Genetic Detection and a Method to Study the Ecology of Deadly Cubozoan Jellyfish

Morrissey, Scott J., Jerry, Dean R., and Kingsford, Michael J. (2022) Genetic Detection and a Method to Study the Ecology of Deadly Cubozoan Jellyfish. Diversity, 14 (12). 1139.

[img]
Preview
PDF (Published Version) - Published Version
Available under License Creative Commons Attribution.

Download (2MB) | Preview
View at Publisher Website: https://doi.org/10.3390/d14121139
 
1
556


Abstract

Cubozoan jellyfish pose a risk of envenomation to humans and a threat to many businesses, yet crucial gaps exist in determining threats to stakeholders and understanding their ecology. Environmental DNA (eDNA) provides a cost-effective method for detection that is less labour intensive and provides a higher probability of detection. The objective of this study was to develop, optimise and trial the use of eDNA to detect the Australian box jellyfish, Chironex fleckeri. This species was the focus of this study as it is known to have the strongest venom of any cubozoan; it is responsible for more than 200 recorded deaths in the Indo-Pacific region. Further, its ecology is poorly known. Herein, a specific and sensitive probe-based assay, multiplexed with an endogenous control assay, was developed, and successfully utilised to detect the deadly jellyfish species and differentiate them from closely related taxa. A rapid eDNA decay rate of greater than 99% within 27 h was found with no detectable influence from temperature. The robustness of the technique indicates that it will be of high utility for detection and to address knowledge gaps in the ecology of C. fleckeri; further, it has broad applicability to other types of zooplankton.

Item ID: 77549
Item Type: Article (Research - C1)
ISSN: 1424-2818
Keywords: Cubozoa, eDNA decay, eDNA dynamics, endogenous control, environmental DNA, zooplankton
Copyright Information: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Date Deposited: 16 Mar 2023 02:13
FoR Codes: 31 BIOLOGICAL SCIENCES > 3105 Genetics > 310599 Genetics not elsewhere classified @ 50%
31 BIOLOGICAL SCIENCES > 3103 Ecology > 310305 Marine and estuarine ecology (incl. marine ichthyology) @ 50%
Downloads: Total: 556
Last 12 Months: 14
More Statistics

Actions (Repository Staff Only)

Item Control Page Item Control Page