Ontology highlight
ABSTRACT:
PROVIDER: PRJNA591695 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR10559329.fastq.gz | Fastqsanger.gz | |||
| SRR10559330.fastq.gz | Fastqsanger.gz | |||
| SRR10559331.fastq.gz | Fastqsanger.gz | |||
| SRR10559332.fastq.gz | Fastqsanger.gz | |||
| SRR10559333.fastq.gz | Fastqsanger.gz |
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Project description:Dynamics of Microbial community compositions in Cochlodinium polykrikoides bloom and non-bloom period Metagenome
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Project description:Tibet is one of the most threatened regions by climate warming, thus understanding how its microbial communities function may be of high importance for predicting microbial responses to climate changes. Here, we report a study to profile soil microbial structural genes, which infers functional roles of microbial communities, along four sites/elevations of a Tibetan mountainous grassland, aiming to explore potential microbial responses to climate changes via a strategy of space-for-time substitution. Using a microarray-based metagenomics tool named GeoChip 4.0, we showed that microbial communities were distinct for most but not all of the sites. Substantial variations were apparent in stress, N and C cycling genes, but they were in line with the functional roles of these genes. Cold shock genes were more abundant at higher elevations. Also, gdh converting ammonium into urea was more abundant at higher elevations while ureC converting urea into ammonium was less abundant, which was consistent with soil ammonium contents. Significant correlations were observed between N-cycling genes (ureC, gdh and amoA) and nitrous oxide flux, suggesting that they contributed to community metabolism. Lastly, we found by CCA, Mantel tests and the similarity tests that soil pH, temperature, NH4+–N and vegetation diversity accounted for the majority (81.4%) of microbial community variations, suggesting that these four attributes were major factors affecting soil microbial communities. Based on these observations, we predict that climate changes in the Tibetan grasslands are very likely to change soil microbial community functional structure, with particular impacts on microbial N cycling genes and consequently microbe-mediated soil N dynamics.
2013-07-13 | GSE48820 | GEO
Project description:Tibet is one of the most threatened regions by climate warming, thus understanding how its microbial communities function may be of high importance for predicting microbial responses to climate changes. Here, we report a study to profile soil microbial structural genes, which infers functional roles of microbial communities, along four sites/elevations of a Tibetan mountainous grassland, aiming to explore potential microbial responses to climate changes via a strategy of space-for-time substitution. Using a microarray-based metagenomics tool named GeoChip 4.0, we showed that microbial communities were distinct for most but not all of the sites. Substantial variations were apparent in stress, N and C cycling genes, but they were in line with the functional roles of these genes. Cold shock genes were more abundant at higher elevations. Also, gdh converting ammonium into urea was more abundant at higher elevations while ureC converting urea into ammonium was less abundant, which was consistent with soil ammonium contents. Significant correlations were observed between N-cycling genes (ureC, gdh and amoA) and nitrous oxide flux, suggesting that they contributed to community metabolism. Lastly, we found by CCA, Mantel tests and the similarity tests that soil pH, temperature, NH4+M-bM-^@M-^SN and vegetation diversity accounted for the majority (81.4%) of microbial community variations, suggesting that these four attributes were major factors affecting soil microbial communities. Based on these observations, we predict that climate changes in the Tibetan grasslands are very likely to change soil microbial community functional structure, with particular impacts on microbial N cycling genes and consequently microbe-mediated soil N dynamics. Twelve samples were collected from four elevations (3200, 3400, 3600 and 3800 m) along a Tibetan grassland; Three replicates in every elevation
2013-07-13 | E-GEOD-48820 | biostudies-arrayexpress
Project description:Microbial community dynamics and coexistence in a sulfide-driven phototrophic bloom
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Project description:Sequencing the metatranscriptome can provide information about the response of organisms to varying environmental conditions. We present a methodology for obtaining random whole-community mRNA from a complex microbial assemblage using Pyrosequencing. The metatranscriptome had, with minimum contamination by ribosomal RNA, significant coverage of abundant transcripts, and included significantly more potentially novel proteins than in the metagenome. Keywords: metatranscriptome, mesocosm, ocean acidification This experiment is part of a much larger experiment. We have produced 4 454 metatranscriptomic datasets and 6 454 metagenomic datasets. These were derived from 4 samples. The experiment is an ocean acidification mesocosm set up in a Norwegian Fjord in 2006. We suspended 6 bags containing 11,000 L of sea water in a Coastal Fjord and then we bubbled CO2 through three of these bags to simulate ocean acidification conditions in the year 2100. The other three bags were bubbled with air. We then induced a phytoplankton bloom in all six bags and took measurements and performed analyses of phytoplankton, bacterioplankton and physiochemical characteristics over a 22 day period. We took water samples from the peak of the phytoplankton bloom and following the decline of the phytoplankton bloom to analyses using 454 metagenomics and 454 metatranscriptomics. Day 1, High CO2 Bag and Day 1, Present Day Bag, refer to the metatranscriptomes from the peak of the bloom. Day 2, High CO2 Bag and Day 2, Present Day Bag, refer to the metatranscriptomes following the decline of the bloom. Obviously High CO2 refers to the ocean acidification mesocosm and Present Day refers to the control mesocosm. Raw data for both the metagenomic and metatranscriptomic components are available at NCBI's Short Read Archive at ftp://ftp.ncbi.nlm.nih.gov/sra/Studies/SRP000/SRP000101
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