Transcriptome analysis of the euryhaline alga, Prymnesium parvum (Prymnesiophyceae): effects of salinity on differential gene expression

Abstract:

There is limited information on the underlying physiological responses and molecular mechanisms involved in the ability of the ichthyotoxic alga, Prymnesium parvum, to tolerate a broad range of salinities. We report an RNA sequencing analysis of the transcriptome of P. parvum, including a de novo assembly generating 47,289 transcripts. Of them, 35.4% were identifiable, and 30.4% and 16.8% were classified into gene ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, respectively. Cultures were grown in media at salinities of 5 and 30 practical salinity units (psu), and the differential expression of 2507 transcripts (5.3%) was detected. Specifically, 1507 (3.2%) and 1000 (2.1%) transcripts were up- and downregulated, respectively, at 30 vs 5 psu. Relevant candidate genes identified included those whose products are involved in osmolyte production, salinity stress, ion transport, and acetate metabolism. Thirty-two different polyketide synthase (PKS) transcripts were identified, none of which were differentially expressed under our experimental conditions. However, our analysis revealed evidence of posttranscriptional regulation of polyketide prymnesin production and the contributory effects of putative hemolysins and polyunsaturated fatty acids (PUFAs) toward ichthyotoxicity. Moreover, gene transcription associated with vesicular transport was increased at the lower salinity. This comprehensive transcriptome characterization sheds light on transcriptional responses that occur following alterations in salinity in P. parvum.

Key Words::

• Euryhaline
• Gene expression
• Haptophyte
• Prymnesium parvum
• RNA-Seq
• Salinity
• Transcriptome

ACKNOWLEDGEMENTS

We thank Dr. Jeremiah Hackett, Dr. William Driscoll, and Dr. Jennifer Wisecaver from the University of Arizona Department of Ecology and Evolutionary Biology for arranging for the RNA-Seq analysis. We also thank Dr. Jin Zhang, Dr. Matt Ashworth, Michael Gupta, Dhivya Arasappan, and the staff at the Texas Advanced Computing Center at the University of Texas at Austin for their assistance with the data analysis.

SUPPLEMENTARY DATA

Supplementary data associated with this article can be found online at http://dx.doi.org/10.2216/15-74.1.s1.