Marine metagenome
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1057731 | ENA |
REPOSITORIES: ENA
Similar Datasets
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
2008-02-08 | GSE10119 | GEO
Project description:Metagenome data from soil samples were collected at 0 to 10cm deep from 2 avocado orchards in Channybearup, Western Australia, in 2024. Amplicon sequence variant (ASV) tables were constructed based on the DADA2 pipeline with default parameters.
2025-06-15 | GSE298403 | GEO
Project description:Microbial Metagenome, Metatranscriptome & Phylogenetic Libraries
| PRJNA326482 | ENA
Project description:Qingdao coastal seawater metagenome sequencing
| PRJNA681633 | ENA
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
2008-02-08 | E-GEOD-10119 | biostudies-arrayexpress
Project description:Marine metagenome, Marine metatranscriptome Raw sequence reads
| PRJNA550987 | ENA
Project description:More than 99% of identified prokaryotes, including many from the marine environment, cannot be cultured in the laboratory. This lack of capability restricts our knowledge of microbial genetics and community ecology. Metagenomics, the culture-independent cloning of environmental DNAs that are isolated directly from an environmental sample, has already provided a wealth of information about the uncultured microbial world. It has also facilitated the discovery of novel biocatalysts by allowing researchers to probe directly into a huge diversity of enzymes within natural microbial communities. Recent advances in these studies have led to a great interest in recruiting microbial enzymes for the development of environmentally-friendly industry. Although the metagenomics approach has many limitations, it is expected to provide not only scientific insights but also economic benefits, especially in industry. This review highlights the importance of metagenomics in mining microbial lipases, as an example, by using high-throughput techniques. In addition, we discuss challenges in the metagenomics as an important part of bioinformatics analysis in big data.
| S-EPMC4678775 | biostudies-literature