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Bibliography: Transcriptome responses to salinity shifts in algae and bacteria - A global warming induced salinity shift study
Dillon Brownell, Jeremy Jacobson, and Sally Grindstaff
Background:
Chrysochromulina tobin (C. tobin) is a vital part of coastal ecosystems. It functions as primary producer and is associated with an 8-membered bacterial cohort.
This bacterial cohort is responsible for unknown changes in algal gene expression, however it is known to make algae more robust to increases in salinity.
As climate change is expected to cause alterations in precipitation patterns, coastal ecosystems will likely experience salinity shifts - this research may
predict the response of C. tobin and it’s bacterial cohort. C. tobin also has potential for biofuel production due to its high lipid content. Exploration of
gene expression in lipid production pathways may be informative for large-scale algae farms.
Software:
1. A. Alexa, J. Rahnenfuhrer, topGO: Enrichment Analysis for Gene Ontology (Bioconductor version: Release (3.13), 2021; https://bioconductor.org/packages/topGO/).
topGO: Enrichment Analysis for Gene Ontology
2. S. F. Altschul, W. Gish, W. Miller, E. W. Myers, D. J. Lipman, Basic local alignment search tool. Journal of Molecular Biology. 215, 403–410 (1990).
Basic local alignment search tool (BLAST)
3. S. Anders, P. T. Pyl, W. Huber, HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics. 31, 166–169 (2015).
HTSeq—a Python framework to work with high-throughput sequencing data
4. S. Andrews, FastQC: A Quality Control Tool for High Throughput Sequence Data (2010; http://www.bioinformatics.babraham.ac.uk/projects/fastqc/).
FastQC: A Quality Control Tool for High Throughput Sequence Data
5. A. M. Bolger, M. Lohse, B. Usadel, Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 30, 2114–2120 (2014).
Trimmomatic: a flexible trimmer for Illumina sequence data
6. E. L. Clarke, L. J. Taylor, C. Zhao, A. Connell, J.-J. Lee, B. Fett, F. D. Bushman, K. Bittinger, Sunbeam: an extensible pipeline for analyzing metagenomic sequencing experiments. Microbiome. 7, 46 (2019).
Sunbeam: an extensible pipeline for analyzing metagenomic sequencing experiments
7. M. Kanehisa, S. Goto, KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 28, 27–30 (2000).
KEGG: Kyoto Encyclopedia of Genes and Genomes
8. H. Li, B. Handsaker, A. Wysoker, T. Fennell, J. Ruan, N. Homer, G. Marth, G. Abecasis, R. Durbin, The Sequence Alignment/Map format and SAMtools. Bioinformatics. 25, 2078–2079 (2009).
The Sequence Alignment/Map format and SAMtools
9. M. I. Love, W. Huber, S. Anders, Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
10. W. Luo, M. S. Friedman, K. Shedden, K. D. Hankenson, P. J. Woolf, GAGE: generally applicable gene set enrichment for pathway analysis. BMC Bioinformatics. 10, 161 (2009).
GAGE: generally applicable gene set enrichment for pathway analysis
11. S. T. Westreich, M. L. Treiber, D. A. Mills, I. Korf, D. G. Lemay, SAMSA2: a standalone metatranscriptome analysis pipeline. BMC Bioinformatics. 19, 175 (2018).
SAMSA2: a standalone metatranscriptome analysis pipeline
12. A. Dobin, C. A. Davis, F. Schlesinger, J. Drenkow, C. Zaleski, S. Jha, P. Batut, M. Chaisson, T. R. Gingeras, STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 29, 15–21 (2013).
STAR: ultrafast universal RNA-seq aligner - NCBI
Literature:
13. R. Cheng, J. Feng, B.-X. Zhang, Y. Huang, J. Cheng, C.-X. Zhang, Transcriptome and Gene Expression Analysis of an Oleaginous Diatom Under Different Salinity Conditions. Bioenerg. Res. 7, 192–205 (2014).
14. J. J. Cole, Interactions Between Bacteria and Algae in Aquatic Ecosystems. Annu. Rev. Ecol. Syst. 13, 291–314 (1982).
15. K. R. Fixen, S. R. Starkenburg, B. T. Hovde, S. L. Johnson, C. R. Deodato, H. E. Daligault, K. W. Davenport, C. S. Harwood, R. A. Cattolico, Genome Sequences of Eight Bacterial Species Found in Coculture with the Haptophyte Chrysochromulina tobin. Genome Announc. 4, e01162-16 (2016).
16. B. T. Hovde, C. R. Deodato, H. M. Hunsperger, S. A. Ryken, W. Yost, R. K. Jha, J. Patterson, R. J. M. Jr, S. B. Barlow, S. R. Starkenburg, R. A. Cattolico, Genome Sequence and Transcriptome Analyses of Chrysochromulina tobin: Metabolic Tools for Enhanced Algal Fitness in the Prominent Order Prymnesiales (Haptophyceae). PLOS Genetics. 11, e1005469 (2015).
17. B. T. Hovde, S. R. Starkenburg, H. M. Hunsperger, L. D. Mercer, C. R. Deodato, R. K. Jha, O. Chertkov, R. J. Monnat, R. A. Cattolico, The mitochondrial and chloroplast genomes of the haptophyte Chrysochromulina tobin contain unique repeat structures and gene profiles. BMC Genomics. 15, 604 (2014).
18. C. D. Lowe, L. V. Mello, N. Samatar, L. E. Martin, D. J. Montagnes, P. C. Watts, The transcriptome of the novel dinoflagellate Oxyrrhis marina (Alveolata: Dinophyceae): response to salinity examined by 454 sequencing. BMC Genomics. 12, 519 (2011).
19. N. L. Poff, M. M. Brison, J. W. Day Jr., “Aquatic ecosystems and global climate change” (1022.5, Pew Center on Global Climate Change, 2002), p. 56.
20. C. R. Deodato, S. B. Barlow, B. T. Hovde, R. A. Cattolico, Naked Chrysochromulina (Haptophyta) isolates from lake and river ecosystems: An electron microscopic comparison including new observations on the type species of this taxon. Algal Research. 40, 101492 (2019).
21. N. W. Bigelow, W. R. Hardin, J. P. Barker, S. A. Ryken, A. C. MacRae, R. A. Cattolico, A Comprehensive GC–MS Sub-Microscale Assay for Fatty Acids and its Applications. J Am Oil Chem Soc. 88, 1329–1338 (2011).
22. N. Bigelow, J. Barker, S. Ryken, J. Patterson, W. Hardin, S. Barlow, C. Deodato, R. A. Cattolico, Chrysochromulina sp.: A proposed lipid standard for the algal biofuel industry and its application to diverse taxa for screening lipid content. Algal Research. 2, 385–393 (2013).
23. S. A. Amin, L. R. Hmelo, H. M. van Tol, B. P. Durham, L. T. Carlson, K. R. Heal, R. L. Morales, C. T. Berthiaume, M. S. Parker, B. Djunaedi, A. E. Ingalls, M. R. Parsek, M. A. Moran, E. V. Armbrust, Interaction and signalling between a cosmopolitan phytoplankton and associated bacteria. Nature. 522, 98–101 (2015).
24. I. Krohn-Molt, M. Alawi, K. U. Förstner, A. Wiegandt, L. Burkhardt, D. Indenbirken, M. Thieß, A. Grundhoff, J. Kehr, A. Tholey, W. R. Streit, Insights into Microalga and Bacteria Interactions of Selected Phycosphere Biofilms Using Metagenomic, Transcriptomic, and Proteomic Approaches. Frontiers in Microbiology. 8, 1941 (2017).
25. J. Lian, R. H. Wijffels, H. Smidt, D. Sipkema, The effect of the algal microbiome on industrial production of microalgae. Microb Biotechnol. 11, 806–818 (2018).
26. H. Liu, I. Probert, J. Uitz, H. Claustre, S. Aris-Brosou, M. Frada, F. Not, C. de Vargas, Extreme diversity in noncalcifying haptophytes explains a major pigment paradox in open oceans. PNAS. 106, 12803–12808 (2009).
27. B.-H. Nam, J. Jang, K. Caetano-Anolles, Y.-O. Kim, J. Y. Park, H. Sohn, S. H. Yoon, H. Kim, W. Kwak, Microbial community and functions associated with digestion of algal polysaccharides in the visceral tract of Haliotis discus hannai: Insights from metagenome and metatranscriptome analysis. PLoS One. 13, e0205594 (2018).
28. R. S. Poretsky, I. Hewson, S. Sun, A. E. Allen, J. P. Zehr, M. A. Moran, Comparative day/night metatranscriptomic analysis of microbial communities in the North Pacific subtropical gyre. Environmental Microbiology. 11, 1358–1375 (2009).
29. Y. Chisti, Biodiesel from microalgae. Biotechnology Advances. 25, 294–306 (2007).
30. M. G. Grabherr, B. J. Haas, M. Yassour, J. Z. Levin, D. A. Thompson, I. Amit, X. Adiconis, L. Fan, R. Raychowdhury, Q. Zeng, Z. Chen, E. Mauceli, N. Hacohen, A. Gnirke, N. Rhind, F. di Palma, B. W. Birren, C. Nusbaum, K. Lindblad-Toh, N. Friedman, A. Regev, Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat Biotechnol. 29, 644–652 (2011).
31. J.-P. Cañavate, C. Fernández-Díaz, An appraisal of the variable response of microalgal lipids to culture salinity. Reviews in Aquaculture. n/a, doi:10.1111/raq.12592.
32. P. Vo Hoang Nhat, H. H. Ngo, W. S. Guo, S. W. Chang, D. D. Nguyen, P. D. Nguyen, X. T. Bui, X. B. Zhang, J. B. Guo, Can algae-based technologies be an affordable green process for biofuel production and wastewater remediation? Bioresource Technology. 256, 491–501 (2018).