Ontology highlight
ABSTRACT:
PROVIDER: PRJNA901126 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR22269422_1.fastq.gz | Fastqsanger.gz | |||
| SRR22269422_2.fastq.gz | Fastqsanger.gz | |||
| SRR22269423_1.fastq.gz | Fastqsanger.gz | |||
| SRR22269423_2.fastq.gz | Fastqsanger.gz | |||
| SRR22269424_1.fastq.gz | Fastqsanger.gz |
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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:Although genetically modified glyphosate resistant soybeans with cp4-epsps gene have been widely planted all over the world, the proteomic characteristics of them are not very clear. In this study, the soybean seeds of a genetically modified (GM) soybean line H06-698 (H) with cp4-epsps gene and its non-transgenic counterpart Mengdou12 (M), which collected from different planting regions in two years, were analyzed with label-free proteomics technique.
2021-05-10 | PXD025908 |
Project description:Arsenic (As) bioavailability in the rice rhizosphere is influenced by many microbial interactions, particularly by metal-transforming functional groups at the root-soil interface. This study was conducted to examine As-transforming microbes and As-speciation in the rice rhizosphere compartments, in response to two different water management practices (continuous and intermittently flooded), established on fields with high to low soil-As concentration. Microbial functional gene composition in the rhizosphere and root-plaque compartments were characterized using the GeoChip 4.0 microarray. Arsenic speciation and concentrations were analyzed in the rhizosphere soil, root-plaque, porewater and grain samples. Results indicated that intermittent flooding significantly altered As-speciation in the rhizosphere, and reduced methyl-As and AsIII concentrations in the pore water, root-plaque and rice grain. Ordination and taxonomic analysis of detected gene-probes indicated that root-plaque and rhizosphere assembled significantly different metal-transforming functional groups. Taxonomic non-redundancy was evident, suggesting that As-reduction, -oxidation and -methylation processes were performed by different microbial groups. As-transformation was coupled to different biogeochemical cycling processes establishing functional non-redundancy of rice-rhizosphere microbiome in response to both rhizosphere compartmentalization and experimental treatments. This study confirmed diverse As-biotransformation at root-soil interface and provided novel insights on their responses to water management, which can be applied for mitigating As-bioavailability and accumulation in rice grains.
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Project description:This data set contains 1376 mass spectrometry reads from root, rhizosphere and leaf sample of Populus Trichocarpa, as well as associated controls. This metabolomics data set was collected as part of a larger campaign which complements the metabolomics data with metagenome sequencing, transcriptomics, and soil measurement data.
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Project description:Many of the microorganisms that are normally present in the soil, actually inhabit the rhizosphere and interact with plants. Those plant–microorganisms interactions may be beneficial or harmful. Among the first are the arbuscular mycorrhizal fungi (AMF). These soil fungi have been reported to improve plant resistance/tolerance to pests and diseases. On the other hand, soilborne pathogens represent a threat to agriculture generating important yield losses, depending upon the pathogen and the crop. One example is the “Sudden Death Syndrome” (SDS), a severe disease in soybean (Glycine max (L.) Merr) caused by a complex of at least four species of Fusarium sp., among which Fusarium virguliforme and F. tuccumaniae are the most prevalent in Argentina. This study provides, under strict in vitro culture conditions, a global analysis of transcript modifications in mycorrhizal and non-mycorrhizal soybean root associated with F. virguliforme inoculation. Microarray results showed qualitative and quantitative changes in the expression of defense-related genes in mycorrhizal soybean, suggesting that AMF are good candidates for sustainable plant protection against F. virguliforme.
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Project description:According to the Canadian Food Inspection Agency and Health Canada, genetically modified crops are considered safe if they are substantially equivalent to a conventional crop in regards to agronomic, physiological and compositional characteristics. A recurring issue in safety assessment of genetically modified crops is the paucity of analytical methods to detect unintended or unexpected outcomes of genetic modification. Traditional targeted compound comparative analyses are limited in scope and capacity to detect unintended changes in chemical composition. This study explored the potential of using microarray technology to assess the substantial equivalence of gene expression profiles between genetically modified and conventional soybean cultivars. Different pre processing methods were applied to the raw expression data from the arrays, and clustering methods were used to try and differentiate the genetically modified cultivars from the conventional cultivars. Results showed that more variation existed between different strains of conventional cultivars than between conventional and genetically modified cultivars. For more information, please see: Cheng, K.C., Beaulieu, J., Iquira, E., Belzile, F.J., Fortin, M.G. and Strömvik, M.V. (2008). âEffect of transgenes on global gene expression in soybean is within the natural range of variation of their conventional counterparts.â Journal of Agricultural and Food Chemistry (in press) Experiment Overall Design: Five samples (biological replicates) of total RNA from each of the five different soybean varieties were selected for hybridization to Affymetrix Soybean GeneChips, for a total of 25 chips (following total RNA integrity assessment). Spike controls B2, bio-B, bio-C, bio-D and Cre-x were added to each hybridization cocktail. Arrays were washed and stained in an Affymetrix Fluidics Station prior to scanning on the Affymetrix GeneChip Scanner 3000. Image acquisition and processing was done with the Affymetrix Microarray Analysis Suite 5.0.
2008-06-16 | E-GEOD-9374 | biostudies-arrayexpress
Project description:According to the Canadian Food Inspection Agency and Health Canada, genetically modified crops are considered safe if they are substantially equivalent to a conventional crop in regards to agronomic, physiological and compositional characteristics. A recurring issue in safety assessment of genetically modified crops is the paucity of analytical methods to detect unintended or unexpected outcomes of genetic modification. Traditional targeted compound comparative analyses are limited in scope and capacity to detect unintended changes in chemical composition. This study explored the potential of using microarray technology to assess the substantial equivalence of gene expression profiles between genetically modified and conventional soybean cultivars. Different pre processing methods were applied to the raw expression data from the arrays, and clustering methods were used to try and differentiate the genetically modified cultivars from the conventional cultivars. Results showed that more variation existed between different strains of conventional cultivars than between conventional and genetically modified cultivars. For more information, please see: Cheng, K.C., Beaulieu, J., Iquira, E., Belzile, F.J., Fortin, M.G. and Strömvik, M.V. (2008). Effect of transgenes on global gene expression in soybean is within the natural range of variation of their conventional counterparts. Journal of Agricultural and Food Chemistry. Keywords: Expression comparison between genetically modified cultivars
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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. Triplicate samples were taken for both rhizosphere and bulk soil, in which each individual sample was a pool of four plants or soil cores. To determine the abundance of functional genes in the rhizosphere and bulk soils, GeoChip 3.0 was used.
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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. Triplicate samples were taken for both rhizosphere and bulk soil, in which each individual sample was a pool of four plants or soil cores. To determine the abundance of functional genes in the rhizosphere and bulk soils, GeoChip 3.0 was used.
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