Abstract:
Transcriptomic analyses were undertaken on both in situ collected and experimentally warmed blue mussels (Mytilus edulis) from Greenland. M. edulis were collected from the Godthabsfjorden near Nuuk, Greenland (64.45555, -51.14416) at the following locations and dates: Inner fjord (64.45941, -50.31030) on 11/06/2018; outer fjord (64.19666, -51.69) on 13/06/2018, and sub-tidal (64.19666, -51.69) on 13/06/2018 (outer fjord at 20-40cm below the lowest low water mark). The in situ collected inner and outer fjord intertidal animals with outer fjord subtidal animals used as controls were collected at 27 degree Celsius, 19 degree Celsius and 3 degree Celsius, respectively. Some of the outer fjord subtidal M. edulis were experimentally warmed to 22 degree Celsius and 32 degree Celsius for one hour to mimic high aerial exposure temperatures in the inner and outer fjord intertidal, respectively. RNA-Seq was performed on 5 animals for each treatment, with all subsequent bioinformatics analyses performed by Novogene, China.
This work was supported by the Carlsberg Foundation, the Independent Research Fund Denmark (Danmarks Frie Forskningsfond) (DFF-International Postdoc; case no. 7027-00060B), a Marie Sklodowska-Curie Individual Fellowship (IF) under contract number 797387 and Aage V. Jensens Fond (Aage V. Jensens Foundation) and NERC-UKRI core funding to the British Antarctic Survey.
Keywords:
HSP70, Mytilus edulis, blue mussel, cellular stress response, climate change, thermal tolerance
Clark, M., Peck, L., & Thyrring, J. (2020). Resilience in Greenland intertidal Mytilus: The hidden stress defense (Version 1.0) [Data set]. UK Polar Data Centre, Natural Environment Research Council, UK Research & Innovation. https://doi.org/10.5285/26ddb511-3050-4d87-9e13-d034262ca566
| Access Constraints: | No restrictions on data access. |
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| Use Constraints: | Data released under Open Government Licence V3.0: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/. |
| Creation Date: | 2020-11-17 |
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| Dataset Progress: | Complete |
| Dataset Language: | English |
| ISO Topic Categories: |
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| Parameters: |
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| Personnel: | |
| Name | UK PDC |
| Role(s) | Metadata Author |
| Organisation | British Antarctic Survey |
| Name | Prof Melody S Clark |
| Role(s) | Investigator |
| Organisation | British Antarctic Survey |
| Name | Prof Lloyd S Peck |
| Role(s) | Investigator |
| Organisation | British Antarctic Survey |
| Name | Dr Jakob Thyrring |
| Role(s) | Investigator |
| Organisation | University of British Columbia |
| Parent Dataset: | N/A |
| Reference: | Clark MS, Peck LS, Thyrring J (2021). Resilience in Greenland intertidal Mytilus: The hidden stress defense. Science of the Total Environment 767, 144366. https://doi.org/10.1016/j.scitotenv.2020.144366 Altschul SF, Madden TL, Schaffer AA, Zhang JH, Zhang Z, Miller W, Lipman DJ. (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Research 25:3389-3402. Benjamini Y, Hochberg Y. (1995) Controlling the false discovery rate - A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society Series B-Statistical Methodology 57:289-300. Buchfink B, Xie C, Huson DH. (2015) Fast and sensitive protein alignment using DIAMOND. Nature Methods 12:59-60. Finn RD, Tate J, Mistry J, Coggill PC, Sammut SJ, Hotz HR, Ceric G, Forslund K, Eddy SR, Sonnhammer ELL, et al. (2008) The Pfam protein families database. Nucleic Acids Research 36:D281-D288. Goetz S, Garcia-Gomez JM, Terol J, Williams TD, Nagaraj SH, Nueda MJ, Robles M, Talon M, Dopazo J, Conesa A. (2008) High-throughput functional annotation and data mining with the Blast2GO suite. Nucleic Acids Research 36:3420-3435. Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, Adiconis X, Fan L, Raychowdhury R, Zeng QD, et al. (2011) Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nature Biotechnology 29:644-U130. Kanehisa M, Araki M, Goto S, Hattori M, Hirakawa M, Itoh M, Katayama T, Kawashima S, Okuda S, Tokimatsu T, et al. (2008). KEGG for linking genomes to life and the environment. Nucleic Acids Research 36:D480-D484. Li B, Dewey CN. (2011) RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12:323. Mao XZ, Cai T, Olyarchuk JG, Wei LP. (2005) Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary. Bioinformatics 21:3787-3793. Moriya Y, Itoh M, Okuda S, Yoshizawa AC, Kanehisa M. (2007) KAAS: an automatic genome annotation and pathway reconstruction server. Nucleic Acids Research 35:W182-W185. Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, Simonovic M, Doncheva NT, Morris JH, Bork P, et al. (2019) STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Research 47:D607-D613. Wang LK, Feng ZX, Wang X, Wang XW, Zhang XG. (2010) DEGseq: an R package for identifying differentially expressed genes from RNA-seq data. Bioinformatics 26:136-138. Young MD, Wakefield MJ, Smyth GK, Oshlack A. (2010). Gene ontology analysis for RNA-seq: accounting for selection bias. Genome Biology 11:R14. |
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| Lineage: | 25 individuals were sequenced from the 5 sets of sampling/experimental work detailed above. All analyses were performed by Novogene and comprised the following stages and application of software packages. Raw reads were quality controlled for error rate using Phred and GC content using the Illumina CASAVA v1.8 software. Reads were cleaned with the removal of Illumina kit adapter sequences and adapter contamination, where the level of uncertain nucleotides N > 10% and where low quality bases as defined by the Phred Q20 score constituted more than 50% of a read. De novo transcriptome assembly was performed using Trinity version r20140413p1 with parameters min_kmer_cov=2, min_glue=2, others were set to default, using the modules Inchworm, Chrysalis and Butterfly (Grabherr et al., 2011). Hierarchical clustering was performed using the Corset program in Trinity to remove read redundancy. The longest transcripts from each cluster were selected as unigenes. Annotation of the unigenes was performed using seven databases (NR, NT, KO, SwissProt, Pfam, Go and KOG). Blast searching against NT was performed using NBCI blast 2.2.28+ with an e-value threshold of 1e-5 (Altschul et al., 1997). Diamond v0.8.22 (Buchfink et al., 2015) was used to blast search the unigenes against NR, SwissProt and KOG. The e-value threshold for NR and SwissProt was 1e-5 and 1e-3 for KOG. Pfam (Finn et al., 2008) was screened using the hmmscan package in HMMER v3.1b1 with an e-value threshold of 0.01. GO annotation was based on the protein annotation results from NR and Pfam using Blast2GO vb2g4pipe_2.5 (Goetz et al., 2008; Young et al., 2010) with an e-value threshold of 1e-6. KEGG mapping was performed using KAAS (KEGG Automated Annotation Server) v.r140224 with an e-value threshold of 1e-8 (Mao et al., 2005; Moriya et al., 2007; Kanehisa et al., 2008). GO enrichment was performed using GOSeqtopGO vGOSeq 1.32.0, topGO-2.32.0) with a corrected p value of <0.05. KEGG enrichment was performed using KOBAS v3.0 with a corrected p value of <0.05. The de novo transcriptome was used as a reference assembly and the reads from each library mapped back to the transcriptome and quantified using Bowtie2 vbowtie2-2.2.2.2 and RSEM vRSEM-v1.3.0 (Li et al., 2011) with output referenced as FPKM (Fragments Per Kilobase of transcript sequence per Million base pairs sequenced). The threshold for expression was set at FPKM >3.0. Differential expression between the different sets of samples was calculated using DEGseq v1.12.0 (Wang et al., 2010) with normalization via TMM and FDR calculated using BH (Benjamini and Hochberg, 1995) with output threshold of log2fold change >1 and adjusted p value <0.005. Protein gene identifiers were extracted from the SwissProt annotations for the MI v. MO differential expression analysis for analysis via the STRING v11 program (https://string-db.org/) to visualize protein-protein interactions (Szklarczyk et al., 2019). | |
| Temporal Coverage: | |
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| Start Date | 2018-06-01 |
| End Date | 2018-06-30 |
| Spatial Coverage: | |
| Latitude | |
| Southernmost | 64.19666 |
| Northernmost | 64.45941 |
| Longitude | |
| Westernmost | -51.69 |
| Easternmost | -50.3103 |
| Altitude | |
| Min Altitude | N/A |
| Max Altitude | N/A |
| Depth | |
| Min Depth | N/A |
| Max Depth | N/A |
| Location: | |
| Location | Arctic |
| Detailed Location | Greenland, Godthåbsfjorden near Nuuk |
| Data Storage: | Six .cvs files. The first six columns of each table are very similar. The first column contains the Trinity gene identifier, the next two columns are the expression levels of the two conditions under study, followed by the log2foldchange, the p value and the adjusted p value (padjust). Condition identifiers: MI: animals sampled in situ from the inner fjord region MO: animals sampled in situ from the outer fjord region MC: animals taken from the outer fjord subtidal region which were used as the control for most bioinformatics comparisons 22: animals taken from the outer fjord subtidal region and experimentally warmed at 22 degree Celsius for 1 hour. 32: animals taken from the outer fjord subtidal region and experimentally warmed at 32 degree Celsius for 1 hour. 1: Novogene annotation: Full set of gene annotations (as described above), as provided by Novogene. 2: Upregulated transcripts 22 v MC with NR and SwissProt annotation, as provided by Novogene. 22 v MC = 22 degree Celsius experimentally warmed samples compared with control animals. 3: Upregulated transcripts 32 v MC with NR and SwissProt annotation, as provided by Novogene. 32 v MC = 32 degree Celsius experimentally warmed samples compared with control animals. 4: Upregulated transcripts MI v MC with NR and SwissProt annotation, as provided by Novogene. MI v MC = Inner fjord in situ collected samples compared with control animals. 5: Upregulated transcripts MO v MC with NR and SwissProt annotation, as provided by Novogene. MO v MC = Outer fjord in situ collected samples compared with control animals. 6:Upregulated transcripts MI v MO for STRING with NR and SwissProt annotation, as provided by Novogene. MI v MO = Inner fjord in situ collected samples compared with outer fjord in situ collected samples and SwissProt gene name symbols extracted from SwissProt annotations and identifiers. |
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