Accessing BCO-DMO data
Brought to you by BCO-DMO
|
|
BCO-DMO ERDDAP
Accessing BCO-DMO data |
log in
Brought to you by BCO-DMO |
| griddap | Subset | tabledap | Make A Graph | wms | files | Accessible | Title | Summary | FGDC | ISO 19115 | Info | Background Info | RSS | Institution | Dataset ID | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 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_986592_v1 | https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_986592_v1.graph | https://erddap.bco-dmo.org/erddap/files/bcodmo_dataset_986592_v1/ | public | [Longitudinal study NCBI SRA] - NCBI Sequence Read Archive (SRA) accession numbers for fastq sequence files of 16S amplicons from a longitudinal study of SCTLD at St. John, U.S. Virgin Islands from 2020 to 2024 (A multi-scale approach to predicting infectious multi-host disease spread in marine benthic communities) | In St. John, U.S. Virgin Islands, a longitudinal study of Colpophyllia natans was conducted. Six corals per site (two sites) were tagged and repeatedly sampled from July 2020 through March 2024, during which time, stony coral tissue loss disease (SCTLD) arrived on the reefs. As the tagged corals contracted SCTLD, coral tissue and near-coral seawater (2-5 centimeters from colony surface) were collected. Coral tissue was separated from the coral skeleton, and the seawater was filtered through 0.2-micrometer (µm) filters. DNA was extracted from the tissue and filters, and 16S ribosomal RNA gene sequencing was done to determine the bacteria and archaea communities that live within and near the corals. The goal of the study was to determine how coral-associated microbiomes are affected by the arrival of SCTLD through time. This data set contains the fastq files of the 16S amplicon sequencing of the coral tissue and near-coral seawater communities. National Center for Biotechnology Information (NCBI) SRA: SRP550314; BioProject: PRJNA1194595\n\ncdm_data_type = Other\nVARIABLES:\nExperiment_Accession (unitless)\nInstrument (unitless)\nStudy_Accession (unitless)\nStudy_Title (unitless)\nSample_Accession (unitless)\nLibrary_Name (unitless)\nCollection_date (unitless)\nlatitude (degrees_north)\nlongitude (degrees_east)\n | https://erddap.bco-dmo.org/erddap/metadata/fgdc/xml/bcodmo_dataset_986592_v1_fgdc.xml | https://erddap.bco-dmo.org/erddap/metadata/iso19115/xml/bcodmo_dataset_986592_v1_iso19115.xml | https://erddap.bco-dmo.org/erddap/info/bcodmo_dataset_986592_v1/index.htmlTable | https://osprey.bco-dmo.org/dataset/986592
| https://erddap.bco-dmo.org/erddap/rss/bcodmo_dataset_986592_v1.rss | https://erddap.bco-dmo.org/erddap/subscriptions/add.html?datasetID=bcodmo_dataset_986592_v1&showErrors=false&email= | BCO-DMO | bcodmo_dataset_986592_v1 | |||
| https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_936069_v1 | https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_936069_v1.graph | https://erddap.bco-dmo.org/erddap/files/bcodmo_dataset_936069_v1/ | public | [Metagenome and metatranscriptome sequences from deep-sea hydrothermal vent microbial communities] - Metagenome and metatranscriptome sequences from deep-sea hydrothermal vent microbial communities collected on cruises AT42-22, TN405, and NA108 from May 2019 to Jun 2022 (Collaborative Research: Microbes need frenemies: unveiling microbial relationships with protists and viruses that support deep-sea hydrothermal vent food webs) | This dataset is a collection of sample metadata, identified for all samples, and NCBI accession information for samples and sequence runs produced as part of the \"Microbes need frenemies\" project. This project examines trophic interactions among microbial eukaryotes, viruses, bacteria, and archaea at deep-sea hydrothermal vents using metagenomics and metatranscriptomics and characterizes these ecologically-significant interactions, such as mutualism, predator-prey, or virus-host. \n\nWe sequenced samples collected during the 2020 expedition AT42-22 to the Mid-Cayman Rise hydrothermal vent fields, as well as from the 2019 expedition NA108 to the Gorda Ridge and the 2022 expedition TN405 to the Axial seamount. Sequencing targeted archaea, bacteria, and viruses with metagenomics and microbial eukaryotes with metatranscriptomics. We plan to use these data to identify ecologically-significant interactions among protists, viruses, bacteria, and archaea, with a specific emphasis on microbial mortality via viral lysis and eukaryotic grazing. Archived samples were also included in the analysis.\n\ncdm_data_type = Other\nVARIABLES:\nSAMPLE_ID (unitless)\nSHORT_SAMPLE_ID (unitless)\nSAMPLE_NAME (unitless)\nLAB_NUM (unitless)\nCRUISE_ID (unitless)\nFIELD_REGION (unitless)\nYEAR (unitless)\nFIELD_YEAR (unitless)\nVENT (unitless)\nlatitude (degrees_north)\nlongitude (degrees_east)\nORIGIN_TYPE (unitless)\nORIGIN_DESCRIPTION (unitless)\nFRENEMIES_PROJ (unitless)\n... (11 more variables)\n | https://erddap.bco-dmo.org/erddap/metadata/fgdc/xml/bcodmo_dataset_936069_v1_fgdc.xml | https://erddap.bco-dmo.org/erddap/metadata/iso19115/xml/bcodmo_dataset_936069_v1_iso19115.xml | https://erddap.bco-dmo.org/erddap/info/bcodmo_dataset_936069_v1/index.htmlTable | https://www.bco-dmo.org/dataset/936069
| https://erddap.bco-dmo.org/erddap/rss/bcodmo_dataset_936069_v1.rss | https://erddap.bco-dmo.org/erddap/subscriptions/add.html?datasetID=bcodmo_dataset_936069_v1&showErrors=false&email= | BCO-DMO | bcodmo_dataset_936069_v1 | |||
| log in | [Metagenomic samples] - Metagenomic sample information, genetic accession identifiers (NCBI SRA, JGI IMG), and estimated gene copies from Orcas Island coastal waters (2 m depth) in May and June of 2021 (Collaborative Research: Rhythm and Blooms: Deciphering metabolic, functional and taxonomic interactions over the life cycle of a phytoplankton bloom) | This dataset contains NCBI Sequence Read Archive (SRA) accession numbers, DOE JGI Integrated Microbial Genomes & Microbiome (IMG/M) IDs, and estimated gene copies for metagenomic samples collected at Orcas Island, WA, USA Coastal Ocean (2m depth) from 5/27/21 to 6/18/21 collected as part of the following study.\n\nStudy abstract:\n\nFloating, single-celled algae, or phytoplankton, form the base of marine food webs. When phytoplankton have sufficient nutrients to grow quickly and generate dense populations, known as blooms, they influence productivity of the entire food web, including rich coastal fisheries. The present research explores how the environment (nutrients) as well as physical and chemical interactions between individual cells in a phytoplankton community and their associated bacteria act to control the timing of bloom events in a dynamic coastal ecosystem. The work reveals key biomolecules within the base of the food web that can inform food web functioning (including fisheries) and be used in global computational models that forecast the impacts of phytoplankton activities on global carbon cycling. A unique set of samples and data collected in 2021 and 2022 that captured phytoplankton and bacterial communities before, during, and after phytoplankton blooms, is analyzed using genomic methods and the results are used to interrogate these communities for biomolecules associated with blooms stages. The team mentors undergraduates, graduate students, and postdoctoral researchers in the fields of biochemical oceanography, genome sciences, and time-series multivariate statistics. University of Washington organized hackathons to develop publicly accessible portals for the simplified interrogation and visualization of 'omics data, accessible to high schoolers and undergraduates. These portals are implemented in investigator-led undergraduate teaching modules in the University of Rhode Island Ocean Classroom. The research team also returns to Orcas Island, WA, where the field sampling takes place, to host a series of annual Science Weekends to foster scientific engagement with the local community.\nPhytoplankton blooms, from initiation to decline, play vital roles in biogeochemical cycling by fueling primary production, influencing nutrient availability, impacting carbon sequestration in aquatic ecosystems, and supporting secondary production. In addition to influences from environmental conditions, the physical and chemical interactions among planktonic microbes can significantly modulate blooms, influencing the growth, maintenance, and senescence of phytoplankton. Recent work in steady-state open ocean ecosystems has shown that important chemicals are transferred amongst plankton on time-dependent metabolic schedules that are related to diel cycles. It is unknown how these metabolic schedules operate in dynamic coastal environments that experience perturbations, such as phytoplankton blooms. Here, the investigators are examining metabolic scheduling using long-term, diel sample sets to reveal how chemical and biological signals associated with the initiation, maintenance, and cessation of phytoplankton blooms are modulated on both short (hrs) and long (days-weeks) time scales. Findings are advancing the ability to predict and manage phytoplankton dynamics, providing crucial insights into ecological stability and future oceanographic sampling strategies. Additionally, outcomes of this study are providing a new foundational understanding of the succession of microbial communities and their chemical interactions across a range of timescales. In the long term, this research has the potential to identify predictors of the timing of phytoplankton blooms, optimize fisheries management, and guide future research on carbon sequestration.\n\ncdm_data_type = Other\nVARIABLES:\nDateID_PT (unitless)\n... (33 more variables)\n | BCO-DMO | bcodmo_dataset_984169_v1 | ||||||||||||
| https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_914399_v1 | https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_914399_v1.graph | https://erddap.bco-dmo.org/erddap/files/bcodmo_dataset_914399_v1/ | public | [Microbial eukaryotic diversity: Mid-Cayman Rise SRA dataset] - 18S rRNA amplicon sequencing of microbial eukaryotes from the Mid-Cayman Rise acquired Jan-Feb, 2020 (Probing subseafloor microbial interactions via hydrothermal vent fluids: A focus on protists) | Single-celled microbial eukaryotes inhabit deep-sea hydrothermal vent environments and play critical ecological roles in the vent-associated microbial food web. 18S rRNA amplicon sequencing of diffuse venting fluids from two geochemically-distinct hydrothermal vent fields was applied to investigate community diversity patterns among protistan assemblages. Piccard and Von Damm vent fields are situated 20 km apart at the Mid-Cayman Rise in the Caribbean Sea. We describe species diversity patterns with respect to hydrothermal vent field and sample type, identify putative vent endemic microbial eukaryotes, and test how vent fluid geochemistry may influence microbial community diversity. Individual vent fields supported distinct and highly diverse assemblages of protists that included potentially endemic or novel vent-associated strains. This data adds to our growing knowledge of the biogeography of deep-sea microbial eukaryotes.\n\ncdm_data_type = Other\nVARIABLES:\nExperiment_Accession (unitless)\nExperiment_Title (unitless)\nOrganism_Name (unitless)\nInstrument (unitless)\nStudy_Accession (unitless)\nStudy_Title (unitless)\nSample_Accession (unitless)\nTotal_Size_Mb (Mb)\nTotal_Bases (bp)\nLibrary_Name (unitless)\nLibrary_Strategy (unitless)\nLibrary_Source (unitless)\nLibrary_Selection (unitless)\nVent_field (unitless)\nCollection (unitless)\nVent_name (unitless)\nDiveID (unitless)\n | https://erddap.bco-dmo.org/erddap/info/bcodmo_dataset_914399_v1/index.htmlTable | https://www.bco-dmo.org/dataset/914399
| https://erddap.bco-dmo.org/erddap/rss/bcodmo_dataset_914399_v1.rss | https://erddap.bco-dmo.org/erddap/subscriptions/add.html?datasetID=bcodmo_dataset_914399_v1&showErrors=false&email= | BCO-DMO | bcodmo_dataset_914399_v1 |