| Contributors | Affiliation | Role |
|---|---|---|
| Orellana, Monica V. | Institute for Systems Biology (ISB) | Principal Investigator |
| Baliga, Nitin | Institute for Systems Biology (ISB) | Co-Principal Investigator |
| Ashworth, Justin | Institute for Systems Biology (ISB) | Contact |
| Rauch, Shannon | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
Microarrays for Thalassiosira pseudonana diatoms grown in the laboratory under different conditions including
diel cycles and elevated CO2 levels.
Data from Ashworth et al. (2013) Proc. Natl. Acad. Sci. USA 110(18):7518-23 are publicly available on the NCBI GEO database under the accession code: GSE45252.
Data were submitted to the NCBI GEO database on May 16, 2014 under the accession code: GSE57737 and will be made publicly available upon publication of an accompanying manuscript in preparation.
References:
Ashworth J, Coesel S, Lee A, Armbrust EV, Orellana MO*, Baliga NS*. (2013) Genome-wide diel growth state transitions in the diatom Thalassiosira pseudonana. Proc. Natl. Acad. Sci. 110(18):7518-23. doi:10.1073/pnas.1300962110
Transcriptomic profiling of the diatom Thalassiosira pseudonana at normal and elevlated CO2 levels and at normal and elevated light levels. Common reference total RNA (Agilent Quick-Amp Cy3-labeled) was used in all arrays as an internal standard. Triplicate batch cultures grown at normal (~400 ppm) and elevated (~800 ppm) CO2 levels, both at i) normal or ii) elevated light levels. Samples were taken during a) exponential and b) stationary growth during all growth experiments.
Result: 48 total transcriptomic measurements: [3 parallel replicates] x [400 ppm, 800 ppm] x [normal light, high
light] x [exponential, stationary] x [2 serial replicates].
Array slides were scanned using an Agilent slide scanner. Data were processed from Agilent files using the limma package in R, including background correction, loess (within-array) and 'Aquantile' (between-array) normalization.
| File |
|---|
Thaps_microarrays.csv (Comma Separated Values (.csv), 406 bytes) MD5:af4f83e8407394ca48fd0449c525f9d7 Primary data file for dataset ID 546404 |
| Parameter | Description | Units |
| taxon | Taxon/species of study. | text |
| publication | Publication where the details of the study can be found. Ashworth_et_al_2013 = Ashworth J, Coesel S, Lee A, Armbrust EV, Orellana MO*, Baliga NS*. (2013) Genome-wide diel growth state transitions in the diatom Thalassiosira pseudonana. Proc. Natl. Acad. Sci. 110(18):7518-23. doi:10.1073/pnas.1300962110 | text |
| GEO_accession | Accession number and hyperlink to the NCBI GEO database. | alphanumeric |
| Website | |
| Platform | Institute for Systems Biology |
| Start Date | 2013-07-01 |
| End Date | 2013-07-01 |
Description from the NSF award abstract:
Diatoms account for approximately 40 percent of primary production in the world's oceans and are the most productive marine phytoplankton group. They form the basis of food webs in coastal and ocean upwelling areas that support important fisheries and have a major role in global carbon and silicon cycles. The goal of this project is to understand the impact of ocean acidification, in combination with other stressors, on the marine diatom Thalassiosira pseudonana. This project will generate a predictive model of expression of all genes of this diatom that can be used to forecast the diatom's response to projected environmental scenarios to an acidifying ocean. A combination of laboratory and field studies will be used; diatoms will be grown under carbon dioxide concentrations that reflect today's values as well as future predicted conditions and light levels and nutrients concentrations will also be varied. Physiological and gene expression responses will be measured and integrated using computational and modeling methods to gain an unbiased, systems-level understanding of the response of diatoms to ocean acidification. This combined approach will enable the forecasting and prediction of the diatom's response to environmental change and the elucidation and genomic interpretation of biochemically relevant processes in natural environment.
NSF Climate Research Investment (CRI) activities that were initiated in 2010 are now included under Science, Engineering and Education for Sustainability NSF-Wide Investment (SEES). SEES is a portfolio of activities that highlights NSF's unique role in helping society address the challenge(s) of achieving sustainability. Detailed information about the SEES program is available from NSF (https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=504707).
In recognition of the need for basic research concerning the nature, extent and impact of ocean acidification on oceanic environments in the past, present and future, the goal of the SEES: OA program is to understand (a) the chemistry and physical chemistry of ocean acidification; (b) how ocean acidification interacts with processes at the organismal level; and (c) how the earth system history informs our understanding of the effects of ocean acidification on the present day and future ocean.
Solicitations issued under this program:
NSF 10-530, FY 2010-FY2011
NSF 12-500, FY 2012
NSF 12-600, FY 2013
NSF 13-586, FY 2014
NSF 13-586 was the final solicitation that will be released for this program.
PI Meetings:
1st U.S. Ocean Acidification PI Meeting(March 22-24, 2011, Woods Hole, MA)
2nd U.S. Ocean Acidification PI Meeting(Sept. 18-20, 2013, Washington, DC)
3rd U.S. Ocean Acidification PI Meeting (June 9-11, 2015, Woods Hole, MA – Tentative)
NSF media releases for the Ocean Acidification Program:
Press Release 10-186 NSF Awards Grants to Study Effects of Ocean Acidification
Discovery Blue Mussels "Hang On" Along Rocky Shores: For How Long?
Press Release 13-102 World Oceans Month Brings Mixed News for Oysters
| Funding Source | Award |
|---|---|
| NSF Emerging Frontiers Division (NSF EF) |