Dataset: Gulf of Alaska copepods: annotated transcriptomes

Name: Annotated de novo transcriptomes generated from six co-occurring species of calanoid copepods from the R/V Tiglax TXF18, TXS19, TXF15, TXF17 in the Gulf of Alaska from 2015-2019
Published: 2024-04-01
Keywords: Neocalanus flemingeri, Eucalanus bungii, Calanus marshallae, Metridia pacifica, Neocalanus cristatus, Neocalanus plumchrus, oceans

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Cite This Dataset

Spatial Extent: N:60.6667 E:-147.6667 S:59.845 W:-149.4667

Gulf of Alaska

Temporal Extent: 2015-05-10 - 2019-04-30

Project:

Collaborative Research: Molecular profiling of the ecophysiology of dormancy induction in calanid copepods of the Northern Gulf of Alaska LTER site (Diapause preparation)

Principal Investigator:

Daniel K. Hartline (University of Hawaii at Manoa, PBRC)

Scientist:

Petra H. Lenz (University of Hawaii at Manoa, PBRC)

Contact:

Petra H. Lenz (University of Hawaii at Manoa, PBRC)

Data Manager:

Matthew C. Cieslak (University of Hawaii at Manoa, PBRC)

BCO-DMO Data Manager:

Lynne M. Merchant (Woods Hole Oceanographic Institution, WHOI BCO-DMO)

Version:

Version Date:

2024-04-01

Restricted:

Validated:

Current State:

Preliminary and in progress

Annotated de novo transcriptomes generated from six co-occurring species of calanoid copepods from the R/V Tiglax TXF18, TXS19, TXF15, TXF17 in the Gulf of Alaska from 2015-2019

Abstract:

The dataset includes the annotation files of nine high-quality de novo transcriptomes generated from shotgun assemblies of short-sequence reads. The species are ecologically-important members of sub-arctic North Pacific marine zooplankton communities. The de novo assemblies included one generated several years ago plus eight new ones generated from six co-occurring species of calanoid copepods in the Gulf of Alaska. The transcriptomes include the first published ones for Neocalanus plumchrus, Neocalanus cristatus, Eucalanus bungii and Metridia pacifica and three for Neocalanus flemingeri and two for Calanus marshallae. Total RNA from single individuals was used to construct gene libraries that were sequenced on an Illumina Next-Seq platform. Short-sequence reads were assembled with Trinity software and resulting transcripts were annotated using the SwissProt database with additional functional annotation using gene ontology terms and enzyme function. The annotations files are the first ones published for these species. The integrated database can be used for quantitative inter- and intra-species comparisons of gene expression patterns across biological processes using the annotations. These data are further described in the following publications: Hartline, et al. (2023) (DOI: 10.1038/s41597-023-02130-1), Roncalli, et al. (2022) (DOI: 10.1111/mec.16354), and Roncalli, et al. (2019) (DOI: 10.1038/s42003-019-0565-5)

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Description

These data are further described in the following publications:

Hartline, D. K., Cieslak, M. C., Castelfranco, A. M., Lieberman, B., Roncalli, V., & Lenz, P. H. (2023). De novo transcriptomes of six calanoid copepods (Crustacea): a resource for the discovery of novel genes. Scientific Data, 10(1). https://doi.org/10.1038/s41597-023-02130-1

Roncalli, V., Niestroy, J., Cieslak, M. C., Castelfranco, A. M., Hopcroft, R. R., & Lenz, P. H. (2022). Physiological acclimatization in high‐latitude zooplankton. Molecular Ecology, 31(6), 1753–1765. Portico. https://doi.org/10.1111/mec.16354

Roncalli, V., Cieslak, M. C., Germano, M., Hopcroft, R. R., & Lenz, P. H. (2019). Regional heterogeneity impacts gene expression in the subarctic zooplankter Neocalanus flemingeri in the northern Gulf of Alaska. Communications Biology, 2(1). https://doi.org/10.1038/s42003-019-0565-5

Methods & Sampling

Sample collection: Zooplankton were collected from depth (2015, 2017, 2018, and 2019) at two stations in Prince William Sound: “PWS2” (Lat: 60°32′. N, Long: -147°48.2′ W) and “PWS3” (Lat: 60°40.0′ N, Long: -147°40.0′ W,) and the Gulf station “GAK1” (Lat: 59º50.7′ N, Long: -149º28′ W). Collection date, station and depth stratum for each individual are given in Hartline et al. (2023) and Roncalli et al. (2019). Zooplankton collections were made using vertical net tows with either a QuadNet with two 150 µm and two 53 µm mesh nets (April and May collections), or a multiple opening and closing plankton net (0.25 m2 cross-sectional area; 150 μm mesh nets; Multinet-Midi, Hydro-Bios; September collections). Zooplankton samples were diluted, and copepods were sorted under a dissection microscope to select individuals from the target species. Briefly, live and undamaged individuals were identified and staged using morphological criteria and preserved in RNALater Stabilization Reagent. Preserved copepods were frozen first in -20ºC during the cruises, and then transferred to −80°C until further processing. Species identification were confirmed through the COI sequence in the assembled transcriptomes.

Total RNA extraction, library construction, RNA sequencing and quality control: For each target species, total RNA was extracted from individuals using QIAGEN RNeasy Plus Mini Kit (catalog # 74134) in combination with a Qiashredder column (catalog # 79654). Selection for sequencing was based on high RNA yields and purity of extraction (RIN>8). The final list included pre-adults (CV) for Neocalanus flemingeri (n=3), Neocalanus cristatus (n=1), Calanus marshallae (n=2), Eucalanus bungii (n=1), an adult male (developmental stage CVI) for Neocalanus plumchrus (n=1) and an adult female for Metridia pacifica (n=1). Total RNA was shipped on dry ice to the Georgia Genomics Bioinformatics Core (https://dna.uga.edu) for RNA-Seq. There, double-stranded cDNA libraries (KAPA Stranded mRNA-Seq Kit, with KAPA mRNA Capture Beads (cat #KK8421]) from each individual were multiplexed and sequenced using an Illumina Next-Seq 500 instrument (High-Output Flow Cell, 150 bp, paired end). Quality of each RNA-Seq library was reviewed with the FastQC software28. From each RNA-Seq library, low quality reads were removed using FASTQ Toolkit (v. 2.2.5 within BaseSpace). Illumina adaptors, reads <50 bp long, reads with an average Phred score <30 and the first 12 bp from each read, were removed from each library. The same workflow was applied to all nine datasets.

Data Processing Description

De novo assembly, mapping, core-gene statistics: Individual de novo transcriptomes were generated from each RNA-Seq dataset at the National Center for Genome Analysis Support's (NCGAS; Indiana University, Bloomington, IN, USA) Mason Linux cluster using Trinity software (v. 2.4.0, except N. plumchrus, v. 2.0.6). Initial evaluation involved self-mapping of reads against the respective de novo assembly using Bowtie2 software (v. 2.3.5.1). Completeness of each de novo assembly was evaluated using Benchmarking Universal Single-Copy Orthologs (BUSCO) software31 by searching each assembly for the presence of eukaryote “core” genes using the Arthropoda database as reference (BUSCO version 5.3.2, dataset: arthropoda_odb10 (2020-09-10, 90 genomes, 1,013 BUSCOs). RNA-Seq data and transcriptome shotgun assemblies (TSAs) have been deposited with links to BioProject accession numbers PRJNA496596, and PRJNA662858 in the NCBI (National Center for Biotechnology Information) BioProject database (https://www.ncbi.nlm.nih.gov/bioproject/).

Functional annotation: Assemblies were functionally annotated against the NCBI Swiss-Prot protein and UniProt databases. Initial annotations were obtained by using the BLASTx algorithm on a local BLAST webserver with a Beowulf cluster using the Swiss-Prot protein database (downloaded February 2021) as reference and a threshold E-value of 10-5. Transcripts with BLAST annotations were then searched against the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway databases using UniProt.

BCO-DMO Processing

# Processing of submitted annotated individual transcriptome files and metadata

* Submitted annotated transcriptome files
Filename: n-flem_CV2015_GAK1_AccAnnots_multispp_Aug23_q-fix-2.csv
Description: Neocalanus flemingeri, annotated transcriptome #1

Filename: Nf2018_CV_Acc&Annot-single-rev_quoted.csv
Description: Neocalanus flemingeri, annotated transcriptome #2

Filename: Nf2019_CV-PWS2_Acc&Annot.csv
Description: Neocalanus flemingeri, annotated transcriptome #3

Filename: Np2015_maleR1_Acc&Annot.csv
Description: Neocalanus plumchrus, annotated transcriptome, adult male

Filename: Nc2017_CV_Acc&Annot.csv
Description: Neocalanus cristatus, annotated transcriptome

Filename: Cm2017_CV_Acc&Annot.csv
Description: Calanus marshallae, annotated transcriptome #1

Filename: Cm2018_CV_Acc&Annot.csv
Description: Calanus marshallae, annotated transcriptome #2

Filename: Eb2017_CV_Acc&Annot.csv
Description: Eucalanus bungii, annotated transcriptome

Filename: Mp2017_AF_Acc&Annot.csv
Description: Metridia pacifica, annotated transcriptome, adult female

* The metadata table with NCBI accessions was created using information from the submitter and by gathering accession numbers from NCBI for the BioProjects.

Metadata from Submitter via email:
File Name: Summary Table for the Annotated Transcriptomes in BCO.docx
Title: Summary table from Lenz of metadata for transcriptome annotation files

Table columns
Species: Species of the collected organisms
Annot Filename: Name of the submitted annotated transcriptomes file
Stage/Collection information: Life Stage, Sex if indicated, Collection date, station, depth range in meters
NCBI TSA#: NCBI TSA project accession

Fixes: Changed GHLB01000000 to GHLB00000000 because the TSA project master records accessions begin with a four-letter prefix of the TSA project followed by eight zeroes

* Clarifying metadata values with submitter

Looking at corresponding NCBI BioSample records, the depth listed is not within the collection depth range listed in the file “Summary Table for the Annotated Transcriptomes in BCO.docx”. To clarify this difference, I emailed a spreadsheet with both the BioSample depth listed and the depth ranges given. From correspondence, the BioSample depth refers to the depth of the water column at a station lat and lon and not the collection depth range of a plankton net. So the BioSample depth values are not used in the metadata table.

File name: transcriptomes_species_date_station_depth_table-PL-1.xlsx
Title: Submitter modified version of DM created metadata file

# Using the BCO-DMO data processor laminar, load in submitted annotated transcriptomes files and the DM created metadata table. Keep the fill value '#N/A' which stands for 'no result found'.

* Data Manager (DM) created metadata table used :

File name: transcriptome_annotations_metadata_table.csv
Title: DM created metadata table of supporting information for each transcriptome annotation

Station lat and lon values retrieved from the 'Methods & Sampling' section of the submission tool. They were then converted to decimal degrees with 4 digit precision.

A column TSA_project_accession was included to join the metadata table with the annotated transcriptome files later in processing, and is removed in the final metadata table.

From the National Center for Biotechnology Information (NCBI), various accession numbers, titles, and urls were located for each annotated transcriptome file.

Table columns:
Species, Station, Latitude, Longitude, date, Depth_range, Maximum_depth, Life_stage, Sex, TSA_project_accession, TSA_master_accession, SRA_accession, Experiment_title, Experiement_accession, BioSample, Sample_accession, Study_title, Study_accession, BioProject

- Create a new column for each annotated transcriptome file, TSA_project_accession, to join on the metadata table using regular expressions to extract the first 4 letters of each TSA accession number and then concatenate 8 zeros. This is the NCBI format for a TSA project accession number.

- Join each annotated transcriptome file with the metadata table on the key TSA_project_accession.

- Remove the parameter TSA_project_accession, since it was only used for the Join process. The TSA project accession number with the version is already recorded as the parameter TSA_master_accession.

- Add a suffix ‘.1’ to each TSA accession number to indicate version 1.

- Rename Accession# to Genbank_accession which is the TSA accession value with a version.

- Rename parameters in each annotated transcriptome file by removing commas and parentheses. And replacing spaces with underscores to follow BCO-DMO parameter naming conventions.

- Reorder the parameters so that experiment metadata parameters are at the beginning of each annotated transcriptome file and most NCBI accession numbers are at the end

- Using a second laminar processor pipeline, load in the individual annotated transcriptomes files that were created by laminar processing above and concatenate all the individual annotated transcriptome files into the primary dataset file.

More Information about this dataset

Funding Sources

Funding Source	Award Number
NSF Division of Ocean Sciences	OCE-1756767
NSF Division of Ocean Sciences	OCE-1459235
NSF Division of Ocean Sciences	OCE-1756859

Deployments

Deployment	Synonyms	Start Date	Platform	Investigator
TXF15		2015-09-09	R/V Tiglax	Russell R. Hopcroft (Chief Scientist)	data info
TXF17		2017-09-09	R/V Tiglax	Russell R. Hopcroft (Chief Scientist)	data info
TXF18	TGX201809	2018-09-11	R/V Tiglax	Russell R. Hopcroft (Chief Scientist)	data info
TXS15		2015-05-05	R/V Tiglax	Russell R. Hopcroft (Chief Scientist)	data info
TXS19	TGXS19 TGX201904	2019-04-26	R/V Tiglax	Russell R. Hopcroft (Chief Scientist)	data info

Instruments

Automated DNA Sequencer

Supplied Name: Illumina Next-Seq 500

Supplied Description:

Desktop sequencer

Instrument Type

Generic Name: Automated DNA Sequencer

Acronym: Automated Sequencer

Generic Description:

General term for a laboratory instrument used for deciphering the order of bases in a strand of DNA. Sanger sequencers detect fluorescence from different dyes that are used to identify the A, C, G, and T extension reactions. Contemporary or Pyrosequencer methods are based on detecting the activity of DNA polymerase (a DNA synthesizing enzyme) with another chemoluminescent enzyme. Essentially, the method allows sequencing of a single strand of DNA by synthesizing the complementary strand along it, one base pair at a time, and detecting which base was actually added at each step.

Microscope - Optical

Supplied Name: Dissection microscope

Supplied Description:

An optical microscope variant

Instrument Type

Generic Name: Microscope - Optical

Community Identifier: http://vocab.nerc.ac.uk/collection/L05/current/LAB05/

Generic Description:

Instruments that generate enlarged images of samples using the phenomena of reflection and absorption of visible light. Includes conventional and inverted instruments. Also called a "light microscope".

MultiNet

Supplied Name: Multinet-Midi, Hydro-Bios

Supplied Description:

Hydro-Bios Multinet-Midi with a 0.25 m2 cross-sectional area and 150 μm mesh

Instrument Type

Generic Name: MultiNet

Community Identifier: http://vocab.nerc.ac.uk/collection/L22/current/NETT0099/

Generic Description:

The MultiNet© Multiple Plankton Sampler is designed as a sampling system for horizontal and vertical collections in successive water layers. Equipped with 5 or 9 net bags, the MultiNet© can be delivered in 3 sizes (apertures) : Mini (0.125 m2), Midi (0.25 m2) and Maxi (0.5 m2). The system consists of a shipboard Deck Command Unit and a stainless steel frame to which 5 (or 9) net bags are attached by means of zippers to canvas. The net bags are opened and closed by means of an arrangement of levers that are triggered by a battery powered Motor Unit. The commands for actuation of the net bags are given via single or multi-conductor cable between the Underwater Unit and the Deck Command Unit. Although horizontal collections typically use a mesh size of 300 microns, mesh sizes from 100 to 500 may also be used. Vertical collections are also common. The shipboard Deck Command Unit displays all relevant system data, including the actual operating depth of the net system.

Plankton Net

Supplied Name: QuadNet

Supplied Description:

Two 150 µm and two 53 µm mesh nets

Instrument Type

Generic Name: Plankton Net

Community Identifier: http://vocab.nerc.ac.uk/collection/L05/current/22/

Generic Description:

A Plankton Net is a generic term for a sampling net that is used to collect plankton. It is used only when detailed instrument documentation is not available.

Parameters

Date and time formats are described in python strftime() syntax.

Supplied Name	Supplied description	Supplied Units	Standard Name
seq_id	The Trinity software names assembled by Trinity software are named hierarchically grouping sequences by similarity	unitless	sequence
Genbank_accession	NCBI (National Center for Biotechnology Information) Accession number for nucleotide sequence in the Transcriptome Shotgun Assembly (TSA) Sequence Database. The accession number is a unique identifier assigned to a record in the sequence database GenBank at NCBI. It is of the format [alphabetical prefix][series of digits].[version]. A change in the record is tracked by an integer extension of the accession number, an Accession.version identifier. The initial version of a sequence has the extension “.1”.	unitless	Genbank_accession
Genbank_accession_url	URL of the GenBank accession	unitless	external_link
TSA_Master_Accession	NCBI (National Center for Biotechnology Information) Accession number for the Transcriptome Shotgun Assembly (TSA) master record. The accession number is a unique identifier assigned to a master record in the database GenBank at NCBI. It is of the format [alphabetical prefix][00000000].[version]. A change in the record is tracked by an integer extension of the accession number, an Accession.version identifier. The initial version of a sequence has the extension “.1”.	unitless	accession_number
Species	A taxonomic binomial that consists of a genus name followed by the species name	unitless	species
Station	Station identifier	unitless	station
Latitude	Sampling location latitude, south is negative	decimal degrees	lat
Longitude	Sampling location longitude, west is negative	decimal degrees	lon
Collection_date	Collection date of organism Format: %Y-%m-%d	unitless	date
Depth_range	Collection depth range	meters (m)	depth_r
Maximum_depth	Maximum depth of collection area	meters (m)	depth_bottom
Life_stage	Organism life history stage	unitless	stage
Sex	sex	unitless	sex
Entry	Uniprot KB entry identifies the top BLAST (Basic Local Alignment Search Tool) hit sequence to the assembled nucleotide sequence, searches were conducted using the blastx algorithm, #N/A indicates that there was no positive BLAST hit that met the e-value threshold	unitless	sequence
Entry_name	Uniprot entry name for the top hit, #N/A = no hit	unitless	no_bcodmo_term
evalue	Expected probability, e-value is the number of expected hits of similar quality (score) that could be found just by chance, cut-off value used for the annotation: E-value = 10-5, #N/A = no hit	unitless	no_bcodmo_term
Protein_names	Protein names, #N/A = no hit	unitless	protein_ID
Gene_names	Gene name based on the reference genome of the top hit, #N/A = no hit	unitless	no_bcodmo_term
Organism	Species name of top hit sequence, #N/A = no hit	unitless	species
Cross_reference_KEGG	KEGG identification based on the cross-reference of protein annotation and the Kyoto Encyclopedia of Genes and Genomes database, #N/A = no hit	unitless	no_bcodmo_term
Gene_ontology_IDs	GO terms based on cross-reference of protein annotation to the Gene Ontology Resource for functional identification as to Biological Process (BP), Cellular Component (CC) and Molecular Function (MF), proteins are typically involved in multiple processes, #N/A = no hit	unitless	no_bcodmo_term
Gene_ontology_GO	Identification of GO term with a functional description, #N/A = no hit	unitless	no_bcodmo_term
Gene_ontology_biological_process	Gene ontology terms and descriptions associated with Biological Process, #N/A = no hit	unitless	no_bcodmo_term
Gene_ontology_cellular_component	Gene ontology terms and descriptions associated with Cellular Component, #N/A = no hit	unitless	no_bcodmo_term
Gene_ontology_molecular_function	Gene ontology terms and descriptions associated with Molecular Function, #N/A = no hit	unitless	no_bcodmo_term

Database

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Dataset: Gulf of Alaska copepods: annotated transcriptomes