Data for Saccharina latissima RNA seq experiment
Data files
Nov 04, 2024 version files 23.56 KB
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CommonGardenExperiment_metadata.xlsx
9.94 KB
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DescriptionOfRawdata.xlsx
10.31 KB
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README.md
3.32 KB
Abstract
Sugar kelp (Saccharina latissima) is an ecologically and increasingly economically important kelp, distributed from temperate to Arctic rocky shores. However, S. latissima is presently threatened by ongoing climate changes. Genetic variations have previously been identified across S. latissima populations. However, little is known regarding the genetic basis for adaptation and acclimation to different environmental conditions.
In this study, a common garden experiment was performed with sporophytes originating from North-Norway (NN), Mid-Norway (MN), and South-Norway (SN), representing areas with highly different temperatures and photoperiods. Transcriptomic analyses revealed significant variation in the gene expression of cultures from North-Norway, associated with low temperature and long photoperiods, compared to Mid- and South-Norway. Genes that were differentially expressed under different photoperiod and temperature conditions included genes linked to photosynthesis, chlorophyll biosynthesis, heat response, growth, protein synthesis, and translation. However, the transcriptional responses to variations in photoperiod and temperature differed between different populations of S. latissima (NN, MN, and SN), indicating genotypic adaptations. Overall, our study provides deeper insight into the local adaptations of S. latissima populations along the Norwegian Coast with implications for the conservation of natural populations.
README: Data for Saccharina latissima RNA seq experiment
File: CommonGardenExperiment_metadata.xlsx
Description
Metadata associated with a Common Garden Experiment involving three populations of Saccharina latissima (sugar kelp). The populations were obtained from North-Norway (i.e. Tromso), Mid-Norway (i.e. Trondheim), and South-Norway (i.e. Bergen). Growth experiments were conducted in the laboratory under conditions mimicking the in situ temperatures and photoperiod for each population. At the end of each growth experiments RNA was extracted using 3-5 replicates. Sequencing of RNA was performed with Illumina paired-end sequencing.
This resulted in 70 fastq files aviable from SRA (PRJNA1164979) (3 populations x 3 conditions x (3-5)replicates x 2(paired end) = 70).
Reads were mapped to a reference genome of S. latissima available from the Phaeoexplorer Database (ANR-10-INBS-09).
Variables
- Sample for RNAseq analyses: This indicates the source of the population and the growth conditions. E.g. 'Slatissima_Tromso_TrondheimCondition' is a sample of S. latissima grown under Trondheim conditions
- Organism: Species name (i.e. S. latissima)
- Source of population: The area along the Norwegian coast the population was collected from.
- Sporophyte age at time of sampling for RNAseq: The age of the Sporophytes at the end of the growth experiment (at the time of sampling for RNAseq).
- Date of sampling for RNAseq: Date of ampling for RNAseq
- Growth stage at the time of sampling for RNAseq: Growth stage of S. latissima at the time of sampling for RNAseq
- Population collected by: Name of person collecting each population of S. latissima.
- Geolocation of population sampling: Geographical coordinates of source of the three S. latissima populations.
- Temperature (degC) in common garden experiment: Growth condition (Temperature in degrees Celsius) in the growth experiment
- Photoperiod (hours of light) in Common Garden Experiment: Growth condition (hours of light per day) in growth experiment.
File: DescriptionOfRawdata.xlsx
Raw data are available from Sequence Read Archive (SRA) under accession number PRJNA1164979.
Variables
- Sample for RNAseq analyses: Same as in the CommonGardenExperiment_metadata.xlsx file. The name indicates the source of the population and the growth conditions. E.g. 'Slatissima_Tromso_TrondheimCondition' is a sample of S. latissima grown under Trondheim conditions
- SampleID: ID of one RNA extraction (there are replicate RNA extractions from each experiment)
- Description: All data is RNA-Seq of Saccharina latissima (sporohytes)
- Sequencer: All sequences are derived from sequencing with Illumina HiSeq 4000
- Filename: Filename of each raw data file. Each file can be downloaded from SRA (PRJNA1164979)
File: Trimming.sh
Script for trimming paired end reads with Trim Galore.
File: Mapping.sh
Script for mapping reads to reference genome using STAR.
File: FeatureCounts.sh
Command used for gene counting
File: DESeq2-DGE-analysis-MBR.qmd
DESeq2 pipeline for identification and analyses of differentially expressed genes.
File: topGO_analyses_R.txt
R script for enrichment analysis of Gene Ontology (GO)
terms using topGO.
Methods
A common garden experiment (CGE) was carried out between 2 February – 13 March 2018 at the University of Bergen, with material of S. latissima collected in North-Norway (69° 38’ N, 18° 57’ E) (NN), Mid-Norway (63° 43’ N, 8° 49’ E) (MN) and South-Norway (60° 16’ N, 5° 13’ E) (SN). Tissue pieces carrying mature sori with sporangia were cut from 10-12 Saccharina latissima, collected at 1-5 m depth between 8-12 January 2018 at all three sites in Norway. The material from NN and MN was wrapped up in moist paper with cooling elements and transported to the laboratory and seeded the day of arrival, during two successive days. The tissue with sori was treated as described in Forbord et al. (2018) to prevent diatom growth in the cultures, and thereafter submerged in beaker glasses with cool (12°C) sterile sea water and stirred until spore release was observed using microscope. The spore solution was applied to tagged, clean and heat-treated granite stones (10x10 cm). After 10 min exposure to spore solution the stones were placed in sterile sea water. The material from SN was kept in moist paper in a fridge overnight to provoke spore release and was otherwise treated as described by Forbord et al. (2018). Additional plates for checking development of each culture were seeded in the same way.
The seeded stones were transferred to a climate room. Each batch of gametophytic culture (NN, MN and SN) was grown in separate tanks with running sea water, but with similar photon fluence rates (around 50 µE m-2s-1, measured with a spherical sensor) and temperature (9-10°C) conditions. The running sea water of the climate rooms is from 100 m depth, filtered through a sand filter, and treated with UV light. The development of each culture batch was checked regularly, and 1 February minute sporophytes were observed in all three batches.
The CGE was carried out in a climate room divided into three compartments through complete enclosures of black and opaque plastic, where each compartment had two tanks (30 cm x 50 cm x 25 cm (height)) with running seawater, representing replicates. The conditions of the three compartments were set to mimic temperature and day-length conditions of NN, MN and SN in mid-May: NN with 4°C and 24 h light, MN with 6°C and 19 h light and SN with 9°C and 17 h light. The temperature conditions are within the ranges measured in April-May in the three regions by Forbord et al. (2020) or in mid-May according to Sætre (1973), which represent a period of rapid growth of S. latissima. The granite stones with growing sporophytes were added to the tanks with three stones in each, representing NN, MN and SN genotypes. Flow rate of running sea water was about 1 L per 20 sec in all the tanks, and photon fluence rates were kept at similar levels (46-50 µE m-2s-1). The tanks were rinsed regularly to prevent diatom growth, and temperatures of the tanks were checked every second or third day and adjusted when needed. Small variations normally within 1°C occurred during the experiment. On termination the stones were photographed, and two or three of the largest sporophytes per stone were sampled, put on RNA-later in a fridge overnight, and frozen at -80°C.
RNA-seq library / dataset
Total RNA was extracted from the flash frozen kelp tissue using 2% CTAB and 2M DTT, followed by separation of DNA/RNA from lipids and proteins using chloroform:isoamyl alcohol (24:1). The supernatant was removed, precipitated using isopropanol, pelleted, and washed with absolute alcohol, and finally resuspended in Low TE buffer. Isolation of RNA from extractions was achieved by removing DNA using the TURBO DNA-free™ Kit (Invitrogen). Extracted RNA quality and quantity was checked using a Qubit RNA HS kit and Agilent RNA HS kit on a 4200 TapeStation System.
RNA libraries were constructed using the NEBNext® Ultra II RNA RNA Library Prep Kit for Illumina® (New England Biolabs) and quality checked using the Agilent 4200 TapeStation System. Paired-end sequencing (2x75bp) of transcriptomes was performed on an Illumina HiSeq4000, giving ca. 30 million reads per sample.
RNA-seq data was available from 35 samples. Within the RNA-seq subset, sample replicates were categorized according to genotype and temperature/light conditions. Specifically, for the SN genotype there were 4 samples each at 6°C/19 h and 4°C/24 h, along with 3 reference samples at 9°C/17 h. For the MN genotype, the sample distribution was 3 samples at 9°C/17 h, 5 samples at 4°C/24 h and 5 reference samples at 6°C/19 h. For the NN genotype there were 3 reference samples at 4°C/24 h, 4 samples at 6°C/19 h, and 4 samples at 9°C/17 h. Transcripts were aligned to a reference genome obtained through the France Génomique National infrastructure project Phaeoexplorer (ANR-10-INBS-09).
Bioinformatics analysis
To assess the quality of the raw sequencing reads, the quality control software FastQC (version 0.11.9) was used. The reads were trimmed using Trim Galore (version 0.6.6). Minimum read length before cutoff were set to 60 bp since shorter reads often have low qualities (Krueger, 2015). Trim Galore was run with default setting, i.e. a Phredscore threshold of 20 and a maximum error rate of 0.1 to obtain clean reads of high quality. MultiQC was used to summarize the results from the read quality trimming done with Trim Galore (Ewels et al., 2016). Trimmed reads were aligned to the reference genome of S. latissima using STAR (version 2.7.10a) (Dobin et al., 2015; Denoeud et al., 2024). Prior to alignment, the reference genome was indexed by running --runmode genomeGenerate. No Gene Transer Format (GTF) file was available and the provided General Feature Format (GFF) file was formatted in STAR to avoid problems when running sequence alignment. This was solved by replacing --sjdbGTFfile with --sjdbGTFtagExonParentTranscript. The setting instructs STAR to use “Parent” tag in the GFF-file to link exons to transcripts. The featureCounts software (version 2.0.1) was used to count the number of reads mapping to each gene in the Saccharina latissimi reference genome. Pairwise comparisons of differential gene expression were performed using DESeq2 (version 1.34.0) (Love et al., 2014). Reference replicates were compared against replicate groups with same genotype under different conditions. An absolute LFC (log2FoldChange) of ≥ 2 and a p-value of < 0.05 was used as thresholds to determine the significance in gene expression between groups. The identifier from the GFF-file was used to find annotation from Interproscan. A GO enrichment analysis was carried out using topGO (version 2.46.0) to identify overrepresented GO-terms.