This metadata record was created in error and a DOI assigned to it before the error was noticed. The correct metadata record is available here: https://data.aad.gov.au/metadata/records/AAS_4015_Krill_Gonad_Transcriptome with the DOI doi:10.26179/5cd3c8fec9ad8.

This metadata record contains an Excel spreadsheet with Operational Taxonomic Units (OTUs) gained from Eukaryotic 18S rDNA PCR amplification and high-throughput sequencing of samples from Biofilm slides deployed as part of the antFOCE experiment in the austral summer of 2014/15 at Casey station, East Antarctica. Refer to antFOCE report section 4.5.3 for deployment, sampling and analysis details. https://data.aad.gov.au/metadata/records/AAS_4127_antFOCE_Project4127 Sampling design 2 trays of 8 horizontal standard glass microscope slides (72 x 25 mm) per chamber. Four of the glass slides were scored with a diamond pencil approximately 18 mm from the right hand end of the slide and deployed scored side up. The remaining four slides were unmodified. Slides were sampled at: - Tmid - one tray per chamber / open plot. The sampled try was repopulated with fresh slides and redeployed - Tend – 2 slides trays per chamber / open plot. Sampling procedure After 31 days deployment, 1 slide tray per chamber / open plot was sampled. At Tend both trays in each chamber / open plot were sampled. To minimize disturbance while being raised to the surface, each tray was removed from the tray holder by divers and placed in a seawater filled container with a lid. On the surface, slides were removed from the tray using ethanol sterilized forceps. The four unscoured slides per chamber / open plot were placed in a plastic microscope slide holder with a sealable lid. The scoured slides were placed individually in 70 ml plastic sample jars. Lab procedure - Casey The slide holder (4 unscoured slides) from each chamber / open plot was frozen at -20C immediately upon return to the lab. The scoured slides were preserved in sea water containing 1% final concentration glutaraldehyde in separate jars. Preservation Issue: Scoured slides were not refrigerated, either at Casey, during RTA or in Kingston before the 26th Nov 2015, when they were transferred to the 4C Cold Store. antFOCE Background The antFOCE experimental system was deployed in O’Brien Bay, approximately 5 kilometres south of Casey station, East Antarctica, in the austral summer of 2014/15. Surface and sub-surface (in water below the sea ice) infrastructure allowed controlled manipulation of seawater pH levels (reduced by 0.4 pH units below ambient) in 2 chambers placed on the sea floor over natural benthic communities. Two control chambers (no pH manipulation) and two open plots (no chambers, no pH manipulation) were also sampled to compare to the pH manipulated (acidified) treatment chambers. Details of the antFOCE experiment can be found in the report – "antFOCE 2014/15 – Experimental System, Deployment, Sampling and Analysis". This report and a diagram indicating how the various antFOCE data sets relate to each other are available at: https://data.aad.gov.au/metadata/records/AAS_4127_antFOCE_Project4127 AntFOCE biofilm DNA methods Laurence Clarke, Shane Powell, Bruce Deagle DNA extraction The biofilm was removed from the top of each slide with a cotton swab and DNA extracted directly from the swab using the MoBio PowerBiofilm DNA isolation kit following the manufacturer’s protocol. Extraction blanks were extracted in parallel to detect contamination. Eukaryotic 18S rDNA PCR amplification and high-throughput sequencing DNA extracts were PCR-amplified in triplicate with primers designed to amplify 140-170 bp of eukaryotic 18S ribosomal DNA (Jarman et al. 2013). The forward primer was modified to improve amplification of protists. Table 1. First and second round primers, including MID tags (Xs). ILF_ProSSU3'F_X TCGTCGGCAGCGTCAGATGTGTATAAGAGACAG XXXXXX CACCGCCCGTCGCWMCTACCG ILR_SSU3'R_Y GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG XXXXXX GGTTCACCTACGGAAACCTTGTTACG msqFX AATGATACGGCGACCACCGAGATCTACAC XXXXXXXXXX TCGTCGGCAGCGTCAGATGTGTATAAGAGACAG msqRY CAAGCAGAAGACGGCATACGAGAT XXXXXXXXXX GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG PCR amplifications were performed in two rounds, the first to amplify the 18S region and add sample-specific multiplex-identifier (MID) tags and Illumina sequencing primers, the second to add the P5 and P7 sequencing adapters and additional MIDs. Each reaction mix for the first PCR contained 0.1 µM each of forward and reverse primer, 0.2 µg/µL BSA, 0.2 U Phusion DNA polymerase in 1 x Phusion Master Mix (New England Biolabs, Ipswich, MA, USA) and 1 micro L DNA extract in a total reaction volume of 10 micro L. PCR thermal cycling conditions were initial denaturation at 98 degrees C for 30 secs, followed by 25 cycles of 98 degrees C for 5 secs, 67 degrees C for 20 secs and 72 degrees C for 20 secs, with a final extension at 72 degrees C for 5 min. Replicate PCR products were pooled then diluted 1:10 and Illumina sequencing adapters added in a second round of PCR using the same reaction mix and thermal cycling conditions as the first round, except the concentration of BSA was halved (0.1 micro g/micro L), and the number of cycles was reduced to 10 with an annealing temperature of 55 degrees C. Products from each round of PCR were visualized on 2% agarose gels. Second round PCR products were pooled in equimolar ratios based on band intensity. The pooled products were purified using Agencourt AMPure XP beads (Beckman Coulter, Brea, CA, USA) and the concentration of the library measured using the Qubit dsDNA HS assay on a QUBIT 2.0 Fluorometer (Life Technologies, Carlsbad, CA, USA). The pool was diluted to 2 nM and paired-end reads generated on a MiSeq (Illumina, San Diego, CA, USA) with MiSeq Reagent Nano kit vs (300-cycles). Bacterial 16S rDNA PCR amplification and high-throughput sequencing Bioinformatics Reads were sorted by sample-specific MIDs added in the second round PCR using the MiSeq Reporter software. Fastq reads were merged using the -fastq_mergepairs command in USEARCH v8.0.1623 (Edgar 2010). Merged reads were sorted by "internal" 6 bp MID tags, and locus-specific primers trimmed with custom R scripts using the ShortRead package (Morgan et al. 2009), with only reads containing perfect matches to the expected MIDs and primers retained. Reads for all samples were dereplicated and global singletons discarded (-derep_fulllength -minuniquesize 2), and clustered into OTUs with the UPARSE algorithm (Edgar 2013) using the '-cluster_otus' command. Potentially chimeric reads were also discarded during this step. Reads for each sample were then assigned to OTUs (-usearch_global -id .97), and an OTU table generated using a custom R script. Taxonomy was assigned to each OTU using MEGAN version 5.10.5 (Huson et al. 2011) based on 50 hits per OTU generated by BLASTN searches against the NCBI 'nt' database (downloaded August 2015). Default LCA parameters were used, except Min support = 1, Min score = 100, Top percent = 10. Alpha and beta-diversity analyses were performed based on a rarefied OTU table with QIIME v1.8.0 (alpha_rarefaction.py, beta_diversity_through_plots.py, Caporaso et al. 2010). References Caporaso JG, Kuczynski J, Stombaugh J, et al. (2010) QIIME allows analysis of high-throughput community sequencing data. Nature Methods 7, 335-336. Huson DH, Mitra S, Ruscheweyh HJ, Weber N, Schuster SC (2011) Integrative analysis of environmental sequences using MEGAN4. Genome Research 21, 1552-1560. Jarman SN, McInnes JC, Faux C, et al. (2013) Adelie penguin population diet monitoring by analysis of food DNA in scats. PLoS One 8, e82227.

The present data set corresponds to the genotypes for seven microsatellite markers for three Antarctic sea urchin species of the genus Abatus. Sea urchin individuals were collected in five sites separated by up to 5 km in the near-shore area surrounding Davis Station in the Vestfold Hills Region, East Antarctica. For each microsatellite loci, the size of each allele was scored (in base pairs) using the CEQ 8000 Genetic Analysis System software v.8.0. Fragments were separated on an automated sequencer (CEQ 8000, Beckman Coulter) in the Central Science Laboratory at University of Tasmania.

These data come from a set of experiments conducted on the coastal waters near Davis Station in January 2017. The first set of data are from a transect near the Sorsdal glacier and out to sea, to characterise DMSP-mediated phytoplankton bacteria interactions along a salinity gradient. The second data set are from a series of incubation experiments to gain deeper insight into the role of various infochemicals in Antarctic phytoplankton-bacteria relationships. Specifically, DMSP, VitB12, Tryptophan and Methionine. The last data set is derived from two incubation experiments: a short term DMSP addition experiment to look at its uptake and utilisation by the microbial community; and a longer-term (5 day) stable isotope probing experiment to track DMSP through the lower trophic food web.

RNA was extracted from pooled gonad tissues and tails of five sexually mature males and females, respectively, originating from the krill aquarium at the AAD in Tasmania, Australia. For RNA extractions, RNeasy mini kits (QIAGEN) were used and total RNA (8 micrograms each) was sent to Geneworks, South Australia (www.geneworks.com.au), for Illumina TruSeq 75 bp paired-end sequencing in two technical replica. Reads Yield Total Yield Krill_Male_sex_a_read1_sequence.txt 8,120,993 609,074,475 bases 1,218,148,950 bases Krill_Male_sex_a_read2_sequence.txt 8,120,993 609,074,475 bases Krill_Male_sex_b_read1_sequence.txt 10,465,586 784,918,950 bases 1,569,837,900 bases Krill_Male_sex_b_read2_sequence.txt 10,465,586 784,918,950 bases Krill_Male_tissue_a_read1_sequence.txt 7,867,804 590,085,300 bases 1,180,170,600 bases Krill_Male_tissue_a_read2_sequence.txt 7,867,804 590,085,300 bases Krill_Male_tissue_b_read1_sequence.txt 10,956,251 821,718,825 bases 1,793,118,450 bases Krill_Male_tissue_b_read2_sequence.txt 10,956,251 821,718,825 bases Krill_Female_sex_read1a_sequence.txt 29,447,654 2,208,574,050 bases 4,417,148,100 bases Krill_Female_sex_read2a_sequence.txt 29,447,654 2,208,574,050 bases Krill_Female_sex_read1b_sequence.txt 18,223,515 1,366,763,625 bases 2,733,527,250 bases Krill_Female_sex_read2b_sequence.txt 18,223,515 1,366,763,625 bases The insert size for these libraries is approx 160bp.

1st Experiment 24/11/16 ************************************************************************************************ See 2016_11_24_Miseq_Sheet 1. Sanger Sequencing Plate #4 - 25mg of Tissue was extracted by AGRF. DNA was diluted to 5ng/ul. Samples were sanger sequenced with 16SAR (Palumbi) primer. If they failed, I used COI3 cocktail (Ivanova). FASTA sequences from Plate 4 are in the folder named Sanger Sequence FASTA Plate #4. Naming - Plate position, primer, sample ID. ie reater than A1-16S-AR_1952. 2. DNA and Tissue Pools of Plate 4 We wanted to explore the possibility of using a metabarcoding approach. For metabarcoding we re-examined specimens already identified from sanger sequences. We mixed DNA from many samples (n=16 or n=96) and did a single amplification (i.e. up to 96 DNA extractions processed in a single-tube marker amplification). We also took it a step further and tried blending a set amount of tissue from many fish specimens (n=16 or n=96) and did a single DNA extraction on the tissue mixes (i.e. a single DNA extraction and single tube amplification for up to 96 samples). See 2016_11_24_Miseq_Sheet for DNA and Tissue Pool mixes. 3. Miseq Run 16 samples were ran on a 250bp pe read. Each sample was amplified with 3 primer sets - COI (please note one dual labelled set was used), 12s and 16s (Primers listed on 2016_11_24_Miseq_Sheet). They were diluted 1:10 and illumina sequencing adaptors were added (please note I used same I7 and I5 per sample, so they had to be sorted on amplicon). 2016_11_24_fastq_files has the data from miseq. and 2016_11_24_merged_fastq_files has the merged files. For some unknown reason 16s tissue produced no data. 2nd Experiment 04/07/17 ************************************************************************************************* 1. DNA Extractions Plate #1, 2 and 3 - 25mg of Tisse was extracted by AGRF. DNA was diluted to 5ng/ul. We also used Plate #4 from experiment above. See Plate Layout for sample allocation. 2. Tissue and DNA Pools DNA pools were from Plate 1, 2, 3 and 4. Tissue Mixes were from Plate 2 and 4 only. We wanted to explore the possibility of using a metabarcoding approach. We mixed DNA from many samples (n=16 or n=96) and did a single amplification (i.e. up to 96 DNA extractions processed in a single-tube marker amplification). We also took it a step further and tried blending a set amount of tissue from many fish specimens (n=16 or n=96) and did a single DNA extraction on the tissue mixes (i.e. a single DNA extraction and single tube amplification for up to 96 samples). See plate layout for DNA and Tissue Pool mixes. 3. Miseq Run 577 samples were sequenced in a 250bp pe read. See 2017_07_04_Miseq Sheet. Plate 1, 2 3 and 4 were all sequenced with Leray Primers.(Please note I accidentally amplified the first half of plate one with one pair of dual labelled COI primers, index on miseq sheet). I also made a plate of tissue and DNA pools (see plate layout for DNA and Tissue Pool mixes) and amplified those with 4 primers (primer sequences on miseq sheet) COI (individual dual labelled primers, 1st round index are on miseq sheet) 12s Fish 16s Chordate NADH The last 4 samples with 12s were to add to database as there are no 12S sequences for those species on genbank. See PCR recipes for annealing temp and cycling etc I accidentally put the marker under sample name so the original sample ID was lost and miseq gave it a new name (name from miseq output) and then another new name from merged file. Finally I gave them a unique sample ID. See name file if you need more information. 2017_07_04 has the data from miseq. and 2017_07_04_merged_fastq_files has the merged files. Samples were clustered using zero radius OTU's. 4.Results See Results database. The spreadsheet has all of the possible name combinations from the run. It also contains the Haul ID and date, time, lat, long etc. There is a morph taxa ID which refers to what the observer has identified the fish and then there is Seq_Taxa_ID which is the sequencing result. There is also a list of primers that were used to identify the fish. 0 indicated that the primer wasnt used, 1 indicates it was. The second tab has all of the info for the samples that failed. *************************************************************************************************

We use RNA sequencing to investigate which genetic/physiological pathways in Antarctic krill are affected by increased CO2 levels. We carried out larval CO2 exposure experiments in March 2012 at the AAD aquarium. Two developmental stages were used (Calyptopis I and Furcilia V) and three CO2 levels (control, 1000 and 2000 ppm). These were short term experiments (2 days) - since initial longer experiments starting with fertilized eggs resulted in differences in developmental stages between treatments and control which could confound the data. RNA was extracted from larvae and high-throughput RNA sequencing (RNA-seq) was carried out on 6 samples (2 stages * 3 treatments). Sequencing was carried out on an Illumina sequencer (Genome Analyzer II). We collected ~ 60 million sequence reads per sample (Data in FASTA format each read gives 100 base pairs of sequence), so a total of ~360 million reads (36 billion bp of data).

These spreadsheets provide the proportions of prey DNA sequences in the scats of Adelie penguins at Bechervaise Island and Whitney Point in East Antarctica. Samples were collected during two stages of the breeding season: mid brood guard (Bechervaise Island-January 4-6th 2013, Whitney Point 23- 28th December 2012) and mid creche (23-26th January 2013). Scat samples were collected from breeding birds, chicks and non-breeders at Bechervaise Island and breeding birds and chicks at Whitney Point. 'Breeders' were identified as individuals brooding or provisioning a chick, whereas 'non-breeders' were usually pairs that had reoccupied the colony and were building new practice nests with no chick present. Non-breeders in the colony include immature birds that have not yet bred and mature birds of breeding age that did not breed in a particular season (e.g. no partner or insufficient body condition) DNA from each sample was extracted and sequenced as per the protocols in the following paper: Jarman, S.N., McInnes, J.C., Faux, C., Polanowski, A.M., Marthick, J., Deagle, B.E., Southwell, C. and Emmerson, L. 2013 Adelie penguin population diet monitoring by analysis of food DNA in scats. PLoS One 8, e82227. (doi:10.1371/journal.pone.0082227). The Raw Data spreadsheet contains the proportion of each prey group of each individual sample, plus the total sequence count of prey items. Only samples with greater than 100 prey sequences are included in the dataset. The summary datasheet contains only prey taxa which contained greater than 2% of the proportion of sequences. Analysis of these data have been published in: McInnes JC, Emmerson L, Southwell C, Faux C, Jarman SN. (2016) Simultaneous DNA-based diet analysis of breeding, non-breeding and chick Adelie Penguins http://dx.doi.org/10.1098/rsos.150443

Krill-associated bacterial communities characterised by high-throughput DNA sequencing of the 16S ribosomal RNA gene. The data is decribed in 'Clarke LJ, Suter L, King R, Bissett A and Deagle BE (2019) Antarctic Krill Are Reservoirs for Distinct Southern Ocean Microbial Communities. Front. Microbiol. 9:3226. doi: 10.3389/fmicb.2018.03226' available here: https://www.frontiersin.org/articles/10.3389/fmicb.2018.03226/full

In March 2018, 23 environmental DNA (eDNA) samples (2 L of filtered seawater) were collected between Hobart, Tasmania and subantarctic Macquarie Island. These samples were processed using six different genetic metabarcoding markers targeting different taxonomic groups within the metazoan clade: A broad cytochrome c oxidase subunit I (COI) marker targeting all metazoans, and five different 16S markers targeting fish, cephalopods and crustaceans (one degenerate marker), fish (two markers of different lengths), cephalopods (one marker) and crustaceans (one marker). The aim of this study was to identify an ideal set of molecular markers to identify as many metazoan species as possible from small environmental samples, with a particular focus on vertebrates, crustaceans and cephalopods. The data and methods are described in the word file "V4 2018 eDNA group specific markers.docx", results are summarised in the excel file "Marker.detection.xlsx" and additional sample information is in the excel files "2018_11_07_eDNA-sample-info.xls" and "sample.map.csv". Each genetic marker used in this study has its own folder, containing the raw FASTQ sequencing data, the processed FASTA sequencing data, the bioinformatics processing pipeline, the zOTU fasta file, BLAST output, MEGAN output and curated zOTU table. For further explanations please refer to the word file "V4 2018 eDNA group specific markers.docx".