Dataset: Groundwater microorganism retroelement protein sequences

Name: Protein sequences from diversity-generating retroelements in groundwater microorganisms collected near Rifle, Colorado between 2011 and 2012 (Viruses in Methanotrophic Marine Ecosystems project)
Published: 2017-04-11
Keywords: oceans

Cite This Dataset

Spatial Extent: N:39.5291 E:-107.7721 S:39.5291 W:-107.7721

Project:

Dimensions: The Role of Viruses in Structuring Biodiversity in Methanotrophic Marine Ecosystems (Viruses in Methanotrophic Marine Ecosystems)

Program:

Dimensions of Biodiversity (Dimensions of Biodiversity)

Principal Investigator:

David L. Valentine (University of California-Santa Barbara, UCSB)

Student:

Blair Paul (University of California-Santa Barbara, UCSB-MSI)

Contact:

David L. Valentine (University of California-Santa Barbara, UCSB)

BCO-DMO Data Manager:

Amber D. York (Woods Hole Oceanographic Institution, WHOI BCO-DMO)

Version Date:

2017-04-11

Restricted:

Validated:

Current State:

Final no updates expected

Protein sequences from diversity-generating retroelements in groundwater microorganisms collected near Rifle, Colorado between 2011 and 2012 (Viruses in Methanotrophic Marine Ecosystems project)

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Description

This dataset includes links to diversity-generating retroelement sequences files in .fasta format. There are separate .fasta files for reverse transcriptase protein sequences and variable protein sequences. These sequences were derived from previously generated sequence accessions at the National Center for Biotechnology Information (NCBI). Original sampling took place near Rifle, Colorado between 2011 and 2012.

To access the .fasta files and the list of source sequences, click the "Get Data" button at the top of this page.

These data are published in the following journal article:
Paul, B.G., Burstein, D., Castelle, C.J., Handa, S., Arambula, D., Czornyj, E., Thomas, B.C., Ghosh, P., Miller, J.F., Banfield, J.F. and Valentine, D.L. (2017) Retroelement-guided protein diversification abounds in vast lineages of Bacteria and Archaea. Nature Microbiology, 2, p.17045. doi: 10.1038/nmicrobiol.2017.45

Methods & Sampling

A bioinformatic analysis of metagenome-assembled genomes to identify retroelements was performed. This study used data from several previously described sampling efforts (Brown et al. 2015, Castelle et al. 2015, and Anantharaman et al. 2016). Original sampling was conducted within an unconfined aquifer at the Rifle Integrated Field Research Challenge (IFRC) site, which is adjacent to the Colorado River, near Rifle, Colorado, USA (39.5291, -107.7721). Samples were collected between August 25th to December 12th of 2011, and August 2nd to December 12th of 2012. Sequencing of these samples took place at the Joint Genome Institute using the Illumina HiSeq 2000 platform to generate 2 × 150 paired-end reads.

For more information about sampling methodology see Paul et al. 2017.

Data Processing Description

These sequences were processed using Python v2.7.12, and Geneious v8.1.4.

Data Files

File
retroelement_seq.csv (Comma Separated Values (.csv), 901 bytes) MD5:6544cead21a1b7f2f8ab4ee1c2e6ce02 Primary data file for dataset ID 687822

More Information about this dataset

Funding Sources

Funding Source	Award Number
NSF Division of Ocean Sciences	OCE-1046144

Deployments

Deployment	Synonyms	Start Date	Platform	Investigator
Valentine_IFRC_site			Colorado_River	David L. Valentine (Principal Investigator)	data info

Instruments

Automated DNA Sequencer

Supplied Name: Illumina HiSeq 2000

Supplied Description:

Instrument Type

Generic Name: Automated DNA Sequencer

Acronym: Automated Sequencer

Generic Description:

General term for a laboratory instrument used for deciphering the order of bases in a strand of DNA. Sanger sequencers detect fluorescence from different dyes that are used to identify the A, C, G, and T extension reactions. Contemporary or Pyrosequencer methods are based on detecting the activity of DNA polymerase (a DNA synthesizing enzyme) with another chemoluminescent enzyme. Essentially, the method allows sequencing of a single strand of DNA by synthesizing the complementary strand along it, one base pair at a time, and detecting which base was actually added at each step.

Parameters

Date and time formats are described in python strftime() syntax.

Supplied Name	Supplied description	Supplied Units	Standard Name
file_name	Filename	unitless	file_name
description	File description	unitless	brief_desc
file_link	Link to download the data file	unitless	file_link

Status message

Database

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Dataset: Groundwater microorganism retroelement protein sequences