Soil and water
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA398988 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR5947160.fastq.gz | Fastqsanger.gz | |||
| SRR5947170.fastq.gz | Fastqsanger.gz | |||
| SRR5947161.fastq.gz | Fastqsanger.gz | |||
| SRR5947171.fastq.gz | Fastqsanger.gz | |||
| SRR5947162.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 17 |
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Project description:A cultivation facility that can assist users in controlling the soil water condition is needed for accurately phenotyping plants under drought stress in an artificial environment. Here we report the Internet of Things (IoT)-based pot system controlling optional treatment of soil water condition (iPOTs), an automatic irrigation system that mimics the drought condition in a growth chamber. The Wi-Fi-enabled iPOTs system allows water supply from the bottom of the pot, based on the soil water level set by the user, and automatically controls the soil water level at a desired depth. The iPOTs also allows users to monitor environmental parameters, such as soil temperature, air temperature, humidity, and light intensity, in each pot. To verify whether the iPOTs mimics the drought condition, we conducted a drought stress test on rice varieties and near-isogenic lines, with diverse root system architecture, using the iPOTs system installed in a growth chamber. Similar to the results of a previous drought stress field trial, the growth of shallow-rooted rice accessions was severely affected by drought stress compared with that of deep-rooted accessions. The microclimate data obtained using the iPOTs system increased the accuracy of plant growth evaluation. Transcriptome analysis revealed that pot positions in the growth chamber had little impact on plant growth. Together, these results suggest that the iPOTs system represents a reliable platform for phenotyping plants under drought stress.
2021-08-24 | GSE171578 | GEO
Project description:Burkholderia pseudomallei can adapt to and thrive in a variety of environments, including soil and water, and also can infect different hosts, including humans, leading to the tropical disease melioidosis. Modulation of gene and protein expression is one of this pathogen's adaptive survival mechanisms, which could lead to changes in the bacteria's cell membrane, metabolism, and virulence. To better understand bacterial adaptation and host-pathogen interactions, this study compared the expression profiles of B. pseudomallei from infected mice to B. pseudomallei cultivated in soil extract media. B. pseudomallei in vivo was created by infecting mice through the intraperitoneal route and harvesting the spleens on day 5 post infection. Total RNA was isolated and sequenced from the harvested spleen. Sequence reads were mapped to the B. pseudomallei UKMD286 strain genome sequence.
2022-07-22 | E-MTAB-11200 | biostudies-arrayexpress
Project description:Purpose: Deconstructing the soil microbiome into reduced-complexity functional modules represents a novel method of microbiome analysis. The goals of this study are to confirm differences in transcriptomic patterns among five functional module consortia. Methods: mRNA profiles of 3 replicates each of functional module enrichments of soil inoculum in M9 media with either 1) xylose, 2) n-acetylglucosamine, 3) glucose and gentamycin, 4) xylan, or 5) pectin were generated by sequencing using an Illumina platform (GENEWIZ performed sequencing). Sequence reads that passed quality filters were aligned to a soil metagenome using Burrows Wheeler Aligner. Resulting SAM files were converted to raw reads using HTSeq, and annotated using Uniref90 or EGGNOG databases. Results: To reduce the size of the RNA-Seq counts table and increase its computational tractability, transcripts containing a minimum of 75 total counts, but no more than 3 zero counts, across the 15 samples were removed. The subsequent dataset was normalized using DESeq2, resulting in a dataset consisting of 6947 unique transcripts across the 15 samples, and 185,920,068 reads. We identified gene categories that were enriched in a sample type relative to the overall dataset using Fisher’s exact test. Conclusions: our dataset confirms that the functional module consortia generated from targeted enrichments of a starting soil inoculum had distinct functional trends by enrichment type.
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Project description:Soil water repellency (SWR) (i.e. soil hydrophobicity or decreased soil wettability) is a major cause of global soil degradation and a key agricultural concern. This metabolomics data will support the larger effort measuring soil water repellency and soil aggregate formation caused by microbial community composition through a combination of the standard drop penetration test, transmission electron microscopy characterization and physico-chemical analyses of soil aggregates at 6 timepoints. Model soils created from clay/sand mixtures as described in Kallenbach et al. (2016, Nature Communications) with sterile, ground pine litter as a carbon/nitrogen source were inoculated with 15 different microbial communities known to have significantly different compositions based on 16S rRNA sequencing. This data will allow assessment of the direct influence of microbial community composition on soil water repellency and soil aggregate stability, which are main causes of soil degradation.
The work (proposal:https://doi.org/10.46936/10.25585/60001346) conducted by the U.S. Department of Energy Joint Genome Institute (https://ror.org/04xm1d337), a DOE Office of Science User Facility, is supported by the Office of Science of the U.S. Department of Energy operated under Contract No. DE-AC02-05CH11231.
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