List of size fractionated eukaryotic plankton community samples and associated metadata (Database W1)

The present data set provides an Excel file in a zip archive. The file lists 334 samples of size fractionated eukaryotic plankton community with a suite of associated metadata (Database W1). Note that if most samples represented the piconano- (0.8-5 µm, 73 samples), nano- (5-20 µm, 74 samples), micro- (20-180 µm, 70 samples), and meso- (180-2000 µm, 76 samples) planktonic size fractions, some represented different organismal size-fractions: 0.2-3 µm (1 sample), 0.8-20 µm (6 samples), 0.8 µm - infinity (33 samples), and 3-20 µm (1 sample). The table contains the following fields: a unique sample sequence identifier; the sampling station identifier; the Tara Oceans sample identifier (TARA_xxxxxxxxxx); an INDSC accession number allowing to retrieve raw sequence data for the major nucleotide databases (short read archives at EBI, NCBI or DDBJ); the depth of sampling (Subsurface - SUR or Deep Chlorophyll Maximum - DCM); the targeted size range; the sequences template (either DNA or WGA/DNA if DNA extracted from the filters was Whole Genome Amplified); the latitude of the sampling event (decimal degrees); the longitude of the sampling event (decimal degrees); the time and date of the sampling event; the device used to collect the sample; the logsheet event corresponding to the sampling event ; the volume of water sampled (liters). Then follows information on the cleaning bioinformatics pipeline shown on Figure W2 of the supplementary litterature publication: the number of merged pairs present in the raw sequence file; the number of those sequences matching both primers; the number of sequences after quality-check filtering; the number of sequences after chimera removal; and finally the number of sequences after selecting only barcodes present in at least three copies in total and in at least two samples. Finally, are given for each sequence sample: the number of distinct sequences (metabarcodes); the number of OTUs; the average number of barcode per OTU; the Shannon diversity index based on barcodes for each sample (URL of W4 dataset in PANGAEA); and the Shannon diversity index based on each OTU (URL of W5 dataset in PANGAEA).

Individual codes, GenBank accession numbers and GenBank accession links for Mediterranean sponges

Metabolomic analysis has shown the chemical richness of the sponge-associated actinomycetes Streptomyces sp. SBT349, Nonomureae sp. SBT364, and Nocardiopsis sp. SBT366. The genomes of these actinomycetes were sequenced and the genomic potential for secondary metabolism was evaluated. Their draft genomes have sizes of 8.0, 10, and 5.8Mb having 687, 367, and 179 contigs with a GC content of 71.6, 70.7, and 72.7%, respectively. Moreover, antiSMASH 3.0 predicted 108, 149, and 75 secondary metabolite gene clusters, respectively which highlight the metabolic capacity of the three actinomycete species to produce diverse classes of natural products.

Individual codes, GenBank accession numbers and GenBank accession links for sponge-associated actinobacterial isolates

Here, we report the draft genome sequences of three actinobacterial isolates, Micromonospora sp. RV43, Rubrobacter sp. RV113, and Nocardiopsis sp. RV163 that had previously been isolated from Mediterranean sponges. The draft genomes were analyzed for the presence of gene clusters indicative of secondary metabolism using antiSMASH 3.0 and NapDos pipelines. Our findings demonstrated the chemical richness of sponge-associated actinomycetes and the efficacy of genome mining in exploring the genomic potential of sponge-derived actinomycetes.

Whole rock and Cr-rich spinel geochemistry of ODP Legs 152 and 163 and DSDP Hole 38-338 samples

Coring during Ocean Drilling Program and Deep Sea Drilling Project Legs 163, 152, 104, 81, and 38 recovered sequences of altered basalt from North Atlantic seaward-dipping reflector sequences (SDRS) erupted during the initial rifting of Greenland from northern Europe and likely associated with excessive mantle temperatures caused by an impacting mantle plume head. Cr-rich spinel is found abundantly as inclusions and groundmass crystals within the olivine-rich lavas of Hole 917A (Leg 152) cored into the Southeast Greenland SDRS, but only rarely as inclusions within plagioclase in the lavas of the Vøring Plateau SDRS, and it is absent from other cored SDRS lavas from the Rockall Plateau and Southeast Greenland. Eruptive melt compositions determined from inferred, thermodynamically-defined, spinel-melt exchange equilibria indicate that the most primitive melts represented by Hole 917A basalts have Mg/(Mg + Fe2+) at least as high as 0.70 and approach near-primary mantle melt compositions. In contrast, Cr-rich spinels from Hole 338 (Leg 38) lavas on the Vøring Plateau SDRS give evidence for melt with Mg/(Mg + Fe2+) only as high as 0.64. This study underlines that primitive melts similar to those from Hole 917A comprise only a small fraction of the eruptive North Atlantic SDRS melts, and that most SDRS basalts were, in fact, too evolved to have precipitated Cr-rich spinel, with true melt Mg/(Mg + Fe2+) likely below 0.60. The evolved nature of the SDRS basalts implies large amounts of fractionation at the base of the crust or deep within it, consistent with seismic results that indicate an abnormally thick Layer 3 underlying the SDRS.

Metadata und statistic analysis of archael and bacterial sequences originating from sediments of the Håkon Mosby mud volcano (Z1-Z3, all habitats)

DNA extraction was carried out as described on the MICROBIS project pages (http://icomm.mbl.edu/microbis ) using a commercially available extraction kit. We amplified the hypervariable regions V4-V6 of archaeal and bacterial 16S rRNA genes using PCR and several sets of forward and reverse primers (http://vamps.mbl.edu/resources/primers.php). Massively parallel tag sequencing of the PCR products was carried out on a 454 Life Sciences GS FLX sequencer at Marine Biological Laboratory, Woods Hole, MA, following the same experimental conditions for all samples. Sequence reads were submitted to a rigorous quality control procedure based on mothur v30 (doi:10.1128/AEM.01541-09) including denoising of the flow grams using an algorithm based on PyroNoise (doi:10.1038/nmeth.1361), removal of PCR errors and a chimera check using uchime (doi:10.1093/bioinformatics/btr381). The reads were taxonomically assigned according to the SILVA taxonomy (SSURef v119, 07-2014; doi:10.1093/nar/gks1219) implemented in mothur and clustered at 98% ribosomal RNA gene V4-V6 sequence identity. V4-V6 amplicon sequence abundance tables were standardized to account for unequal sampling effort using 1000 (Archaea) and 2300 (Bacteria) randomly chosen sequences without replacement using mothur and then used to calculate inverse Simpson diversity indices and Chao1 richness (doi:10.2307/4615964). Bray-Curtis dissimilarities (doi:10.2307/1942268) between all samples were calculated and used for 2-dimensional non metric multidimensional scaling (NMDS) ordinations with 20 random starts (doi:10.1007/BF02289694). Stress values below 0.2 indicated that the multidimensional dataset was well represented by the 2D ordination. NMDS ordinations were compared and tested using Procrustes correlation analysis (doi:10.1007/BF02291478). All analyses were carried out with the R statistical environment and the packages vegan (available at: http://cran.r-project.org/package=vegan), labdsv (available at: http://cran.r-project.org/package=labdsv), as well as with custom R scripts. Operational taxonomic units at 98% sequence identity (OTU0.03) that occurred only once in the whole dataset were termed absolute single sequence OTUs (SSOabs; doi:10.1038/ismej.2011.132). OTU0.03 sequences that occurred only once in at least one sample, but may occur more often in other samples were termed relative single sequence OTUs (SSOrel). SSOrel are particularly interesting for community ecology, since they comprise rare organisms that might become abundant when conditions change.16S rRNA amplicons and metagenomic reads have been stored in the sequence read archive under SRA project accession number SRP042162.

Availability of sequences of aquatic and terrestrial taxa in genetic databases (GenBank and BOLD - the Barcode of Life Database) in 2010, 2012 and 2016

Correct species identifications are of tremendous importance for invasion ecology, as mistakes could lead to misdirecting limited resources against harmless species or inaction against problematic ones. DNA barcoding is becoming a promising and reliable tool for species identifications, however the efficacy of such molecular taxonomy depends on gene region(s) that provide a unique sequence to differentiate among species and on availability of reference sequences in existing genetic databases. Here, we assembled a list of aquatic and terrestrial non-indigenous species (NIS) and checked two leading genetic databases for corresponding sequences of six genome regions used for DNA barcoding. The genetic databases were checked in 2010, 2012, and 2016. All four aquatic kingdoms (Animalia, Chromista, Plantae and Protozoa) were initially equally represented in the genetic databases, with 64, 65, 69, and 61% of NIS included, respectively. Sequences for terrestrial NIS were present at rates of 58 and 78% for Animalia and Plantae, respectively. Six years later, the number of sequences for aquatic NIS increased to 75, 75, 74, and 63% respectively, while those for terrestrial NIS increased to 74 and 88% respectively. Genetic databases are marginally better populated with sequences of terrestrial NIS of plants compared to aquatic NIS and terrestrial NIS of animals. The rate at which sequences are added to databases is not equal among taxa. Though some groups of NIS are not detectable at all based on available data - mostly aquatic ones - encouragingly, current availability of sequences of taxa with environmental and/or economic impact is relatively good and continues to increase with time.