Abstract
Resource managers need to differentiate between sites with and without contaminants and those where contaminants cause impacts. Potentially, transcriptomes could be used to evaluate sites where contaminant-induced effects may occur, to identify causative stressors of effects and potential adverse outcomes. To test this hypothesis, the hepatic transcriptomes in Barramundi (Lates calcarifer) from two reference sites, two agriculturally impacted sites sampled during the dry season, and an impacted site sampled during the wet season were compared. The hepatic transcriptome was profiled using RNA-Seq. Multivariate analysis showed that transcriptomes were clustered based on site and by inference water quality, but not sampling time. The largest differences in transcriptomic profile were between reference sites and a site sampled during high run-off, showing that impacted sites can be identified via RNASeq.
Transcripts with altered abundance were linked to xenobiotic metabolism, peroxisome proliferation and stress responses, indicating putative stressors with the potential for adverse outcomes in barramundi.
Transcripts with altered abundance were linked to xenobiotic metabolism, peroxisome proliferation and stress responses, indicating putative stressors with the potential for adverse outcomes in barramundi.
Original language | English |
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Pages (from-to) | 166-179 |
Number of pages | 14 |
Journal | Marine Environmental Research |
Volume | 129 |
Early online date | 31 May 2017 |
DOIs | |
Publication status | Published - Aug 2017 |
Bibliographical note
Publisher Statement: NOTICE: this is the author’s version of a work that was accepted for publication in Marine Environmental Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Marine Environmental Research, [(in press), (2017)] DOI: 10.1016/j.marenvres.2017.05.006© 2017, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Keywords
- Transcriptomics
- RNA Seq
- Barramundi
- Great Barrier Reef
- pesticides
- herbicides
- agricultural contamination