| Contributors | Affiliation | Role |
|---|---|---|
| Stepanauskas, Ramunas | Bigelow Laboratory for Ocean Sciences | Principal Investigator |
| Copley, Nancy | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
Some of the accessions are not yet available [2017-10-27]. A free login account is required to access some of the pages at IMG, in particular, those located at img.jgi.doe.gov/cgi-bin/mer/.
Publications using this dataset:
Pachiadaki MG, Sintes E, Bergauer K, Brown JM, Record NR, Swan BK, Mathyer ME, Hallam SJ, Lopez-Garcia P, Takaki Y, Nunoura T, Woyke T, Herndl GJ, Stepanauskas R (2017). Major role of nitrite-oxidizing bacteria in dark ocean carbon fixation. Science 358 (6366): 1046-1051.
Bergauer K, Fernandez-Guerra A, Garcia JA, Sprenger RR, Stepanauskas R, Pachiadaki MG, Jensen ON, Herndl GJ (2017). Organic matter processing by microbial communities throughout the Atlantic water column as revealed by metaproteomics. PNAS doi: 10.1073/pnas.1708779115.
Samples were collected by collaborators, cryopreserved and shipped frozen to Bigelow Laboratory Single Cell Genomics Facility Center (SCGC). Cells were sorted, identified and sequenced by the SCGC, following SCGC’s standard practices: https://scgc.bigelow.org/PDFs/SCGC_Services_Description.pdf
On average, at least 5 million 2x150 bp or longer paired-end reads were generated per SAG using in-house MiSeq and with a NextSeq (Illumina) instruments. The obtained reads are were pre-processed and, de novo assembled, and quality-controlled using algorithms SCGC's standard protocols that are optimized for single cell MDA products . A combination of tetramer homogeneity tests and blast searches against reference databases is were used to detect potential DNA contaminants among the assembled contigs. Benchmark data demonstrating SCGC SAG WGS whole genome sequencing pipeline performance are available here: from the SCGC website: http://data.bigelow.org/~scgc/WGS_benchmark_data/.
Genome annotation was performed through IMG (http://img-stage.jgi-psf.org/cgi-bin/submit/main.cgi).
Further information on Bigelow Laboratory Single Cell Genomics Center (SCGC) Facilities (pdf)
Relevant References:
In preparation:
In review:
Published:
BCO-DMO Processing Notes:
- added conventional header with dataset name, PI name, version date
- modified parameter names to conform with BCO-DMO naming conventions
- replaced spaces with underscores
| File |
|---|
taxon_table_SAG.csv (Comma Separated Values (.csv), 75.04 KB) MD5:37da1229f48e2aaa4d13c242129dbd40 Primary data file for dataset ID 666274 |
| Parameter | Description | Units |
| SAG | Single amplified genome identifier | unitless |
| IMG_Genome_ID | Accession number from IMG/M (Integrated Microbial Genomes and Microbiome Samples) | unitless |
| date_collection | sample collection date; formatted as yyyy-mm-dd | unitless |
| site_collection_growth_cond | Collection or isolation site; or growth conditions | unitless |
| depth | Collection depth | meters |
| lat | Latitude; north is positive | decimal degrees |
| lon | Longitude; east is positive | decimal degrees |
| Assembled_Genome_Size | Assembled genome size | base pairs |
| Gene_Count | Gene count | genes |
| Scaffold_Count | Scaffold count | scaffolds |
| Availability | Availability: whether the accession is public or date when release is expected | unitless |
| IMG_accession_link | Link to IMG accession page | unitless |
| Dataset-specific Instrument Name | MiSeq and NextSeq 500 (Illumina) |
| Generic Instrument Name | Automated DNA Sequencer |
| Dataset-specific Description | Used to read base pairs |
| Generic Instrument 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. |
| Dataset-specific Instrument Name | high-throughput plate reader (BMG) |
| Generic Instrument Name | plate reader |
| Generic Instrument Description | Plate readers (also known as microplate readers) are laboratory instruments designed to detect biological, chemical or physical events of samples in microtiter plates. They are widely used in research, drug discovery, bioassay validation, quality control and manufacturing processes in the pharmaceutical and biotechnological industry and academic organizations. Sample reactions can be assayed in 6-1536 well format microtiter plates. The most common microplate format used in academic research laboratories or clinical diagnostic laboratories is 96-well (8 by 12 matrix) with a typical reaction volume between 100 and 200 uL per well. Higher density microplates (384- or 1536-well microplates) are typically used for screening applications, when throughput (number of samples per day processed) and assay cost per sample become critical parameters, with a typical assay volume between 5 and 50 µL per well. Common detection modes for microplate assays are absorbance, fluorescence intensity, luminescence, time-resolved fluorescence, and fluorescence polarization. From: http://en.wikipedia.org/wiki/Plate_reader, 2014-09-0-23. |
| Dataset-specific Instrument Name | Roche LC480 |
| Generic Instrument Name | Thermal Cycler |
| Generic Instrument Description | A thermal cycler or "thermocycler" is a general term for a type of laboratory apparatus, commonly used for performing polymerase chain reaction (PCR), that is capable of repeatedly altering and maintaining specific temperatures for defined periods of time. The device has a thermal block with holes where tubes with the PCR reaction mixtures can be inserted. The cycler then raises and lowers the temperature of the block in discrete, pre-programmed steps. They can also be used to facilitate other temperature-sensitive reactions, including restriction enzyme digestion or rapid diagnostics.
(adapted from http://serc.carleton.edu/microbelife/research_methods/genomics/pcr.html) |
| Dataset-specific Instrument Name | Covaris focused ultrasonicator |
| Generic Instrument Name | ultrasonic cell disrupter (sonicator) |
| Generic Instrument Description | Instrument that applies sound energy to agitate particles in a sample. |
| Website | |
| Platform | lab Bigelow |
| Start Date | 2012-09-01 |
| End Date | 2016-08-31 |
| Description | genomics studies |
From NSF award abstract:
The dark ocean, defined as the water column below the photic, contains one of the largest microbial biomes on earth, composed of active and metabolically diverse microorganisms. These biota impact local processes and the global carbon cycling, e.g. by conducting a large fraction of marine organic matter remineralization. An increasing body of evidence suggests that chemoautotrophy in the dark ocean may also be significant, with potentially major implications to the dark ocean's microbial ecology and biogeochemistry. However, it remains largely unanswered what energy sources and metabolic pathways are used to support this microbial-driven dark carbon fixation and which microbial taxonomic groups possess chemoautotrophic metabolic pathways in the dark ocean.
The overall goal of this project is to obtain a comprehensive, global inventory of chemoautotrophs in the dark ocean through large-scale microbial single cell genomics, supplemented with metagenomic and metatranscriptomic sequencing. The investigators will address the following general hypotheses:
1. Multiple prokaryote taxonomic groups found in the dark ocean contain chemoautotrophic metabolic pathways.
2. Both known and previously unrecognized chemoautotrophy pathways are present in dark ocean's prokaryotes.
3. Dark ocean chemoautotrophs are broadly distributed around the globe, with biogeographic patterns determined by the isopycnal movement of water masses, water mass age, and the downward flux of organic matter.
4. Diverse chemoautotrophy pathways are expressed in the dark ocean.
During the course of the project, single amplified genomes (SAGs) will be generated from all major intermediate and deep water masses around the globe, representing all major taxonomic groups of bacteria and archaea that are known to be present in the dark ocean. These SAGs will be analyzed for specific chemoautotrophy-indicative genes. Whole genome sequencing will be performed on a subset of SAGs, enabling detailed annotation of chemoautotrophy pathways. Metagenomic and metatranscriptomic fragment recruitment will be used to determine global patterns of chemoautotroph distribution and chemoautotrophy pathway expression. This ambitious project is made possible by the recent development of techniques and facilities for high-throughput genomic DNA recovery from individual cells at Bigelow Laboratory, genomic sequencing support provided by the U.S. Department of Energy Joint Genome Institute, and the establishment of a broad network of collaborations among many leading dark ocean microbiologists.
The project will generate a large quantity of unique reference materials, laying a solid foundation for future studies of dark ocean microorganisms, including 207 microbial genomes, representing all major taxonomic groups of bacteria and archaea from the dark ocean, multiple metagenomes, metatranscriptomes and pyrotag data sets, as well as genomic DNA from ~2,000 individual cells from diverse prokaryote taxonomic groups, water masses and geographic locations. The work will improve our understanding of the global carbon cycle, with direct relevance to climate change studies.
Publications produced as a result of this research:
Swan BK, Tupper B, Sczyrba A, Lauro FM, Martinez-Garcia M, González JM, Luo H, Wright JJ, Landry ZC, Hanson NW, Thompson BP, Poulton NJ, Schwientek P, Acinas SG, Giovannoni SJ, Moran MA, Hallam SJ, Cavicchioli R, Woyke T, Stepanauskas, R. 2013. Prevalent genome streamlining and latitudinal divergence of marine planktonic bacteria in the surface ocean. PNAS, v.TBD, p. TBD, published online June 25, 2013. doi: 10.1073/pnas.1304246110
| Funding Source | Award |
|---|---|
| NSF Division of Ocean Sciences (NSF OCE) |