Accessing BCO-DMO data
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BCO-DMO ERDDAP
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| griddap | Subset | tabledap | Make A Graph | wms | files | Accessible | Title | Summary | FGDC | ISO 19115 | Info | Background Info | RSS | Institution | Dataset ID | |
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| log in | [Kelletia kelletii: DNA and RNA sequence] - Full genome and transcriptome sequence assembly of the non-model organism Kellet’s whelk, Kelletia kelletii (Collaborative Research: RUI: Combined spatial and temporal analyses of population connectivity during a northern range expansion) | Understanding the genomic characteristics of non-model organisms can bridge research gaps between ecology and evolution. However, the lack of a reference genome and transcriptome for these species makes their study challenging. Here, we complete the first full genome and transcriptome sequence assembly of the non-model organism Kellet's whelk, Kelletia kelletii, a marine gastropod exhibiting a poleward range expansion coincident with climate change. We used a combination of Oxford Nanopore Technologies, PacBio, and Illumina sequencing platforms and integrated a set of bioinformatic pipelines to create the most complete and contiguous genome documented among the Buccinoidea superfamily to date. Genome validation revealed relatively high completeness with low missing metazoan Benchmarking Universal Single-Copy Orthologs (BUSCO) and an average coverage of ∼70x for all contigs. Genome annotation identified a large number of protein-coding genes similar to some other closely related species, suggesting the presence of a complex genome structure. Transcriptome assembly and analysis of individuals during their period of peak embryonic development revealed highly expressed genes associated with specific Gene Ontology (GO) terms and metabolic pathways, most notably lipid, carbohydrate, glycan, and phospholipid metabolism. We also identified numerous heat shock proteins (HSPs) in the transcriptome and genome that may be related to coping with thermal stress during the sessile life history stage. A robust reference genome and transcriptome for the non-model organism K. kelletii provide resources to enhance our understanding of its ecology and evolution and potential mechanisms of range expansion for marine species facing environmental changes.\n\ncdm_data_type = Other\nVARIABLES:\nRun (unitless)\nAssay_Type (unitless)\nAvgSpotLen (unitless)\nBases (unitless)\nBioProject (unitless)\nBioSample (unitless)\nBioSampleModel (unitless)\nBytes (unitless)\nCenter_Name (unitless)\n... (29 more variables)\n | BCO-DMO | bcodmo_dataset_945292_v1 | ||||||||||||
| https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_930084_v1 | https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_930084_v1.graph | https://erddap.bco-dmo.org/erddap/files/bcodmo_dataset_930084_v1/ | public | [Kāneʻohe Bay Time-series - microbial community] - Flow cytometry, 16S rRNA gene amplicons, chlorophyll a, and surface seawater measurements taken between August 2017 to June 2019 Kāneʻohe Bay, Oʻahu, Hawaiʻi (Population genomics and ecotypic divergence in the most dominant lineage of marine bacteria) | These data include temperature, pH, salinity, chlorophyll a concentrations, cellular abundances of Prochlorococcus, Synechococcus, photosynthetic picoeukaryotes, and heterotrophic bacteria, and 16S ribosomal RNA gene amplicon libraries from 200 surface seawater samples collected as part of the Kāneʻohe Bay Time-series (KByT). Near-monthly sampling of surface seawater was conducted between August 2017 to June 2019 at 10 sites within coastal waters of Kāneʻohe Bay, Oʻahu, Hawaiʻi and in the adjacent offshore. Instruments used were a YSI 6,600 sonde, a Turner 10AU fluorometer, an EPICS ALTRA flow cytometer, and an Illumina MiSeq v2 platform.\n\nThese data characterize the partitioning of microbial communities across sharp physiochemical gradients in surface seawaters connecting nearshore and offshore waters in the tropical Pacific. This study provides evidence for the ecological differentiation of SAR11 marine bacteria across nearshore to offshore waters in the tropical Pacific and further increases our understanding of how SAR11 genetic diversity partitions into distinct ecological units. Data were collected by Sarah J. Tucker, Kelle C. Freel, Elizabeth A. Monaghan, Clarisse E. S. Sullivan, Oscar Ramfelt, Yoshimi M. Rii, and Michael S. Rappé.\n\ncdm_data_type = Other\nVARIABLES:\nSample_ID (unitless)\ncollection_date (unitless)\ndepth (m)\nenv_broad_scale (unitless)\nenv_local_scale (unitless)\nenv_medium (unitless)\ngeo_loc_name (unitless)\nlatitude (degrees_north)\nlongitude (degrees_east)\nSite_name (unitless)\nchlorophyll_a_ug_per_L (micrograms per Liter)\nph (no unit)\nsalinity (ppt)\n... (21 more variables)\n | https://erddap.bco-dmo.org/erddap/metadata/fgdc/xml/bcodmo_dataset_930084_v1_fgdc.xml | https://erddap.bco-dmo.org/erddap/metadata/iso19115/xml/bcodmo_dataset_930084_v1_iso19115.xml | https://erddap.bco-dmo.org/erddap/info/bcodmo_dataset_930084_v1/index.htmlTable | https://www.bco-dmo.org/dataset/930084
| https://erddap.bco-dmo.org/erddap/rss/bcodmo_dataset_930084_v1.rss | https://erddap.bco-dmo.org/erddap/subscriptions/add.html?datasetID=bcodmo_dataset_930084_v1&showErrors=false&email= | BCO-DMO | bcodmo_dataset_930084_v1 | |||
| https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_926299_v1 | https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_926299_v1.graph | https://erddap.bco-dmo.org/erddap/files/bcodmo_dataset_926299_v1/ | public | [Microorganisms associated with doliolids] - Eukaryotic and prokaryotic microbial taxa retained by wild-caught doliolids collected during bloom events at three different shelf locations in the northern California Current system in June 2019. (Collaborative Research: Comparative feeding by gelatinous grazers on microbial prey) | Doliolids have a unique ability to impact the marine microbial community through bloom events and high filtration rates. Their predation on large eukaryotic microorganisms is established and evidence of predation on smaller prokaryotic microorganisms is beginning to emerge. We studied the retention of both eukaryotic and prokaryotic microbial taxa by wild-caught doliolids in the northern California Current system. Doliolids were collected during bloom events identified at three different shelf locations with variable upwelling intensity.\n\ncdm_data_type = Other\nVARIABLES:\nbioproject_accession (unitless)\nbiosample_accession (unitless)\nsample_name (unitless)\nsra_sample_accession (unitless)\nsample_accession_title (unitless)\norganism_name (unitless)\norganism_taxonomy_id (unitless)\norganism_taxonomy_name (unitless)\nkeyword (unitless)\nbiosample_package (unitless)\ncollection_date (unitless)\ndepth (m)\nenv_broad_scale (unitless)\nenv_local_scale (unitless)\nenv_medium (unitless)\ngeo_loc_name (unitless)\nlatitude (Sampling_lat, degrees_north)\nlongitude (Sampling_lon, degrees_east)\nsize_frac (unitless)\nhost (unitless)\nsource_material_id (unitless)\nstatus (unitless)\n... (5 more variables)\n | https://erddap.bco-dmo.org/erddap/metadata/fgdc/xml/bcodmo_dataset_926299_v1_fgdc.xml | https://erddap.bco-dmo.org/erddap/metadata/iso19115/xml/bcodmo_dataset_926299_v1_iso19115.xml | https://erddap.bco-dmo.org/erddap/info/bcodmo_dataset_926299_v1/index.htmlTable | https://www.bco-dmo.org/dataset/926299
| https://erddap.bco-dmo.org/erddap/rss/bcodmo_dataset_926299_v1.rss | https://erddap.bco-dmo.org/erddap/subscriptions/add.html?datasetID=bcodmo_dataset_926299_v1&showErrors=false&email= | BCO-DMO | bcodmo_dataset_926299_v1 | |||
| log in | [Microorganisms associated with pyrosomes] - High-throughput sequencing of the 16S rRNA gene, microscopy, and flow cytometry of pyrosome-associated microorganisms compared to seawater sampled during a Pyrosoma atlanticum bloom in the Northern California Current System in July 2018. (Collaborative Research: Comparative feeding by gelatinous grazers on microbial prey) | Pyrosomes are widely distributed pelagic tunicates that have the potential to reshape marine food webs when they bloom. However, their grazing preferences and interactions with the background microbial community are poorly understood. The diversity, relative abundance, and taxonomy of pyrosome-associated microorganisms were compared to seawater during a Pyrosoma atlanticum bloom in the Northern California Current System using high-throughput sequencing of the 16S rRNA gene, microscopy, and flow cytometry.\n\ncdm_data_type = Other\nVARIABLES:\nbioproject_accession (unitless)\nbiosample_accession (unitless)\nsample_name (unitless)\nsra_sample_accession (unitless)\nsample_accession_title (unitless)\norganism_name (unitless)\norganism_taxonomy_id (unitless)\norganism_taxonomy_name (unitless)\nkeywords (unitless)\nbiosample_package (unitless)\ncollection_date (unitless)\nenv_broad_scale (unitless)\nenv_local_scale (unitless)\nenv_medium (unitless)\ngeo_loc_name (unitless)\nhost (unitless)\nlatitude (Sampling_lat, degrees_north)\nlongitude (Sampling_lon, degrees_east)\ndepth (m)\nhost_length (centimeter (cm))\nsource_material_id (unitless)\nstatus (unitless)\n... (20 more variables)\n | BCO-DMO | bcodmo_dataset_926093_v1 | ||||||||||||
| log in | [Northern California Current Microorganisms] - 16S rRNA gene of microorganisms sampled along the Newport Hydrographic (NH) and Trinidad Head (TR) lines, in OR and CA in 2018 and 2019 (Collaborative Research: Comparative feeding by gelatinous grazers on microbial prey) | The Northern California Current ecosystem is a productive system which supports major fisheries. To determine how the microbial community responds to variable upwelling, we examined the 16S rRNA gene of microorganisms from two size fractions, 0.2-1.6µm and greater than 1.6µm along the Newport Hydrographic (NH) and Trinidad Head (TR) lines, in OR and CA.\n\ncdm_data_type = Other\nVARIABLES:\nbioproject_accession (unitless)\nbiosample_accession (unitless)\nmessage (unitless)\nsample_name (unitless)\norganism (unitless)\ncollection_date (unitless)\ndepth (m)\nenv_broad_scale (unitless)\nenv_local_scale (unitless)\nenv_medium (unitless)\ngeo_loc_name (unitless)\nlatitude (Sampling_lat, degrees_north)\nlongitude (Sampling_lon, degrees_east)\nsize_frac (unitless)\nsra_run_accession (unitless)\nsra_study_accession (unitless)\nobject_status (unitless)\nlibrary_ID (unitless)\ntitle (unitless)\nlibrary_strategy (unitless)\nlibrary_source (unitless)\nlibrary_selection (unitless)\nlibrary_layout (unitless)\nplatform (unitless)\n... (5 more variables)\n | BCO-DMO | bcodmo_dataset_926850_v1 | ||||||||||||
| log in | [Salp and pteropod associated microorganisms] - Salp and pteropod associated microorganisms from the Western Edge of the Gulf Stream sampled in September 2019. (Collaborative Research: Comparative feeding by gelatinous grazers on microbial prey) | Microbial mortality impacts the structure of food webs, carbon flow, and the interactions that create dynamic patterns of abundance across gradients in space and time in diverse ecosystems. In the oceans, estimates of microbial mortality by viruses, protists, and small zooplankton do not account fully for observations of loss, suggesting the existence of underappreciated mortality sources. We examined how ubiquitous mucous mesh feeders (i.e. gelatinous zooplankton) could contribute to microbial mortality in the open ocean. We coupled capture of live animals by blue-water diving to sequence-based approaches to measure the enrichment and selectivity of feeding by two coexisting mucous grazer taxa (pteropods and salps) on numerically dominant marine prokaryotes. We show that mucous mesh grazers consume a variety of marine prokaryotes and select between coexisting lineages and similar cell sizes. We show that Prochlorococcus may evade filtration more than other cells and that planktonic archaea are consumed by macrozooplanktonic grazers. Discovery of these feeding relationships identifies a new source of mortality for Earth's dominant marine microbes and alters our understanding of how top-down processes shape microbial community and function.\n\ncdm_data_type = Other\nVARIABLES:\nbioproject_accession (unitless)\nbiosample_accession (unitless)\nmessage (unitless)\nsample_name (unitless)\nsample_title (unitless)\norganism (unitless)\ncollection_date (unitless)\ndepth_f (Depth, feet)\nenv_broad_scale (unitless)\nenv_local_scale (unitless)\nenv_medium (unitless)\ngeo_loc_name (unitless)\nlatitude (Sampling_lat, degrees_north)\nlongitude (Sampling_lon, degrees_east)\n... (15 more variables)\n | BCO-DMO | bcodmo_dataset_926841_v1 |