Amaranthaceae
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA41497 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| AYZS02.dat.gz | Other | |||
| AYZS02.fasta.gz | Fasta.gz | |||
| AYZS02.master.dat | Other | |||
| AYZT01.dat.gz | Other | |||
| AYZT01.fasta.gz | Fasta.gz |
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Project description:Intervention type:DRUG
Name of intervention:Huaier
Dose form / Japanese Medical Device Nomenclature:GRANULES
Route of administration / Site of application:ORAL
Dose per administration:20?
g
Dosing frequency / Frequency of use:OTHER, SPECIFY
20g? per day
Planned duration of intervention:3 months to extending if necessary
Intended dose regimen:20 to 60/day by either bulk or split for 3 months to extended term if necessary
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Comparative intervention name:None
Dose form / Japanese Medical Device Nomenclature:
Route of administration / Site of application:
Dose per administration:
Dosing frequency / Frequency of use:
Planned duration of intervention:
Intended dose regimen:
Primary outcome(s): For mRNA libraries, focus on mRNA studies. Data analysis includes sequencing data processing and basic sequencing data quality control, prediction of new transcripts, differential expression analysis of genes. Gene Ontology (GO) and the KEGG pathway database are used for annotation and enrichment analysis of up-regulated genes and down-regulated genes.
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Project description:To identify known and novel miRNAs involved in the response and adaptation of sugar beet to short-term and long-term alkaline stress, miRNAs were identified by analysis of the deep sequencing of sRNA
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Project description:Background: Sugar beet is an important root crop, accounting for 30 % of the sugar production worldwide. The long growing season make sugar beets exposed to a range of plant pathogens for longer periods than most other crops. Here, contrasting sugar beet genotypes were used for transcriptome analysis to reveal differential responses and new defense genes to Rhizoctonia solani, a soilborn fungal pathogen. Results: After curation of primary RNA-sequencing reads, 16,768 genes deriving from 36 samples composed of two susceptible and two resistant sugar beet genotypes, three time-points (0, two and five days post inoculation), each in three replicates were subjected for analysis. Among the elevated 217 transcripts at 2 dpi, three resistance-like genes (Bv4_088600_cumk, Bv8u_204980_frqg, and Bv_44840_iifo) were activated. By employing edgeR package statistics, 660 genes were significantly different (false discovery rate < 0.05) between resistant and susceptible genotypes in their response to R. solani inoculation. A combination of eukaryotic orthologous group assignments and gene ontology enrichment analyses, revealed three Bet v I/Major latex protein homologous genes (Bv7_162510_pymu, Bv7_162520_etow, Bv_27270_xeas) in the resistant genotypes after five days of fungal challenge. Co-expression network analysis of differentially expressed sugar beet genes further identified a MYB46 transcription factor, a plant disease resistance response protein (DRR206) and a flavonoid o-methyltransferase protein. MYB46 has a key function in secondary cell wall formation and exist as a singleton in the sugar beet genome. The genome of R. solani is enriched in cell wall degrading enzyme encoding genes and it is anticipated that they represent important virulence factors. Compared to Arabidopsis thaliana, sugar beet has 2.4-fold more carbohydrate esterases and particularly large numbers (26-fold) of auxiliary activity encoding genes whose function in cell wall biosynthesis is largely unknown. Conclusions: Based on components identified in this sugar beet transcript data set we conclude that defense responses to R. solani are attributed to a wide range of gene categories but functional information is missing to a large extent. This calls for careful integration to avoid negative side effects to obtain optimal combinations of these traits in order to reach the long-term goal of improved resistance in sugar beet.
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Project description:We analyzed lncRNAs and mRNAs from sugar beet leaves under water control treatment using high-throughput sequencing technology and bioinformatic approaches to explore the genome-wide quantity of lncRNAs and mRNAs and their potential function in the regulation of drought responses.
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