The Genomes of Mycosphaerella graminicola and M. fijiensis

Goodwin, Stephen B.; Kema, Gert H. J.

doi:10.1007/978-3-662-44053-7_5

Cited by 9 publications

(10 citation statements)

References 72 publications

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“…malaccensis double-haploid Pahang [ 78 ], and to the M . fijiensis genome [ 27 ] using Tophat v2.0.9 [ 79 ]. Gene expression levels were determined using HTSeq v0.6.0 [ 80 ], with gene annotations available from JGI.…”

Section: Methodsmentioning

confidence: 99%

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Bioinformatics Prediction of Polyketide Synthase Gene Clusters from Mycosphaerella fijiensis

Noar

Daub

2016

PLoS ONE

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Mycosphaerella fijiensis, causal agent of black Sigatoka disease of banana, is a Dothideomycete fungus closely related to fungi that produce polyketides important for plant pathogenicity. We utilized the M. fijiensis genome sequence to predict PKS genes and their gene clusters and make bioinformatics predictions about the types of compounds produced by these clusters. Eight PKS gene clusters were identified in the M. fijiensis genome, placing M. fijiensis into the 23rd percentile for the number of PKS genes compared to other Dothideomycetes. Analysis of the PKS domains identified three of the PKS enzymes as non-reducing and two as highly reducing. Gene clusters contained types of genes frequently found in PKS clusters including genes encoding transporters, oxidoreductases, methyltransferases, and non-ribosomal peptide synthases. Phylogenetic analysis identified a putative PKS cluster encoding melanin biosynthesis. None of the other clusters were closely aligned with genes encoding known polyketides, however three of the PKS genes fell into clades with clusters encoding alternapyrone, fumonisin, and solanapyrone produced by Alternaria and Fusarium species. A search for homologs among available genomic sequences from 103 Dothideomycetes identified close homologs (>80% similarity) for six of the PKS sequences. One of the PKS sequences was not similar (< 60% similarity) to sequences in any of the 103 genomes, suggesting that it encodes a unique compound. Comparison of the M. fijiensis PKS sequences with those of two other banana pathogens, M. musicola and M. eumusae, showed that these two species have close homologs to five of the M. fijiensis PKS sequences, but three others were not found in either species. RT-PCR and RNA-Seq analysis showed that the melanin PKS cluster was down-regulated in infected banana as compared to growth in culture. Three other clusters, however were strongly upregulated during disease development in banana, suggesting that they may encode polyketides important in pathogenicity.

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Section: Methodsmentioning

confidence: 99%

“…Recent sequencing of the M . fijiensis genome [ 26 , 27 ] allows for a bioinformatics analysis of PKS genes and clusters in the genome. Polyketide synthases in fungi are large, multi-domain enzymes that act iteratively to produce the polyketide chain.…”

Section: Introductionmentioning

confidence: 99%

Bioinformatics Prediction of Polyketide Synthase Gene Clusters from Mycosphaerella fijiensis

Noar

Daub

2016

PLoS ONE

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“…This supports the hypothesis that random-mating -in accord with a heterothallic bipolar mating system, similar to the related Zymoseptoria tritici (Conde-Ferraez et al 2007;Goodwin & Kema 2014;Kema et al 1996;Waalwijk et al 2002) exists within the population and underlines the important role of ascospore dissemination (Carlier et al 1996;Halkett et al 2010;Rieux et al 2014;Rivas et al 2004b). The colonization patterns are also supported by genetic studies from a historical perspective.…”

Section: Pseudocercospora Fijiensis Geneticssupporting

confidence: 80%

The origin, versatility and distribution of azole fungicide resistance in the banana black Sigatoka pathogen Pseudocercospora fijiensis

Aguirre

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“…For instance, species unique to the various semiochemical types were from genera composed of important plant pathogens. Among others, Phoma glomerata, the causal agent of blight, leaf spots, and fruit rot of many plants, was uniquely detected in C6C8 samples, whereas Mycosphaerella areola (mildew)-despite the fact that it typically infects wheat leaves [93,94], field peas [95], and cruciferous vegetables [96]-was only detected in General Longhorn-baited trap samples. This semiochemical is an aggregation pheromone for longhorned beetles in the Spondylidinae [57] and Lamiinae subfamilies [70].…”

Section: Discussionmentioning

confidence: 99%

Next-generation sequencing to investigate existing and new insect associations with phytopathogenic fungal propagules

Tremblay¹,

Kimoto²,

Bérubé³

et al. 2018

Preprint

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Understanding ecological interactions is a key in managing phytopathology. Although entomologists rely mostly on both traditional molecular methods and morphological characteristics to identify pests, next-generation sequencing is becoming the go-to avenue for scientists studying fungal and oomycete phytopathogens. These organisms sometimes infect plants together with insects. There are many relationships yet to be discovered and much to learn about how these organisms interact with one another. Considering the growing number of exotic insect introductions in Canada, a high-throughput strategy for screening those insects is already implemented by the Canadian Food Inspection Agency (CFIA). However, no plan is deployed to investigate the phytopathogenic fungal and oomycete species interacting with insects. Metagenomics analysis was performed on the preservation fluids from CFIA’s insect traps across Canada. Using the Ion Torrent PGM technology and fusion primers for multiplexing and indexing, community profiling was conducted on the different semiochemicals used in the insect traps and the various areas where these traps were placed. Internal transcribed spacer 1 (fungi and oomycetes) and adenosine triphosphate synthase subunit 9-nicotinamide adenine dinucleotide dehydrogenase subunit 9 spacer amplicons were generated. Although direct links between organisms could not be established, moderately phytopathogenic fungi (e.g., Leptographium spp. and Meria laricis) and oomycetes (mainly Peronospora spp. and Pythium spp.) unique to every type of semiochemical were discovered. The entomopathogenic yeast Candida michaelii was also detected. This project demonstrated our ability to screen for unwanted species faster and at a higher scale and throughput than traditional pathogen diagnostic techniques. Additionally, minimal modifications to this approach would allow it to be used in other phytopathology fields.

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The Genomes of Mycosphaerella graminicola and M. fijiensis

Cited by 9 publications

References 72 publications

Bioinformatics Prediction of Polyketide Synthase Gene Clusters from Mycosphaerella fijiensis

Bioinformatics Prediction of Polyketide Synthase Gene Clusters from Mycosphaerella fijiensis

The origin, versatility and distribution of azole fungicide resistance in the banana black Sigatoka pathogen Pseudocercospora fijiensis

Next-generation sequencing to investigate existing and new insect associations with phytopathogenic fungal propagules

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