Dataset Information

Soil metagenome datasets underneath the Arecibo Observatory reflector dish.

ABSTRACT: The Arecibo Observatory (AO) located in Arecibo, Puerto Rico, is the most sensitive, powerful and active planetary radar system in the world [1]. One of its principal components is the 305 m-diameter spherical reflector dish (AORD), which is exposed to high frequency electromagnetic waves. To unravel the microbial communities that inhabit this environment, soil samples from underneath the AORD were collected, DNA extracted, and sequenced using Illumina MiSeq. Taxonomic and functional profiles were generated using the MG-RAST server. The most abundant domain was Bacteria (91%), followed by Virus (8%), Archaea (0.9%) and Eukaryota (0.9%). The most abundant phylum was Proteobacteria (54%), followed by Actinobacteria (8%), Bacteroidetes (5%) and Firmicutes (4%). In terms of functions, the most abundant among the metagenome corresponded to phages, transposable elements and plasmids (16%), followed by clustering-based subsystems (11%), carbohydrates (10%), and amino acids and derivatives (9%). This is the first soil metagenomic dataset from dish antennas and radar systems, specifically, underneath the AORD. Data can be used to explore the effect of high frequency electromagnetic waves in soil microbial composition, as well as the possibility of finding bioprospects with potential biomedical and biotechnological applications.

SUBMITTER: Rodriguez-Reyes MG

PROVIDER: S-EPMC6920479 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Soil metagenome datasets underneath the Arecibo Observatory reflector dish.

Rodriguez-Reyes Miguel G MG Rios-Velazquez Carlos C

Data in brief 20191024

The Arecibo Observatory (AO) located in Arecibo, Puerto Rico, is the most sensitive, powerful and active planetary radar system in the world [1]. One of its principal components is the 305 m-diameter spherical reflector dish (AORD), which is exposed to high frequency electromagnetic waves. To unravel the microbial communities that inhabit this environment, soil samples from underneath the AORD were collected, DNA extracted, and sequenced using Illumina MiSeq. Taxonomic and functional profiles we ...[more]

PMID: 31886328

Similar Datasets

Project description:IntroductionWhole-metagenome sequencing can be a rich source of information about the structure and function of entire metagenomic communities, but getting accurate and reliable results from these datasets can be challenging. Analysis of these datasets is founded on the mapping of sequencing reads onto known genomic regions from known organisms, but short reads will often map equally well to multiple regions, and to multiple reference organisms. Assembling metagenomic datasets prior to mapping can generate much longer and more precisely mappable sequences but the presence of closely related organisms and highly conserved regions makes metagenomic assembly challenging, and some regions of particular interest can assemble poorly. One solution to these problems is to use specialised tools, such as Kelpie, that can accurately extract and assemble full-length sequences for defined genomic regions from whole-metagenome datasets.MethodsKelpie is a kMer-based tool that generates full-length amplicon-like sequences from whole-metagenome datasets. It takes a pair of primer sequences and a set of metagenomic reads, and uses a combination of kMer filtering, error correction and assembly techniques to construct sets of full-length inter-primer sequences.ResultsThe effectiveness of Kelpie is demonstrated here through the extraction and assembly of full-length ribosomal marker gene regions, as this allows comparisons with conventional amplicon sequencing and published metagenomic benchmarks. The results show that the Kelpie-generated sequences and community profiles closely match those produced by amplicon sequencing, down to low abundance levels, and running Kelpie on the synthetic CAMI metagenomic benchmarking datasets shows similar high levels of both precision and recall.ConclusionsKelpie can be thought of as being somewhat like an in-silico PCR tool, taking a primer pair and producing the resulting 'amplicons' from a whole-metagenome dataset. Marker regions from the 16S rRNA gene were used here as an example because this allowed the overall accuracy of Kelpie to be evaluated through comparisons with other datasets, approaches and benchmarks. Kelpie is not limited to this application though, and can be used to extract and assemble any genomic region present in a whole metagenome dataset, as long as it is bound by a pairs of highly conserved primer sequences.

Dataset Information

Soil metagenome datasets underneath the Arecibo Observatory reflector dish.

Publications

Soil metagenome datasets underneath the Arecibo Observatory reflector dish.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets