Ontology highlight
ABSTRACT:
PROVIDER: PRJNA327805 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR3825850_1.fastq.gz | Fastqsanger.gz | |||
| SRR3825850_2.fastq.gz | Fastqsanger.gz | |||
| SRR3825860_1.fastq.gz | Fastqsanger.gz | |||
| SRR3825860_2.fastq.gz | Fastqsanger.gz | |||
| SRR3825851_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 40 |
Similar Datasets
Project description:Xiangjiang River (Hunan, China) has been contaminated with heavy metal for several decades by surrounding factories. However, little is known about the influence of a gradient of heavy metal contamination on the diversity, structure of microbial functional gene in sediment. To deeply understand the impact of heavy metal contamination on microbial community, a comprehensive functional gene array (GeoChip 5.0) has been used to study the functional genes structure, composition, diversity and metabolic potential of microbial community from three heavy metal polluted sites of Xiangjiang River. Three groups of samples, A, B and C. Every group has 3 replicates.
2016-08-02 | E-GEOD-85064 | biostudies-arrayexpress
Project description:In this study, a metaproteomic approach was used for a detailed analysis of the structure of the microbial community, temporal changes and the functional role of the microbiota during pozol fermentation.
2021-07-14 | PXD026781 | Pride
Project description:In this study, a metaproteomic approach was used for a detailed analysis of the structure of the microbial community, temporal changes and the functional role of the microbiota during pozol fermentation.
2022-02-17 | PXD026705 | Pride
Project description:In this study, a metaproteomic approach was used for a detailed analysis of the structure of the microbial community, temporal changes and the functional role of the microbiota during pozol fermentation.
2022-02-17 | PXD026648 | Pride
Project description:Xiangjiang River (Hunan, China) has been contaminated with heavy metal for several decades by surrounding factories. However, little is known about the influence of a gradient of heavy metal contamination on the diversity, structure of microbial functional gene in sediment. To deeply understand the impact of heavy metal contamination on microbial community, a comprehensive functional gene array (GeoChip 5.0) has been used to study the functional genes structure, composition, diversity and metabolic potential of microbial community from three heavy metal polluted sites of Xiangjiang River.
2016-08-02 | GSE85064 | 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+–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