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Transcriptome sequencing of Mycosphaerella fijiensis during association with Musa acuminata reveals candidate pathogenicity genes

Overview of attention for article published in BMC Genomics, August 2016
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  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

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Title
Transcriptome sequencing of Mycosphaerella fijiensis during association with Musa acuminata reveals candidate pathogenicity genes
Published in
BMC Genomics, August 2016
DOI 10.1186/s12864-016-3031-5
Pubmed ID
Authors

Roslyn D. Noar, Margaret E. Daub

Abstract

Mycosphaerella fijiensis, causative agent of the black Sigatoka disease of banana, is considered the most economically damaging banana disease. Despite its importance, the genetics of pathogenicity are poorly understood. Previous studies have characterized polyketide pathways with possible roles in pathogenicity. To identify additional candidate pathogenicity genes, we compared the transcriptome of this fungus during the necrotrophic phase of infection with that during saprophytic growth in medium. Transcriptome analysis was conducted, and the functions of differentially expressed genes were predicted by identifying conserved domains, Gene Ontology (GO) annotation and GO enrichment analysis, Carbohydrate-Active EnZymes (CAZy) annotation, and identification of genes encoding effector-like proteins. The analysis showed that genes commonly involved in secondary metabolism have higher expression in infected leaf tissue, including genes encoding cytochrome P450s, short-chain dehydrogenases, and oxidoreductases in the 2-oxoglutarate and Fe(II)-dependent oxygenase superfamily. Other pathogenicity-related genes with higher expression in infected leaf tissue include genes encoding salicylate hydroxylase-like proteins, hydrophobic surface binding proteins, CFEM domain-containing proteins, and genes encoding secreted cysteine-rich proteins characteristic of effectors. More genes encoding amino acid transporters, oligopeptide transporters, peptidases, proteases, proteinases, sugar transporters, and proteins containing Domain of Unknown Function (DUF) 3328 had higher expression in infected leaf tissue, while more genes encoding inhibitors of peptidases and proteinases had higher expression in medium. Sixteen gene clusters with higher expression in leaf tissue were identified including clusters for the synthesis of a non-ribosomal peptide. A cluster encoding a novel fusicoccane was also identified. Two putative dispensable scaffolds were identified with a large proportion of genes with higher expression in infected leaf tissue, suggesting that they may play a role in pathogenicity. For two other scaffolds, no transcripts were detected in either condition, and PCR assays support the hypothesis that at least one of these scaffolds corresponds to a dispensable chromosome that is not required for survival or pathogenicity. Our study revealed major changes in the transcriptome of Mycosphaerella fijiensis, when associating with its host compared to during saprophytic growth in medium. This analysis identified putative pathogenicity genes and also provides support for the existence of dispensable chromosomes in this fungus.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 57 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 19%
Student > Master 11 19%
Student > Bachelor 7 12%
Researcher 6 11%
Student > Doctoral Student 4 7%
Other 7 12%
Unknown 11 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 27 47%
Biochemistry, Genetics and Molecular Biology 11 19%
Environmental Science 2 4%
Nursing and Health Professions 1 2%
Unspecified 1 2%
Other 2 4%
Unknown 13 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 October 2021.
All research outputs
#6,064,432
of 22,884,315 outputs
Outputs from BMC Genomics
#2,535
of 10,668 outputs
Outputs of similar age
#94,712
of 336,882 outputs
Outputs of similar age from BMC Genomics
#60
of 280 outputs
Altmetric has tracked 22,884,315 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 10,668 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 75% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 336,882 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 280 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.