Transcriptome statistics from samples obtained on LMG1411 collected on the Gould (LMG1411) in the Western Antarctica Peninsula in 2014. (Polar Transcriptomes project)

Data Type: experimental
Version: 1
Version Date: 2016-11-18

» Iron and Light Limitation in Ecologically Important Polar Diatoms: Comparative Transcriptomics and Development of Molecular Indicators (Polar_Transcriptomes)
Marchetti, AdrianUniversity of North Carolina at Chapel Hill (UNC-Chapel Hill)Principal Investigator, Contact
Ake, HannahWoods Hole Oceanographic Institution (WHOI BCO-DMO)BCO-DMO Data Manager

Transcriptome statistics from samples obtained on LMG1411 collected on the Gould (LMG1411) in the Western Antarctica Peninsula in 2014. (Polar Transcriptomes project)

Dataset Description

Transcriptome statistics from samples obtained on LMG1411.

Diatom isolates were obtained from the Western Antarctic Peninsula surface waters.

Methods & Sampling

Nine species of diatoms were isolated from the Western Antarctic Peninsula along the PalmerLTER sampling grid in 2013 and 2014. Isolations were performed using an Olympus CKX41 inverted microscope by single cell isolation with a micropipette (Anderson 2005). Diatom species were identified by morphological characterization and 18S rRNA gene (rDNA) sequencing. DNA was extracted with the DNeasy Plant Mini Kit according to the manufacturer’s protocols (Qiagen). Amplification of the nuclear 18S rDNA region was achieved with standard PCR protocols using eukaryotic-specific, universal 18S forward and reverse primers. Primer sequences were obtained from Medlin et al. (1982). The length of the region amplified is approximately 1800 base pairs (bp). Pseudo-nitzschia species are often difficult to identify by their 18S rDNA sequence, therefore, additional support of the taxonomic identification of P. subcurvata was provided through sequencing of the 18S-ITS1-5.8S regions. Amplification of this region was performed with the 18SF-euk and 5.8SR_euk primers of Hubbard et al. (2008). PCR products were purified using either QIAquick PCR Purification Kit (Qiagen) or ExoSAP-IT (Affymetrix) and sequenced by Sanger DNA sequencing (Genewiz). Sequences were edited using Geneious Pro software (, Kearse et al., 2012) and BLASTn sequence homology searches were performed against the NCBI nucleotide non-redundant (nr) database to determine species with a cutoff identity of 98%.

Diatom phylogenetic analysis was performed with Geneious Pro and included 71 additional diatom 18S rDNA sequences from publically available genomes and transcriptomes, including those in the MMETSP database. Diatom sequences were trimmed to the same length and aligned with MUSCLE (Edgar 2004). A phylogenetic tree was created in Mega with the Maximum-likelihood method of tree reconstruction, the Jukes-Cantor genetic distance model (Jukes and Cantor 1969), and 100 bootstrap replicates.

Illumina TruSeq adapters and poly-A tails were trimmed from raw reads using the Fastx_toolkit clipper function. Fastq_quality_filter was used to remove poor quality sequences, such that remaining sequences had a minimum quality score of 20 with a minimum of 80% of bases within a read meeting this quality score requirement. Any remaining raw sequences less than 50 base pairs in length were also removed. Merged files were assembled de novo using Trinity (Grabherr et al. 2011). The resulting assembly was filtered to remove contigs less than 200 bp in length. Trinity-assembled contigs which exhibited sequence overlap were grouped into isogroups which were then used for sequence homology searches (BLASTx E-value ≤ 10-4) against the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases (Kanehisa 2006).

BUSCO (Benchmarking Universal Single-Copy Orthologs) was used to assess the completeness of genomes and transcriptomes based on sets of single copy orthologous groups derived from OrthoDB that are highly conserved within multiple lineages (Felipe et al. 2015). Completed, duplicated and fragmented orthologs were determined by meeting an ‘expected score’ and having aligned sequences within two standard deviations of the BUSCO gene’s length. A second metric of completeness was performed by evaluating conserved pathways, such as the ribosome and spliceosome, using the single-directional best-hit method in the KEGG Automatic Annotation Server (KAAS) (Moriya et al. 2007). Finally contiguity, was calculated at the 0.75 level as according to Martin and Wang (2011) with custom scripts.

For each transcriptome, unassembled sequence reads were aligned to the final Trinity assembly using Bowtie 2 (Langmead 2012). Mapped reads were normalized by the Reads per Kilobase per Million reads method (RPKM) (Mortazavi et al. 2008).

Gene biogeographical distributions - 20 genes of interest were selected in the study to investigate the molecular basis of iron and light limitation in polar diatoms. Reference sequences for each of these genes were obtained from the F. cylindrus and P. tricornutum JGI genome portals and T. pseudonana and T. oceanica NCBI and GenBank repositories. Reference sequences were identified in the transcriptomes by translated nucleotide homology searches (tBLASTn) with an e-value cutoff of <10-5. A reciprocal tBLASTn homology search was performed for each transcriptome against the KEGG GENES database, using the single-directional best-hit method in the KAAS online tool to ensure consistent gene annotations (Moriya et al. 2007).

Subsequently, reference sequences were identified in the MMETSP protein database by BLASTp (e-value <10-5) homology searches among the diatom transcriptomes. The transcriptomes and their associated latitude and longitude were obtained from iMicrobe Data Commons (Project Code CAM_P_0001000) and the National Center for Marine Algae and Microbiota (NCMA). Custom Matlab scripts allowed global biogeographical distribution of key genes of interest to be mapped.

Data Processing Description

BCO-DMO Data Processing Notes:

-reformatted column names to comply with BCO-DMO standards
-replaced spaces with underscores
-added names to columns that were unnamed

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Data Files

(Comma Separated Values (.csv), 901 bytes)
Primary data file for dataset ID 665311

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speciesSpecies analyzed unitless
raw_sequence_readsTotal number of raw sequence reads per species count
contigs_numNumber of contigs per species. count
isogroups_numNumber of isogroups per species. count
transcriptome_sizeTranscriptome size by species. Megabase
mean_contig_lengthAverage contig length by species. base pair
max_contig_lengthMaximum contig length by species. base pair
min_contig_lengthMinimum contig length by species. base pair
contiguityContiguity threshold 0.75 unitless
BUSCO_pcntCompleteness of genome based on 429 core eukaryotic genes percent
spliceosome_pcntSpliceosome KAAS pathway completeness percent
ribosome_pcntRibosome KAAS pathway completeness percent
KEGGKEGG value; Functionally annotated contigs count
N50N50 value; N50 length is defined as the shortest sequence length at 50% of the genome unitless

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Dataset-specific Instrument Name
Agilent Bioanalyzer 2100
Generic Instrument Name
Dataset-specific Description
Used to determine RNA integrity
Generic Instrument Description
A Bioanalyzer is a laboratory instrument that provides the sizing and quantification of DNA, RNA, and proteins. One example is the Agilent Bioanalyzer 2100.

Dataset-specific Instrument Name
Olympus CKX41
Generic Instrument Name
Inverted Microscope
Dataset-specific Description
Used to perform isolations
Generic Instrument Description
An inverted microscope is a microscope with its light source and condenser on the top, above the stage pointing down, while the objectives and turret are below the stage pointing up. It was invented in 1850 by J. Lawrence Smith, a faculty member of Tulane University (then named the Medical College of Louisiana). Inverted microscopes are useful for observing living cells or organisms at the bottom of a large container (e.g. a tissue culture flask) under more natural conditions than on a glass slide, as is the case with a conventional microscope. Inverted microscopes are also used in micromanipulation applications where space above the specimen is required for manipulator mechanisms and the microtools they hold, and in metallurgical applications where polished samples can be placed on top of the stage and viewed from underneath using reflecting objectives. The stage on an inverted microscope is usually fixed, and focus is adjusted by moving the objective lens along a vertical axis to bring it closer to or further from the specimen. The focus mechanism typically has a dual concentric knob for coarse and fine adjustment. Depending on the size of the microscope, four to six objective lenses of different magnifications may be fitted to a rotating turret known as a nosepiece. These microscopes may also be fitted with accessories for fitting still and video cameras, fluorescence illumination, confocal scanning and many other applications.

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ARSV Laurence M. Gould
Start Date
End Date

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Project Information

Iron and Light Limitation in Ecologically Important Polar Diatoms: Comparative Transcriptomics and Development of Molecular Indicators (Polar_Transcriptomes)

Coverage: Antarctica

The Southern Ocean surrounding Antarctica is changing rapidly in response to Earth's warming climate. These changes will undoubtedly influence communities of primary producers (the organisms at the base of the food chain, particularly plant-like organisms using sunlight for energy) by altering conditions that influence their growth and composition. Because primary producers such as phytoplankton play an important role in global biogeochemical cycling, it is essential to understand how they will respond to changes in their environment. The growth of phytoplankton in certain regions of the Southern Ocean is constrained by steep gradients in chemical and physical properties that vary in both space and time. Light and iron have been identified as key variables influencing phytoplankton abundance and distribution within Antarctic waters. Microscopic algae known as diatoms are dominant members of the phytoplankton and sea ice communities, accounting for significant proportions of primary production. The overall objective of this project is to identify the molecular bases for the physiological responses of polar diatoms to varying light and iron conditions. The project should provide a means of evaluating the extent these factors regulate diatom growth and influence net community productivity in Antarctic waters. The project will also further the NSF goals of making scientific discoveries available to the general public and of training new generations of scientists. It will facilitate the teaching and learning of polar-related topics by translating the research objectives into readily accessible educational materials for middle-school students. This project will also provide funding to enable a graduate student and several undergraduate students to be trained in the techniques and perspectives of modern biology.

Although numerous studies have investigated how polar diatoms are affected by varying light and iron, the cellular mechanisms leading to their distinct physiological responses remain unknown. Using comparative transcriptomics, the expression patterns of key genes and metabolic pathways in several ecologically important polar diatoms recently isolated from Antarctic waters and grown under varying iron and irradiance conditions will be examined. In addition, molecular indicators for iron and light limitation will be developed within these polar diatoms through the identification of iron- and light-responsive genes -- the expression patterns of which can be used to determine their physiological status. Upon verification in laboratory cultures, these indicators will be utilized by way of metatranscriptomic sequencing to examine iron and light limitation in natural diatom assemblages collected along environmental gradients in Western Antarctic Peninsula waters. In order to fully understand the role phytoplankton play in Southern Ocean biogeochemical cycles, dependable methods that provide a means of elucidating the physiological status of phytoplankton at any given time and location are essential.

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Funding SourceAward
NSF Office of Polar Programs (formerly NSF PLR) (NSF OPP)

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