Ontology highlight
ABSTRACT:
PROVIDER: PRJNA627342 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR11586697_1.fastq.gz | Fastqsanger.gz | |||
| SRR11586697_2.fastq.gz | Fastqsanger.gz | |||
| SRR11586698_1.fastq.gz | Fastqsanger.gz | |||
| SRR11586698_2.fastq.gz | Fastqsanger.gz | |||
| SRR11699194.fastq.gz | Fastqsanger.gz |
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Project description:Cotton is the main source of natural fiber in the textile industry, making it one of the most economically important fiber crops in the world. Verticillium wilt, caused by the pathogenic fungus Verticillium dahlia, is one of the most damaging biotic factors limiting cotton production. Mechanistic details of cotton defense responses to verticillium wilt remain unclear. In this study, GFP-labeled strain of V. dahlia was used to track colonization in cotton roots, and clear conidial germination could be observed at 48 hours post-inoculation (hpi), marking this as a crucial time point during infection. Transcriptome analysis identified 1,523 and 8,270 differentially expressed genes (DEGs) at 24 hpi and 48 hpi, respectively. Metabolomic screening found 78 differentially accumulated metabolites (DAMs) at 48 hpi. Conjoint analysis indicated that the phenylpropanoid biosynthesis pathway was activated in cotton infected with V. dahliae. The five metabolites in the phenylpropanoid biosynthesis pathway, including caffeic acid, coniferyl alcohol, coniferin, scopoletin and scopolin, could significantly inhibit V. dahlia growth in vitro, implicating their roles in cotton resistance to Verticillium wilt. The findings expand our understanding of molecular mechanisms underlying the pathogen defense response against V. dahlia infection in upland cotton, which may lead to future insights into controlling Verticillium wilt disease.
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Project description:The advent of next generation sequencing (NGS) has greatly enriched the database of miRNAs. For plants so far 8455 miRNAs sequences from 73 species and 15401 miRNAs sequences from 150 species have been deposited in miRBase 22.0 and Plant Non-coding RNA Database, respectively. The occurrence of miRNAs in such a huge number, which is still increasing, is because of the fact that the profile of miRNAs expression differs greatly from species to species, both quantitatively and qualitatively. Besides, even within a species it is expected that the miRNA expression profile would differ from cultivar to cultivar depending on the trait with regard to which the two cultivars differ. Beises, the expression of a miRNA in a plant organ may differ depending upon it spatial location. The same is reflected in the NGS data of the apical and basal spikelets of the panicle of the rice cultivar Mahalaxmi.
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