Rhizosphere metagenome
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA615328 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Sugar beet rhizosphere microbiome Targeted Locus (Loci)
| PRJNA233435 | ENA
Project description:Background: The soil environment is responsible for sustaining most terrestrial plant life on earth, yet we know surprisingly little about the important functions carried out by diverse microbial communities in soil. Soil microbes that inhabit the channels of decaying root systems, the detritusphere, are likely to be essential for plant growth and health, as these channels are the preferred locations of new root growth. Understanding the microbial metagenome of the detritusphere and how it responds to agricultural management such as crop rotations and soil tillage will be vital for improving global food production. Methods: The rhizosphere soils of wheat and chickpea growing under + and - decaying root were collected for metagenomics sequencing. A gene catalogue was established by de novo assembling metagenomic sequencing. Genes abundance was compared between bulk soil and rhizosphere soils under different treatments. Conclusions: The study describes the diversity and functional capacity of a high-quality soil microbial metagenome. The results demonstrate the contribution of the microbiome from decaying root in determining the metagenome of developing root systems, which is fundamental to plant growth, since roots preferentially inhabit previous root channels. Modifications in root microbial function through soil management, can ultimately govern plant health, productivity and food security.
2020-03-06 | GSE146427 | GEO
Project description:Beet rhizosphere bacterial metagenome under draught stress and inoculation with wild beet root microbiome
| PRJNA793013 | ENA
Project description:Metagenome of Sugar beet associated microorganisms
| PRJDB1801 | ENA
Project description:Microbial communities in the rhizosphere make significant contributions to crop health and nutrient cycling. However, their ability to perform important biogeochemical processes remains uncharacterized. Important functional genes, which characterize the rhizosphere microbial community, were identified to understand metabolic capabilities in the maize rhizosphere using GeoChip 3.0-based functional gene array method.
2014-09-12 | GSE61338 | GEO
Project description:Beet necrotic yellow vein virus (BNYVV) and Beet soil-borne mosaic virus (BSBMV) belong to the genus Benyvirus. Both viruses share a similar genome organization, but disease development induced in their major host plant sugar beet displays striking differences. BNYVV induces excessive lateral root (LR) formation by hijacking auxin-regulated pathways; whereas BSBMV infected roots appear asymptomatic. To elucidate transcriptomic changes associated with the virus-specific disease development of BNYVV and BSBMV, we performed a comparative transcriptome analysis of a virus infected susceptible sugar beet genotype.
2019-11-06 | E-MTAB-8187 | biostudies-arrayexpress
Project description:Gene expression patterns of the plant colonizing bacterium,Pseudomonas putida KT2440 were evaluated as a function of growth in the Arabidopsis thaliana rhizosphere. Gene expression in rhizosphere grown P. putida cells was compared to gene expression in non-rhizosphere grown cells. Keywords: Gene expression
2008-01-11 | GSE9005 | GEO
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.
2017-12-22 | GSE92859 | GEO