Columbia River coastal margin 'omics
Ontology highlight
ABSTRACT:
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR864069_1.fastq.gz | Fastqsanger.gz | |||
| ERR864069_2.fastq.gz | Fastqsanger.gz | |||
| ERR864070_1.fastq.gz | Fastqsanger.gz | |||
| ERR864070_2.fastq.gz | Fastqsanger.gz | |||
| ERR864071_1.fastq.gz | Fastqsanger.gz |
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Project description:EMG produced TPA metagenomics assembly of the Coupled metagenomic and metatransciptomic study of the Columbia River coastal margin salinity gradient (Columbia River coastal margin 'omics) data set
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Project description:Analysis of microbial gene expression in response to physical and chemical gradients forming in the Columbia River, estuary, plume and coastal ocean was done in the context of the environmental data base. Gene expression was analyzed for 2,234 individual genes that were selected from fully sequenced genomes of 246 prokaryotic species (bacteria and archaea) as related to the nitrogen metabolism and carbon fixation. Seasonal molecular portraits of differential gene expression in prokaryotic communities during river-to-ocean transition were created using freshwater baseline samples (268, 270, 347, 002, 006, 207, 212). Total RNA was isolated from 64 filtered environmental water samples collected in the Columbia River coastal margin during 4 research cruises (14 from August, 2007; 17 from November, 2007; 18 from April, 2008; and 16 from June, 2008), and analyzed using microarray hybridization with the CombiMatrix 4X2K format. Microarray targets were prepared by reverse transcription of total RNA into fluorescently labeled cDNA. All samples were hybridized in duplicate, except samples 212 and 310 (hybridized in triplicate) and samples 336, 339, 50, 152, 157, and 199 (hybridized once). Sample location codes: number shows distance from the coast in km; CR, Columbia River transect in the plume and coastal ocean; NH, Newport Hydroline transect in the coastal ocean at Newport, Oregon; AST and HAM, Columbia River estuary locations near Astoria (river mile 7-9) and Hammond (river mile 5), respectively; TID, Columbia River estuary locations in the tidal basin (river mile 22-23); BA, river location at Beaver Army Dock (river mile 53) near Quincy, Oregon; UP, river location at mile 74.
2010-09-10 | E-GEOD-18303 | biostudies-arrayexpress
Project description:Analysis of microbial gene expression in response to physical and chemical gradients forming in the Columbia River, estuary, plume and coastal ocean was done in the context of the environmental data base. Gene expression was analyzed for 2,234 individual genes that were selected from fully sequenced genomes of 246 prokaryotic species (bacteria and archaea) as related to the nitrogen metabolism and carbon fixation. Seasonal molecular portraits of differential gene expression in prokaryotic communities during river-to-ocean transition were created using freshwater baseline samples (268, 270, 347, 002, 006, 207, 212).
2010-09-10 | GSE18303 | GEO
Project description:Bacterioplankton communities are deeply diverse and highly variable across space and time, but several recent studies demonstrate repeatable and predictable patterns in this diversity. We expanded on previous studies by determining patterns of variability in both individual taxa and bacterial communities across coastal environmental gradients. We surveyed bacterioplankton diversity across the Columbia River coastal margin, USA, using amplicon pyrosequencing of 16S rRNA genes from 596 water samples collected from 2007 to 2010. Our results showed seasonal shifts and annual reassembly of bacterioplankton communities in the freshwater-influenced Columbia River, estuary, and plume, and identified indicator taxa, including species from freshwater SAR11, Oceanospirillales, and Flavobacteria groups, that characterize the changing seasonal conditions in these environments. In the river and estuary, Actinobacteria and Betaproteobacteria indicator taxa correlated strongly with seasonal fluctuations in particulate organic carbon (ρ=-0.664) and residence time (ρ=0.512), respectively. In contrast, seasonal change in communities was not detected in the coastal ocean and varied more with the spatial variability of environmental factors including temperature and dissolved oxygen. Indicator taxa of coastal ocean environments included SAR406 and SUP05 taxa from the deep ocean, and Prochlorococcus and SAR11 taxa from the upper water column. We found that in the Columbia River coastal margin, freshwater-influenced environments were consistent and predictable, whereas coastal ocean community variability was difficult to interpret due to complex physical conditions. This study moves beyond beta-diversity patterns to focus on the occurrence of specific taxa and lends insight into the potential ecological roles these taxa have in coastal ocean environments.
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Project description:Through their metabolic activities, microbial populations mediate the impact of high gradient regions on ecological function and productivity of the highly dynamic Columbia River coastal margin (CRCM). A 2226-probe oligonucleotide DNA microarray was developed to investigate expression patterns for microbial genes involved in nitrogen and carbon metabolism in the CRCM. Initial experiments with the environmental microarrays were directed toward validation of the platform and yielded high reproducibility in multiple tests. Bioinformatic and experimental validation also indicated that >85% of the microarray probes were specific for their corresponding target genes and for a few homologs within the same microbial family. The validated probe set was used to query gene expression responses by microbial assemblages to environmental variability. Sixty-four samples from the river, estuary, plume, and adjacent ocean were collected in different seasons and analyzed to correlate the measured variability in chemical, physical and biological water parameters to differences in global gene expression profiles. The method produced robust seasonal profiles corresponding to pre-freshet spring (April) and late summer (August). Overall relative gene expression was high in both seasons and was consistent with high microbial abundance measured by total RNA, heterotrophic bacterial production, and chlorophyll a. Both seasonal patterns involved large numbers of genes that were highly expressed relative to background, yet each produced very different gene expression profiles. April patterns revealed high differential gene expression in the coastal margin samples (estuary, plume and adjacent ocean) relative to freshwater, while little differential gene expression was observed along the river-to-ocean transition in August. Microbial gene expression profiles appeared to relate, in part, to seasonal differences in nutrient availability and potential resource competition. Furthermore, our results suggest that highly-active particle-attached microbiota in the Columbia River water column may perform dissimilatory nitrate reduction (both dentrification and DNRA) within anoxic particle microniches.
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Project description:Glioblastoma (GBM) remains an untreatable disease. Understanding of GBM’s infiltrative biology at the resection margin is limited, despite causing disease recurrence and progression. To address this, we generated a high-throughput single-nucleus (sn)RNA-seq and snATAC-seq multi-omic dataset from six tumors with distinct genomic drivers and combined it with spatial transcriptomics to characterize the unique molecular phenotype of GBM near the margin. By contrasting GBM-specific biology in matching “Core” vs. “Margin” dissections, we define unique, shared “GBM infiltration” and chromatin accessibility signatures near the margin. We prioritize EGFR as a top differentially expressed and accessible “Margin” marker across GBM subtypes, show its dynamic expression along a core-to-margin infiltration trajectory, and validate its role in migration through CRISPR/Cas9 deletion in two patient-derived models. ChIP-seq studies furthermore corroborate preferential TEAD1 binding at EGFR’s accessible regulatory elements. This validated multi-omic dataset enables further studies into tumor and microenvironment biology in the context of residual GBM disease.
2025-07-14 | GSE286413 | GEO
Project description:Glioblastoma (GBM) remains an untreatable disease. Understanding of GBM’s infiltrative biology at the resection margin is limited, despite causing disease recurrence and progression. To address this, we generated a high-throughput single-nucleus (sn)RNA-seq and snATAC-seq multi-omic dataset from six tumors with distinct genomic drivers and combined it with spatial transcriptomics to characterize the unique molecular phenotype of GBM near the margin. By contrasting GBM-specific biology in matching “Core” vs. “Margin” dissections, we define unique, shared “GBM infiltration” and chromatin accessibility signatures near the margin. We prioritize EGFR as a top differentially expressed and accessible “Margin” marker across GBM subtypes, show its dynamic expression along a core-to-margin infiltration trajectory, and validate its role in migration through CRISPR/Cas9 deletion in two patient-derived models. ChIP-seq studies furthermore corroborate preferential TEAD1 binding at EGFR’s accessible regulatory elements. This validated multi-omic dataset enables further studies into tumor and microenvironment biology in the context of residual GBM disease.
2025-07-14 | GSE286419 | GEO
Project description:Glioblastoma (GBM) remains an untreatable disease. Understanding of GBM’s infiltrative biology at the resection margin is limited, despite causing disease recurrence and progression. To address this, we generated a high-throughput single-nucleus (sn)RNA-seq and snATAC-seq multi-omic dataset from six tumors with distinct genomic drivers and combined it with spatial transcriptomics to characterize the unique molecular phenotype of GBM near the margin. By contrasting GBM-specific biology in matching “Core” vs. “Margin” dissections, we define unique, shared “GBM infiltration” and chromatin accessibility signatures near the margin. We prioritize EGFR as a top differentially expressed and accessible “Margin” marker across GBM subtypes, show its dynamic expression along a core-to-margin infiltration trajectory, and validate its role in migration through CRISPR/Cas9 deletion in two patient-derived models. ChIP-seq studies furthermore corroborate preferential TEAD1 binding at EGFR’s accessible regulatory elements. This validated multi-omic dataset enables further studies into tumor and microenvironment biology in the context of residual GBM disease.
2025-07-14 | GSE286415 | GEO
Project description:The abundance of bacterial (AOB) and archaeal (AOA) ammonia oxidisers, assessed using quantitative PCR measurements of their respective a-subunit of the ammonia monooxygenase (amoA) genes, and ammonia oxidation rates were measured in four contrasting coastal sediments in the Western English Channel. Sediment was sampled bimonthly from July 2008 to May 2011, and measurements of ammonia oxidiser abundance and activity compared to a range of environmental variables including salinity, temperature, water column nutrients and sediment carbon and nitrogen content. Despite a higher abundance of AOA amoA genes within all sediments, and at all time-points, rates of ammonia oxidation correlated with AOB and not AOA amoA gene abundance. Other than ammonia oxidation rate, sediment particle size was the only variable that correlated with the spatial and temporal patterns of AOB amoA gene abundance, implying a preference of the AOB for larger sediment particles. This is possibly due to deeper oxygen penetration into the sandier sediments, increasing the area available for ammonia oxidation to occur, higher concentrations of inhibitory sulphide with pore waters of muddier sediments or a combination of both oxygen and sulphide concentrations. Similar to many other temporal studies of nitrification within estuarine and coastal sediments, decreases in AOB amoA gene abundance were evident during summer and autumn, with maximum abundance and ammonia oxidation rates occurring in winter and early spring. The lack of correlation between AOA amoA gene abundance and ammonium oxidation rate suggests an alternative role for amoA-carrying AOA within these sediments.
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