Ontology highlight
ABSTRACT:
PROVIDER: PRJNA694777 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR13528221_1.fastq.gz | Fastqsanger.gz | |||
| SRR13528221_2.fastq.gz | Fastqsanger.gz | |||
| SRR13528222_1.fastq.gz | Fastqsanger.gz | |||
| SRR13528222_2.fastq.gz | Fastqsanger.gz | |||
| SRR13528223_1.fastq.gz | Fastqsanger.gz |
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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:Understanding and quantifying the effects of environmental factors influencing the variation of abundance and diversity of microbial communities was a key theme of ecology. For microbial communities, there were two factors proposed in explaining the variation in current theory, which were contemporary environmental heterogeneity and historical events. Here, we report a study to profile soil microbial structure, which infers functional roles of microbial communities, along the latitudinal gradient from the north to the south in China mainland, aiming to explore potential microbial responses to external condition, especially for global climate changes via a strategy of space-for-time substitution. Using a microarray-based metagenomics tool named GeoChip 5.0, we showed that microbial communities were distinct for most but not all of the sites. Using substantial statistical analyses, exploring the dominant factor in influencing the soil microbial communities along the latitudinal gradient. Substantial variations were apparent in nutrient cycling genes, but they were in line with the functional roles of these genes. 300 samples were collected from 30 sites along the latitudinal gradient, with 10 replicates in every site
2015-05-23 | E-GEOD-69171 | biostudies-arrayexpress
Project description:Understanding and quantifying the effects of environmental factors influencing the variation of abundance and diversity of microbial communities was a key theme of ecology. For microbial communities, there were two factors proposed in explaining the variation in current theory, which were contemporary environmental heterogeneity and historical events. Here, we report a study to profile soil microbial structure, which infers functional roles of microbial communities, along the latitudinal gradient from the north to the south in China mainland, aiming to explore potential microbial responses to external condition, especially for global climate changes via a strategy of space-for-time substitution. Using a microarray-based metagenomics tool named GeoChip 5.0, we showed that microbial communities were distinct for most but not all of the sites. Using substantial statistical analyses, exploring the dominant factor in influencing the soil microbial communities along the latitudinal gradient. Substantial variations were apparent in nutrient cycling genes, but they were in line with the functional roles of these genes.
2015-05-23 | GSE69171 | 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: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:Understanding biological diversity and distribution patterns at multiple spatial scales is a central issue in ecology. Here, we investigated the biogeographical patterns of functional genes in soil microbes from 24 arctic heath sites using GeoChip-based metagenomics and principal coordinates of neighbour matrices (PCNM)-based analysis. Functional gene richness varied considerably among sites, while the proportions of each major functional gene category were evenly distributed. Functional gene composition varied significantly at most medium and broad spatial scales, and the PCNM analyses indicated that 14-20% of the variation in total and major functional gene categories could be attributed primarily to relatively broad-scale spatial effects that were consistent with broad-scale variation in soil pH and total nitrogen. The combination of variance partitioning and multi-scales analysis indicated that spatial distance effects contributed 12% to variation in functional gene composition，whereas environmental factors contributed only 3%. This relatively strong influence of spatial as compared to environmental variation in determining functional gene distributions contrasts sharply with typical microbial phylotype/species-based biogeographical patterns in the Arctic and elsewhere. Our results suggest that the distributions of soil functional genes cannot be predicted from phylogenetic distributions because spatial factors associated with historical contingencies are relatively important determinants of their biogeography.
2014-12-10 | GSE63927 | GEO
Project description:Due to its high altitude and extreme climate conditions, the Tibetan plateau is a region vulnerable to the impact of climate changes and anthropogenic perturbation, thus understanding how its microbial communities function may be of high importance. Here, we report a study to profile soil microbial structural genes, which infers functional roles of microbial communities, aiming to explore potential microbial responses to climate changes and anthropogenic perturbation. Using a microarray-based metagenomics tool named GeoChip 4.0, we showed that microbial communities in treatment site were distinct, compared with those in control site, e.g. shrubland vs grassland, grazing site vs ungrazing site, or warmer site vs colder site. Substantial variations were apparent in stress, N and C cycling genes, but they were in line with the functional roles of these genes.
2013-11-16 | GSE52425 | 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, 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. sixty-three samples were collected from four elevations (3200,3400,3600 and 3800 m) along a Tibetan alpine meadow; Three replicates in each treatment
2013-11-16 | E-GEOD-52425 | biostudies-arrayexpress
Project description:integrated soil metagenomics and metaproteomics to study grassland soil microbial communities
2019-03-27 | PXD013110 | Pride
Project description:Monitoring microbial communities can aid in understanding the state of these habitats. Environmental DNA (eDNA) techniques provide efficient and comprehensive monitoring by capturing broader diversity. Besides structural profiling, eDNA methods allow the study of functional profiles, encompassing the genes within the microbial community. In this study, three methodologies were compared for functional profiling of microbial communities in estuarine and coastal sites in the Bay of Biscay. The methodologies included inference from 16S metabarcoding data using Tax4Fun, GeoChip microarrays, and shotgun metagenomics.
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