chen, L. A Network Approach to Predict Pathogenic Genes for Fusarium graminearum. PLoS ONE 2010, 5, e13021. [Google Scholar] [CrossRef]
  83. Kawamata, T.; Tomari, Y. Making RISC. Trend. Biochem. Sci. 2010, 35, 368–376. [Google Scholar] [CrossRef]
  84. Meister, G. Argonaute Proteins: Functional Insights and Emerging Roles. Nat. Rev. Genet. 2013, 14, 447–459. [Google Scholar] [CrossRef]
  85. Chang, S.-S.; Zhang, Z.; Liu, Y. RNA Interference Pathways in Fungi: Mechanisms and Functions. Annu. Rev. Microbiol. 2012, 66, 305–323. [Google Scholar] [CrossRef] [Green Version]
  86. Chen, Y.; Gao, Q.; Huang, M.; Liu, Y.; Liu, Z.; Liu, X.; Ma, Z. Characterization of RNA Silencing Components in the Plant Pathogenic Fungus Fusarium graminearum. Sci. Rep. 2015, 5, 12500. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  87. Hua, C.; Zhao, J.-H.; Guo, H.-S. Trans-Kingdom RNA Silencing in Plant–Fungal Pathogen Interactions. Mol. Plant Pathol. 2018, 11, 235–244. [Google Scholar] [CrossRef] [Green Version]
  88. Baldwin, T.; Islamovic, E.; Klos, K.; Schwartz, P.; Gillespie, J.; Hunter, S.; Bregitzer, P. Silencing Efficiency of dsRNA Fragments Targeting Fusarium graminearum TRI6 and Patterns of Small Interfering RNA Associated with Reduced Virulence and Mycotoxin Production. PLoS ONE 2018, 13. [Google Scholar] [CrossRef] [PubMed]
  89. Wang, M.; Jin, H. Spray-Induced Gene Silencing: A Powerful Innovative Strategy for Crop Protection. Trend. Microbiol. 2017, 25, 4–6. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  90. Wang, M.; Weiberg, A.; Lin, F.-M.; Thomma, B.P.H.J.; Huang, H.-D.; Jin, H. Bidirectional Cross-Kingdom RNAi and Fungal Uptake of External RNAs Confer Plant Protection. Nat. Plants 2016, 2, 16151. [Google Scholar] [CrossRef] [PubMed]
  91. Chen, W.; Kastner, C.; Nowara, D.; Oliveira-Garcia, E.; Rutten, T.; Zhao, Y.; Deising, H.B.; Kumlehn, J.; Schweizer, P. Host-Induced Silencing of Fusarium culmorum Genes Protects Wheat from Infection. J. Exp. Bot. 2016, 67, 4979–4991. [Google Scholar] [CrossRef] [Green Version]
  92. Koch, A.; Kumar, N.; Weber, L.; Keller, H.; Imani, J.; Kogel, K.-H. Host-Induced Gene Silencing of Cytochrome P450 Lanosterol C14 -Demethylase-Encoding Genes Confers Strong Resistance to Fusarium Species. Proc. Natl. Acad. Sci. USA 2013, 110, 19324–19329. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  93. Koch, A.; Biedenkopf, D.; Furch, A.; Weber, L.; Rossbach, O.; Abdellatef, E.; Linicus, L.; Johannsmeier, J.; Jelonek, L.; Goesmann, A.; et al. An RNAi-Based Control of Fusarium graminearum Infections Through Spraying of Long dsRNAs Involves a Plant Passage and Is Controlled by the Fungal Silencing Machinery. PLoS Pathog. 2016, 12, e1005901. [Google Scholar] [CrossRef]
  94. Cheng, W.; Song, X.-S.; Li, H.-P.; Cao, L.-H.; Sun, K.; Qiu, X.-L.; Xu, Y.-B.; Yang, P.; Huang, T.; Zhang, J.-B.; et al. Host-Induced Gene Silencing of an Essential Chitin Synthase Gene Confers Durable Resistance to Fusarium Head Blight and Seedling Blight in Wheat. Plant Biotechnol. J. 2015, 13, 1335–1345. [Google Scholar] [CrossRef]
  95. Werner, B.; Gaffar, F.Y.; Biedenkopf, D.; Koch, A. RNA-Spray-Mediated Silencing of Fusarium graminearum AGO and DCL Genes Improve Barley Disease Resistance. bioRxiv 2019, 821868. [Google Scholar] [CrossRef]
  96. Jiao, J.; Peng, D. Wheat MicroRNA1023 Suppresses Invasion of Fusarium graminearum via Targeting and Silencing FGSG_03101. J. Plant Interact 2018, 13, 514–521. [Google Scholar] [CrossRef] [Green Version]
  97. He, F.; Zhang, R.; Zhao, J.; Qi, T.; Kang, Z.; Guo, J. Host-Induced Silencing of Fusarium graminearum Genes Enhances the Resistance of Brachypodium distachyon to Fusarium Head Blight. Front. Plant Sci. 2019, 10, 1362. [Google Scholar] [CrossRef] [PubMed]
  98. Höfle, L.; Biedenkopf, D.; Werner, B.T.; Shrestha, A.; Jelonek, L.; Koch, A. Study on the Efficiency of dsRNAs with Increasing Length in RNA-Based Silencing of the Fusarium CYP51 Genes. RNA. Biol. 2020, 17, 463–473. [Google Scholar] [CrossRef] [PubMed]
  99. Gaffar, F.Y.; Imani, J.; Karlovsky, P.; Koch, A.; Kogel, K.-H. Different Components of the RNA Interference Machinery Are Required for Conidiation, Ascosporogenesis, Virulence, Deoxynivalenol Production, and Fungal Inhibition by Exogenous Double-Stranded RNA in the Head Blight Pathogen Fusarium graminearum. Front. Microbiol. 2019, 10. [Google Scholar] [CrossRef] [Green Version]
  100. Ghag, S.B.; Shekhawat, U.K.S.; Ganapathi, T.R. Host-Induced Post-Transcriptional Hairpin RNA-Mediated Gene Silencing of Vital Fungal Genes Confers Efficient Resistance against Fusarium Wilt in Banana. Plant Biotechnol. J. 2014, 12, 541–553. [Google Scholar] [CrossRef]
  101. Fernandes, J.S.; Angelo, P.C.S.; Cruz, J.C.; Santos, J.M.M.; Sousa, N.R.; Silva, G.F. Post-Transcriptional Silencing of the SGE1 Gene Induced by a dsRNA Hairpin in Fusarium oxysporum f. sp. cubense, the Causal Agent of Panama Disease. Genet. Mol. Res. 2016, 15. [Google Scholar] [CrossRef]
  102. Hu, Z.; Parekh, U.; Maruta, N.; Trusov, Y.; Botella, J.R. Down-Regulation of Fusarium oxysporum Endogenous Genes by Host-Delivered RNA Interference Enhances Disease Resistance. Front. Chem. 2015, 3. [Google Scholar] [CrossRef] [Green Version]
  103. Dou, T.; Shao, X.; Hu, C.; Liu, S.; Sheng, O.; Bi, F.; Deng, G.; Ding, L.; Li, C.; Dong, T.; et al. Host-Induced Gene Silencing of Foc TR4 ERG6/11 Genes Exhibits Superior Resistance to Fusarium Wilt of Banana. Plant Biotechnol. J. 2020, 18, 11–13. [Google Scholar] [CrossRef] [Green Version]
  104. Bharti, P.; Jyoti, P.; Kapoor, P.; Sharma, V.; Shanmugam, V.; Yadav, S.K. Host-Induced Silencing of Pathogenicity Genes Enhances Resistance to Fusarium oxysporum Wilt in Tomato. Mol. Biotechnol. 2017, 59, 343–352. [Google Scholar] [CrossRef]
  105. Singh, N.; Mukherjee, S.K.; Rajam, M.V. Silencing of the Ornithine Decarboxylase Gene of Fusarium oxysporum f. sp. lycopersici by Host-Induced RNAi Confers Resistance to Fusarium Wilt in Tomato. Plant Mol. Biol. Rep. 2020. [Google Scholar] [CrossRef]
  106. Tinoco, M.; Dias, B.B.; Dall’Astta, R.C.; Pamphile, J.A.; Aragão, F.J. In Vivo Trans-Specific Gene Silencing in Fungal Cells by in Planta Expression of a Double-Stranded RNA. BMC Biol. 2010, 8, 27. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  107. Agrios, G.N. Plant Pathology, 5th ed.; Elsevier Academic Press: Burlington, MA, USA, 2005. [Google Scholar]
  108. Rauwane, M.E.; Ogugua, U.V.; Kalu, C.M.; Ledwaba, L.K.; Woldesemayat, A.A.; Ntushelo, K. Pathogenicity and Virulence Factors of Fusarium graminearum Including Factors Discovered Using Next Generation Sequencing Technologies and Proteomics. Microorganisms 2020, 8, 305. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  109. Coleman, J.J.; Rounsley, S.D.; Rodriguez-Carres, M.; Kuo, A.; Wasmann, C.C.; Grimwood, J.; Schmutz, J.; Taga, M.; White, G.J.; Zhou, S.; et al. The Genome of Nectria haematococca: Contribution of Supernumerary Chromosomes to Gene Expansion. PLoS Genet. 2009, 5, e1000618. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  110. Kazan, K.; Gardiner, D.M.; Manners, J.M. On the Trail of a Cereal Killer: Recent Advances in Fusarium graminearum Pathogenomics and Host Resistance. Mol. Plant. Pathol. 2012, 13, 399–413. [Google Scholar] [CrossRef] [PubMed]
  111. Giraldo, M.C.; Valent, B. Filamentous Plant Pathogen Effectors in Action. Nat. Rev. Microbiol. 2013, 11, 800–814. [Google Scholar] [CrossRef]
  112. Rovenich, H.; Boshoven, J.C.; Thomma, B.P. Filamentous Pathogen Effector Functions: Of Pathogens, Hosts and Microbiomes. Curr. Opin. Plant Biol. 2014, 20, 96–103. [Google Scholar] [CrossRef] [Green Version]
  113. Koeck, M.; Hardham, A.R.; Dodds, P.N. The Role of Effectors of Biotrophic and Hemibiotrophic Fungi in Infection: Effectors of Biotrophic Fungi. Cell. Microbiol. 2011, 13, 1849–1857. [Google Scholar] [CrossRef] [Green Version]
  114. Ma, L.-J.; Geiser, D.M.; Proctor, R.H.; Rooney, A.P.; O’Donnell, K.; Trail, F.; Gardiner, D.M.; Manners, J.M.; Kazan, K. Fusarium Pathogenomics. Annu. Rev. Microbiol. 2013, 67, 399–416. [Google Scholar] [CrossRef] [Green Version]
  115. Lo Presti, L.; Lanver, D.; Schweizer, G.; Tanaka, S.; Liang, L.; Tollot, M.; Zuccaro, A.; Reissmann, S.; Kahmann, R. Fungal Effectors and Plant Susceptibility. Annu. Rev. Plant Biol. 2015, 66, 513–545. [Google Scholar] [CrossRef]
  116. Dong, S.; Raffaele, S.; Kamoun, S. The Two-Speed Genomes of Filamentous Pathogens: Waltz with Plants. Curr. Opin. Genet. Devel. 2015, 35, 57–65. [Google Scholar] [CrossRef]
  117. Lysenko, A.; Urban, M.; Bennett, L.; Tsoka, S.; Janowska-Sejda, E.; Rawlings, C.J.; Hammond-Kosack, K.E.; Saqi, M. Network-Based Data Integration for Selecting Candidate Virulence Associated Proteins in the Cereal Infecting Fungus Fusarium graminearum. PLoS ONE 2013, 8, e67926. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  118. Idnurm, A.; Howlett, B.J. Pathogenicity Genes of Phytopathogenic Fungi. Mol. Plant. Pathol. 2001, 2, 241–255. [Google Scholar] [CrossRef] [PubMed]
  119. Möbius, N.; Hertweck, C. Fungal Phytotoxins as Mediators of Virulence. Curr. Opin. Plant Biol. 2009, 12, 390–398. [Google Scholar] [CrossRef] [PubMed]
  120. de Wit, P.J.G.M. How Plants Recognize Pathogens and Defend Themselves. Cell. Mol. Life Sci. 2007, 64, 2726–2732. [Google Scholar] [CrossRef] [PubMed]
  121. Michielse, C.B.; van Wijk, R.; Reijnen, L.; Cornelissen, B.J.; Rep, M. Insight into the Molecular Requirements for Pathogenicity of Fusarium oxysporum f. sp. lycopersici through Large-Scale Insertional Mutagenesis. Genome Biol. 2009, 10, R4. [Google Scholar] [CrossRef] [Green Version]
  122. Di Pietro, A.; García-Maceira, F.I.; Méglecz, E.; Roncero, M.I.G. A MAP Kinase of the Vascular Wilt Fungus Fusarium oxysporum Is Essential for Root Penetration and Pathogenesis: Fusarium MAPK Is Essential for Pathogenesis. Mol. Microbiol. 2004, 39, 1140–1152. [Google Scholar] [CrossRef]
  123. Jain, S.; Akiyama, K.; Mae, K.; Ohguchi, T.; Takata, R. Targeted Disruption of a G Protein α Subunit Gene Results in Reduced Pathogenicity in Fusarium oxysporum. Curr. Genet. 2002, 41, 407–413. [Google Scholar] [CrossRef]
  124. Jain, S.; Akiyama, K.; Kan, T.; Ohguchi, T.; Takata, R. The G Protein β Subunit FGB1 Regulates Development and Pathogenicity in Fusarium oxysporum. Curr. Genet. 2003, 43, 79–86. [Google Scholar] [CrossRef]
  125. Jain, S.; Akiyama, K.; Takata, R.; Ohguchi, T. Signaling via the G Protein α Subunit FGA2 Is Necessary for Pathogenesis in Fusarium oxysporum. FEMS Microbiol. Lett. 2005, 243, 165–172. [Google Scholar] [CrossRef] [Green Version]
  126. Rana, A.; Sahgal, M.; Johri, B.N. Fusarium oxysporum: Genomics, Diversity and Plant–Host Interaction. In Developments in Fungal Biology and Applied Mycology; Satyanarayana, T., Deshmukh, S.K., Johri, B.N., Eds.; Springer: Singapore, 2017; pp. 159–199. [Google Scholar] [CrossRef]
  127. Shang, Y.; Xiao, G.; Zheng, P.; Cen, K.; Zhan, S.; Wang, C. Divergent and Convergent Evolution of Fungal Pathogenicity. Genome Biol. Evol. 2016, 8, 1374–1387. [Google Scholar] [CrossRef] [Green Version]
  128. Ilgen, P.; Maier, F.; Schäfer, W. Trichothecenes and Lipases Are Host-Induced and Secreted Virulence Factors of Fusarium graminearum. Cereal Res. Comm. 2008, 36, 421–428. [Google Scholar] [CrossRef]
  129. Voigt, C.A.; Schäfer, W.; Salomon, S. A Secreted Lipase of Fusarium graminearum is a Virulence Factor Required for Infection of Cereals: Lipase as a Virulence Factor. Plant J. 2005, 42, 364–375. [Google Scholar] [CrossRef] [PubMed]
  130. Salomon, S.; Gácser, A.; Frerichmann, S.; Kröger, C.; Schäfer, W.; Voigt, C.A. The Secreted Lipase FGL1 Is Sufficient to Restore the Initial Infection Step to the Apathogenic Fusarium graminearum MAP Kinase Disruption Mutant Δgpmk1. Eur. J. Plant Pathol. 2012, 134, 23–37. [Google Scholar] [CrossRef]
  131. van der Does, H.C.; Fokkens, L.; Yang, A.; Schmidt, S.M.; Langereis, L.; Lukasiewicz, J.M.; Hughes, T.R.; Rep, M. Transcription Factors Encoded on Core and Accessory Chromosomes of Fusarium oxysporum Induce Expression of Effector Genes. PLoS Genet. 2016, 12, e1006401. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  132. Niño-Sánchez, J.; Casado-Del Castillo, V.; Tello, V.; De Vega-Bartol, J.J.; Ramos, B.; Sukno, S.A.; Díaz Mínguez, J.M. The FTF Gene Family Regulates Virulence and Expression of SIX Effectors in Fusarium oxysporum. Mol. Plant. Pathol. 2016, 17, 1124–1139. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  133. Vlaardingerbroek, I.; Beerens, B.; Rose, L.; Fokkens, L.; Cornelissen, B.J.C.; Rep, M. Exchange of Core Chromosomes and Horizontal Transfer of Lineage-Specific Chromosomes in Fusarium oxysporum: Chromosome Transfer and Exchange in F. oxysporum. Environ. Microbiol. 2016, 18, 3702–3713. [Google Scholar] [CrossRef]
  134. Covert, S.F. Supernumerary Chromosomes in Filamentous Fungi. Curr. Genet. 1998, 33, 311–319. [Google Scholar] [CrossRef]
  135. Temporini, E.; van Etten, D.; Hans, D. An Analysis of the Phylogenetic Distribution of the Pea Pathogenicity Genes of Nectria haematococca MPVI Supports the Hypothesis of Their Origin by Horizontal Transfer and Uncovers a Potentially New Pathogen of Garden Pea: Neocosmospora boniensis. Curr. Genet. 2004, 46. [Google Scholar] [CrossRef]
  136. Croll, D.; McDonald, B.A. The Accessory Genome as a Cradle for Adaptive Evolution in Pathogens. PLoS Pathog. 2012, 8, e1002608. [Google Scholar] [CrossRef] [Green Version]
  137. Proctor, R.H.; Hohn, T.M.; McCormick, S.P. Reduced Virulence of Gibberella zeae Caused by Disruption of a Trichothecene Toxin Biosynthetic Gene. Mol. Plant Microbe Interact. 1995, 8, 593–601. [Google Scholar] [CrossRef] [Green Version]
  138. Bai, G.-H.; Desjardins, A.E.; Plattner, R.D. Deoxynivalenol-Nonproducing Fusarium graminearum Causes Initial Infection, but Does Not Cause Disease Spread in Wheat Spikes. Mycopathologia 2002, 153, 91–98. [Google Scholar] [CrossRef] [PubMed]
  139. Goswami, R.S.; Kistler, H.C. Pathogenicity and In Planta Mycotoxin Accumulation among Members of the Fusarium graminearum Species Complex on Wheat and Rice. Phytopathology 2005, 95, 1397–1404. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  140. Desmond, O.J.; Manners, J.M.; Stephens, A.E.; Maclean, D.J.; Schenk, P.M.; Gardiner, D.M.; Munn, A.L.; Kazan, K. The Fusarium Mycotoxin Deoxynivalenol Elicits Hydrogen Peroxide Production, Programmed Cell Death and Defence Responses in Wheat. Mol. Plant. Pathol. 2008, 9, 435–445. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  141. Villani, A.; Proctor, R.H.; Kim, H.-S.; Brown, D.W.; Logrieco, A.F.; Amatulli, M.T.; Moretti, A.; Susca, A. Variation in Secondary Metabolite Production Potential in the Fusarium Incarnatum-Equiseti Species Complex Revealed by Comparative Analysis of 13 Genomes. BMC Genomics 2019, 20, 314. [Google Scholar] [CrossRef]
  142. Hoogendoorn, K.; Barra, L.; Waalwijk, C.; Dickschat, J.S.; van der Lee, T.A.J.; Medema, M.H. Evolution and Diversity of Biosynthetic Gene Clusters in Fusarium. Front. Microbiol. 2018, 9, 1158. [Google Scholar] [CrossRef] [Green Version]
  143. Amarasinghe, C.C.; Fernando, W.G.D. Comparative Analysis of Deoxynivalenol Biosynthesis Related Gene Expression among Different Chemotypes of Fusarium graminearum in Spring Wheat. Front. Microbiol. 2016, 7. [Google Scholar] [CrossRef]
  144. Lee, H.J.; Ryu, D. Worldwide Occurrence of Mycotoxins in Cereals and Cereal-Derived Food Products: Public Health Perspectives of Their Co-Occurrence. J. Agric. Food Chem. 2017, 65, 7034–7051. [Google Scholar] [CrossRef]
  145. Jansen, C.; von Wettstein, D.; Schafer, W.; Kogel, K.-H.; Felk, A.; Maier, F.J. Infection Patterns in Barley and Wheat Spikes Inoculated with Wild-Type and Trichodiene Synthase Gene Disrupted Fusarium graminearum. Proc. Nat. Acad. Sci. USA 2005, 102, 16892–16897. [Google Scholar] [CrossRef] [Green Version]
  146. Lepesheva, G.I.; Waterman, M.R. Sterol 14α-demethylase cytochrome P450 CYP51, a P450 in all biological kingdoms. BBA Gen. Subj. 2007, 177, 467–477. [Google Scholar] [CrossRef] [Green Version]
  147. Liu, W.; Sun, Y.; Chen, W.; Liu, W.; Wan, Z.; Bu, D.; Li, R. The T788G Mutation in the Cyp51C Gene Confers Voriconazole Resistance in Aspergillus flavus Causing Aspergillosis. Antimicrob. Agents Chemother. 2012, 56, 2598–2603. [Google Scholar] [CrossRef] [Green Version]
  148. Sharma, C.; Kumar, R.; Kumar, N.; Masih, A.; Gupta, D.; Chowdhary, A. Investigation of Multiple Resistance Mechanisms in Voriconazole-Resistant Aspergillus flavus Clinical Isolates from a Chest Hospital Surveillance in Delhi, India. Antimicrob. Agents Chemother. 2018, 62. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  149. Machado, A.K.; Brown, N.A.; Urban, M.; Kanyuka, K.; Hammond-Kosack, K.E. RNAi as an Emerging Approach to Control Fusarium Head Blight Disease and Mycotoxin Contamination in Cereals. Pest. Manag. Sci. 2018, 74, 790–799. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  150. Paper, J.M.; Scott-Craig, J.S.; Adhikari, N.D.; Cuomo, C.A.; Walton, J.D. Comparative proteomics of extracellular proteins in vitro and in planta from the pathogenic fungus Fusarium graminearum. Proteomics 2007, 17, 3171–3183. [Google Scholar] [CrossRef] [PubMed]
  151. Panwar, V. RNA Silencing Approaches for Identifying Pathogenicity and Virulence Elements towards Engineering Crop Resistance to Plant Pathogenic Fungi. CAB Rev. 2016, 11. [Google Scholar] [CrossRef] [Green Version]
  152. Cangelosi, B.; Curir, P.; Beruto, M.; Monroy, F.; Borriello, R.; Beruto, M. Protective Effects of Arbuscular Mycorrhizae against Fusarium oxysporum f. sp. ranunculi in Ranunculus asiaticus Cultivations for Flower Crop. J. Hort. Sci. Res. 2017, 1. [Google Scholar]
  153. Haque, S.I.; Matsubara, Y. Arbuscular-Mycorrhiza-Induced Salt Tolerance and Resistance to Fusarium Root Rot in Asparagus Plants. Acta Hortic. 2018, 1227, 365–372. [Google Scholar] [CrossRef]
  154. Meddich, A.; Ait El Mokhtar, M.; Bourzik, W.; Mitsui, T.; Baslam, M.; Hafidi, M. Optimizing Growth and Tolerance of Date Palm (Phoenix Dactylifera L.) to Drought, Salinity, and Vascular Fusarium-Induced Wilt (Fusarium oxysporum) by Application of Arbuscular Mycorrhizal Fungi (AMF). In Root Biology; Giri, B., Prasad, R., Varma, A., Eds.; Soil Biology; Springer International Publishing: Cham, Switzerland, 2018; pp. 239–258. [Google Scholar] [CrossRef]
  155. Olowe, O.M.; Olawuyi, O.J.; Sobowale, A.A.; Odebode, A.C. Role of Arbuscular Mycorrhizal Fungi as Biocontrol Agents against Fusarium verticillioides Causing Ear Rot of Zea mays L. (Maize). Curr. Plant Biol. 2018, 15, 30–37. [Google Scholar] [CrossRef]
  156. Dehariya, K.; Shukla, A.; Sheikh, I.A.; Vyas, D. Trichoderma and Arbuscular Mycorrhizal Fungi Based Biocontrol of Fusarium udum Butler and Their Growth Promotion Effects on Pigeon Pea. J. Agric. Sci. Tech. 2015, 17, 505–517. [Google Scholar]
  157. Peek, A.S.; Behlke, M.A. Design of Active Small Interfering RNAs. Curr. Opin. Mol. Ther. 2007, 9, 110–118. [Google Scholar]
  158. Shabalina, S.; Koonin, E. Origins and Evolution of Eukaryotic RNA Interference. Trend. Ecol. Evol. 2008, 23, 578–587. [Google Scholar] [CrossRef] [Green Version]
  159. Pumplin, N.; Voinnet, O. RNA Silencing Suppression by Plant Pathogens: Defence, Counter-Defence and Counter-Counter-Defence. Nat. Rev. Microbiol. 2013, 11, 745–760. [Google Scholar] [CrossRef] [PubMed]
  160. Nicolás, F.E.; Torres-Martínez, S.; Ruiz-Vázquez, R.M. Loss and Retention of RNA Interference in Fungi and Parasites. PLoS Pathog. 2013, 9, e1003089. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  161. Yin, C.; Hulbert, S. Host Induced Gene Silencing (HIGS), A Promising Strategy for Developing Disease Resistant Crops. Gene Technol. 2015, 4, 130. [Google Scholar] [CrossRef] [Green Version]
Table
Table 1. Currently active filamentous fungi databases, genome browsers, and training.
Table 1. Currently active filamentous fungi databases, genome browsers, and training.
Database and WebsiteUsageReference
PHI-base - Pathogen-Host Interaction database
http://www.phi-base.org/
Pathogens 09 00340 i001		PHI-base is a web-accessible database that catalogues experimentally verified pathogenicity, virulence, and effector genes from fungal, oomycete, and bacterial pathogens. PHI-base is invaluable to the discovery of genes of pathogens, which may be potential targets for chemical and/or other intervention. In collaboration with the FRAC (Fungicide Resistance Action Committee) team, PHI-base also includes antifungal compounds and their target genes. [57,58]
DFVF—Database of virulence factors in fungal pathogens
http://sysbio.unl.edu/DFVF/
Pathogens 09 00340 i002		Experimental biologists and computational biologists can use the database and/or the predicted virulence factors to guide their search for new virulence factors and/or discovery of new pathogen–host interaction mechanisms in fungi. [59]
EnsemblFungi
https://fungi.ensembl.org/index.html
Pathogens 09 00340 i003		Ensembl Fungi is a browser for fungal genomes. A majority of these are taken from the databases of the International Nucleotide Sequence Database Collaboration. Data can be visualised through the Ensembl genome browser. [60]
FungiDB: Fungi Database
https://fungidb.org/fungidb/
Pathogens 09 00340 i004		FungiDB belongs to the EuPathDB family of databases and integrates whole-genome sequence and annotation and also includes experimental and environmental isolate sequence data. The database includes comparative genomics, analysis of gene expression, and supplemental bioinformatics analyses and a web interface for data-mining. [61,62]
JGI—MycoCosm
https://mycocosm.jgi.doe.gov/mycocosm/home
Pathogens 09 00340 i005		MycoCosm enables users to navigate across sequenced fungal genomes and to conduct comparative and genome-centric analyses of fungi and community annotation “The 1000 fungal genomes project”. [63,64]
JGI—GOLD—Genomes Online Database
https://gold.jgi.doe.gov/
Pathogens 09 00340 i006		A manually curated data-management system that catalogues sequencing projects with associated metadata from around the world. GOLD provides a seamless interface with the Integrated Microbial Genomes (IMG) system and supports and promotes the Genomic Standards Consortium (GSC) minimum information standards. [65]
CFGP—Comparative Fungal Genomics Platform
http://cfgp.riceblast.snu.ac.kr/main.php
Pathogens 09 00340 i007		The CFGP 2.0 (Comparative Fungal Genomics Platform): The CFGP interactive informatics workbench has an archive of 283 genomes corresponding to 152 fungal and oomycete species; 27 bioinformatics tools are available for users. [66]
Fungal Pathogen Genomics
https://coursesandconferences.wellcomegenomecampus.org/our-events/fungal-pathogen-genomics
Pathogens 09 00340 i008 Pathogens 09 00340 i009
Pathogens 09 00340 i010		Hands-on training in web-based, data-mining resources for fungal genomes. Comparative genomics, gene trees, whole-genome alignment; identification of orthologs and orthology-based inference; genome browsers and gene pages; RNA-Seq analysis and visualization in VEuPathDB Galaxy; variant calling analysis; development of advanced biologically relevant queries using FungiDB; and introduction to annotation and curation of fungal genomes.Wellcome Genome Campus, Cambridge, UK
Table
Table 2. Host-induced gene silencing (HIGS) and spray-induced gene silencing (SIGS) of target genes in Fusarium species.
Table 2. Host-induced gene silencing (HIGS) and spray-induced gene silencing (SIGS) of target genes in Fusarium species.
SpeciesGene TargetGene FunctionHostYear ReportedReference
F. culmorumFcFgl1aSecreted lipaseWheat2016[91]
FcFmk1aMitogen-activated protein (MAP) kinaseWheat2016[91]
FcGls1aBeta-1,3-glucan synthaseWheat2016[91]
FcChsVaChitin synthaseWheat2016[91]
FcChsVaChitin synthase V, myosin-motor domainWheat2016[91]
F. graminearumCYP51aCytochrome P459 lanosterol C-14-alpha demethylaseArabidopsis thaliana; Barley2013[92]
FgCYP51A; FgCYP51; FgCYP51C1Cytochrome P459 lanosterol C-14-alpha demethylaseBarley2016[93]
Chs3bbChitin synthaseWheat2015[94]
F. graminearumAGO; DCL1ARGONAUTE; DICERBarley2019[95]
F. graminearumFGSG_03101aalpha/beta hydrolaseWheat2018[96]
F. graminearumFg00677; Fg08731Protein kinaseBrachypodium distachyon2019[97]
FgCYP51A; FgCYP51; FgCYP51CCytochrome P450 lanosterol C-14-alpha demethylaseBrachypodium distachyon2019[97]
F. graminearumFgCYP51A; FgCYP51; FgCYP51CCytochrome P459 lanosterol C-14-alpha demethylaseArabidopsis thaliana2019[98]
F. graminearumFgDCL1, FgDCL2Dicer-like proteinsWheat2019[99]
FgAGO1, FgAGO2ARGONAUTE 1 and 2Wheat2019[99]
FgQDE3RecQ helicaseWheat2019[99]
FgQIPAGO-interacting proteinWheat2019[99]
FgRdRP1, FgRdRP2, FgRdRP3, FgRdRP4RNA-dependent RNA polymerasesWheat2019[99]
F. oxysporum f. sp. cubenseVelvetTranscription factorBanana2014[100]
ftf1Fusarium transcription factor 1Banana2014[100]
F. oxysporum f. sp. cubenseSGE1SIX (Secreted In Xylem) Gene Expression 1Banana2016[101]
F. oxysporum f. sp. conglutinanFRP1F-box proteinArabidopsis thaliana2015[102]
F. oxysporum f. sp. conglutinansERG6/11Ergosterol biosynthetic genesBanana2020[103]
F. oxysporumFOW2Zn(II)2Cys6 family putative transcription regulatorTomato2017[104]
ChsVChitin synthase V, myosin-motor domainTomato2017[104]
F. oxysporum f. sp. lycopersiciODCOrnithine decarboxylase; Polyamine (PA) biosynthesisTomato2020[105]
F. verticilloidesGUSaReporter gene—proof of conceptTobacco2010[106]
1 SIGS; all other reports are HIGS; a BSMV (Barley stripe mosaic virus)-mediated gene silencing; b—biolistic/particle bombardment introduction of construct
Table
Table 3. PHI-base curated genes associated with “loss of pathogenicity” mutant phenotype according to Fusarium species.
Table 3. PHI-base curated genes associated with “loss of pathogenicity” mutant phenotype according to Fusarium species.
GeneGene FunctionSpeciesHost Species (Common Name)
FcRav2Regulator—trichothecene type B biosynthesisF. culmorumTriticum aestivum (bread wheat)
FSR1Putative signaling scaffold proteinF. fujikuroiZea mays (maize)
FgGT2GlycosyltransferaseF. graminearumT. aestivum (bread wheat)
MGV1Mitogen-activated protein kinase (MAPK) F. graminearumTriticum (wheat); Solanum lycopersicum (tomato)
MAP1 (GPMK1)Mitogen-activated protein kinase (MAPK) F. graminearumTriticum (wheat); T. aestivum (bread wheat); Glycine max (soybean); A. thaliana; S. lycopersicum (tomato)
STE7Mitogen-activated protein kinase (MAPK) F. graminearumTriticum (wheat); S. lycopersicum (tomato)
STE11Mitogen-activated protein kinase (MAPK)F. graminearumTriticum (wheat); S. lycopersicum (tomato)
Fgrab6; Fgrab7; Fgrab8; Fgrab51; Fgrab52Rab GTPasesF. graminearumT. aestivum (bread wheat)
ACL1Adenosine triphosphate (ATP) citrate lyaseF. graminearumTriticum (wheat)
ACL2Adenosine triphosphate (ATP) citrate lyaseF. graminearumTriticum (wheat)
CPK1cAMP-dependent protein kinase A (PKA)F. graminearumT. aestivum (bread wheat); Z. mays (maize)
CPK2cAMP-dependent protein kinase A (PKA)F. graminearumT. aestivum (bread wheat); Z. mays (maize)
FgSte50Mitogen-activated protein kinase (MAPK) F. graminearumT. aestivum (bread wheat)
Fgk3Glycogen synthase kinaseF. graminearumT. aestivum (bread wheat)
cdc2ACell cycle progressionF. graminearumT. aestivum (bread wheat)
ScOrtholog_YVH1Uncharacterized proteinF. graminearumT. aestivum (bread wheat)
FgVam7Regulator in cellular differentiation and virulenceF. graminearumT. aestivum (bread wheat); S. lycopersicum (tomato)
Fg02025 (FgArb1)ATP-binding cassette (ABC) transporterF. graminearumT. aestivum (bread wheat); Z. mays (maize)
FGA2G alpha protein subunitF. oxysporumS. lycopersicum (tomato)
FRP1F-box proteinF. oxysporumS. lycopersicum (tomato)
FOW2Putative Zn finger transcription factorF. oxysporumCucumis melo (muskmelon); S. lycopersicum (tomato)
Fgb1G-protein subunitF. oxysporumS. lycopersicum (tomato)
fmk1Mitogen-activated protein kinase (MAPK)F. oxysporumS. lycopersicum (tomato); Malus domestica (apple)
chsVClass V chitin synthaseF. oxysporumS. lycopersicum (tomato)
FolCzf1C2H2 transcription factor in fusaric acid biosynthesisF. oxysporumS. lycopersicum (tomato)
Msb2Transmembrane proteinF. oxysporumS. lycopersicum (tomato); M. domestica (apple)
CMLE3-carboxy- cis, cis-muconate lactonizing enzymeF. oxysporumS. lycopersicum (tomato)
con7-1Transcription factorF. oxysporumS. lycopersicum (tomato)
FvVE1Biosynthesis of mycotoxins and other secondary metabolitesF. verticillioidesZ. mays (maize)
FSR1Fungal virulence and sexual matingF. verticillioidesZ. mays (maize)
FvSOWW domain protein required for growthF. verticillioidesZ. mays (maize)
FvSTR1Mitogen-activated protein kinase (MAPK)F. virguliformeG. max (soybean)
Table
Table 4. PHI-base curated genes associated with “reduced virulence” mutant phenotype according to Fusarium species.
Table 4. PHI-base curated genes associated with “reduced virulence” mutant phenotype according to Fusarium species.
GeneGene FunctionSpeciesHost Species (Common Name)
FaTuA1alpha-tubulinF. asiaticumTriticum aestivum ( bread wheat)
FaCdc3; FaCdc12SeptinF. asiaticumT. aestivum ( bread wheat)
Famfs1Phenamacril-resistance related geneF. asiaticumT. aestivum ( bread wheat)
Myo5MyosinF. asiaticumT. aestivum ( bread wheat)
FaDHDPS1Dihydrodipicolinate synthase— deoxynivalenol synthesisF. asiaticumT. aestivum ( bread wheat)
FcABC1ABC transporterF. culmorumTriticum ( wheat)
SET1 (FFUJ_02475)H3K4-specific histone methyltransferaseF. fujikuroiOryza sativa (rice)
ARG1Argininosuccinate lyaseF. oxysporumSolanum lycopersicum (tomato)
FGB1G beta protein subunitF. oxysporumS. lycopersicum (tomato)
CHS2Chitin SynthaseF. oxysporumS. lycopersicum (tomato)
CHS7Chitin SynthaseF. oxysporumS. lycopersicum (tomato)
SGE1Transcriptional regulator—morphological switchingF. oxysporumS. lycopersicum (tomato)
FGA1G alpha protein subunitF. oxysporumS. lycopersicum (tomato)
FOW1Mitochondrial carrier proteinF. oxysporumS. lycopersicum (tomato)
foSNF1Protein kinaseF. oxysporumBrassica oleracea
GAS1Beta-1,3-glucanosyltransferaseF. oxysporumS. lycopersicum (tomato)
FOXG_00016Homology to Velvet familyF. oxysporumSolanum peruvianum (peruvian tomato)
tom1TomatinaseF. oxysporumS. lycopersicum (tomato)
Snt2BAH/PHD-containing transcription factorF. oxysporumCucumis melo (muskmelon)
Ctf1; Ctf2Transcriptional activator – cutinase/lipase F. oxysporumS. lycopersicum (tomato)
FoEBR1putative transcription factorF. oxysporumS. lycopersicum (tomato)
FVS1WCMC-4_G03-encoding geneF. oxysporumC. melo (muskmelon)
FoOCH1putative a-1,6-mannosyltransferaseF. oxysporumMusa x paradisiaca (banana)
AreAGlobal nitrogen regulatorF. oxysporumS. lycopersicum (tomato)
Sho1Tetraspan transmembrane proteinF. oxysporumS. lycopersicum (tomato)
Msb2mucin-like membrane proteinF. oxysporumS. lycopersicum (tomato)
Fbp1F-box proteinF. oxysporumS. lycopersicum (tomato)
FoMkk2Mitogen-activated protein kinase (MAPK)F. oxysporumMusa acuminata (dwarf banana)
FoBck1Mitogen-activated protein kinase (MAPK)F. oxysporumM. acuminata (dwarf banana)
pg1EndopolygalacturonaseF. oxysporumS. lycopersicum (tomato)
pgx6ExopolygalacturonaseF. oxysporumS. lycopersicum (tomato)
GLXCWP2 antigenF. oxysporumTriticum aestivum (bread wheat)
fmk1Mitogen-activated protein kinase (MAPK)F. oxysporumS. lycopersicum (tomato)
mpk1Mitogen-activated protein kinase (MAPK)F. oxysporumS. lycopersicum (tomato)
GPABC1ABC transporterF. sambucinumSolanum tuberosum (potato)
CSN1ChitosanaseF. solaniPisum sativum (pea)
Table
Table 5. PHI-base curated trichothecene (TRI) genes associated with “reduced virulence” mutant phenotype according to Fusarium species.
Table 5. PHI-base curated trichothecene (TRI) genes associated with “reduced virulence” mutant phenotype according to Fusarium species.
TRI GeneProtein EncodedSpeciesHost Species
TRI5Trichodiene synthase F. graminearumSecale cereale (rye); Triticum (wheat); Triticum aestivum; (bread wheat); Glycine max (soybean)
TRI5Trichodiene synthase F. pseudograminearumTriticum aestivum (bread wheat)
TRI6Transcription regulator - Zinc finger C2H2 superfamily F. graminearumTriticum aestivum (bread wheat)
TRI10Transcription regulator - Zinc finger C2H2 superfamily F. graminearumTriticum (wheat)
TRI12Trichothecene efflux pump, transmembrane transporter F. graminearumT. aestivum (bread wheat)
TRI14Putative trichothecene biosynthesis proteinF. graminearumT. aestivum (bread wheat)

Share and Cite

MDPI and ACS Style

Rampersad, S.N. Pathogenomics and Management of Fusarium Diseases in Plants. Pathogens 2020, 9, 340. https://doi.org/10.3390/pathogens9050340

AMA Style

Rampersad SN. Pathogenomics and Management of Fusarium Diseases in Plants. Pathogens. 2020; 9(5):340. https://doi.org/10.3390/pathogens9050340

Chicago/Turabian Style

Rampersad, Sephra N. 2020. "Pathogenomics and Management of Fusarium Diseases in Plants" Pathogens 9, no. 5: 340. https://doi.org/10.3390/pathogens9050340

APA Style

Rampersad, S. N. (2020). Pathogenomics and Management of Fusarium Diseases in Plants. Pathogens, 9(5), 340. https://doi.org/10.3390/pathogens9050340

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop