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Accuracy of nonmolecular identification of growth-hormone-transgenic coho salmon after simulated escape
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Animal ecology.ORCID iD: 0000-0002-3157-7289
Karolinska Institute Stockholm, Sweden.
DFO Centre for Aquaculture and Environmental Research, West Vancouver, Canada.
2015 (English)In: Ecological Applications, ISSN 1051-0761, E-ISSN 1939-5582, Vol. 25, no 6, 1618-1629 p.Article in journal (Refereed) Published
Abstract [en]

Concerns with transgenic animals include the potential ecological risks associated with release or escape to the natural environment, and a critical requirement for assessment of ecological effects is the ability to distinguish transgenic animals from wild type. Here, we explore geometric morphometrics (GeoM) and human expertise to distinguish growth-hormone-transgenic coho salmon (Oncorhynchus kisutch) specimens from wild type. First, we simulated an escape of 3-month-old hatchery-reared wild-type and transgenic fish to an artificial stream, and recaptured them at the time of seaward migration at an age of 13 months. Second, we reared fish in the stream from first-feeding fry until an age of 13 months, thereby simulating fish arising from a successful spawn in the wild of an escaped hatchery-reared transgenic fish. All fish were then assessed from photographs by visual identification (VID) by local staff and by GeoM based on 13 morphological landmarks. A leave-one-out discriminant analysis of GeoM data had on average 86% (72–100% for individual groups) accuracy in assigning the correct genotypes, whereas the human experts were correct, on average, in only 49% of cases (range of 18–100% for individual fish groups). However, serious errors (i.e., classifying transgenic specimens as wild type) occurred for 7% (GeoM) and 67% (VID) of transgenic fish, and all of these incorrect assignments arose with fish reared in the stream from the first-feeding stage. The results show that we presently lack the skills of visually distinguishing transgenic coho salmon from wild type with a high level of accuracy, but that further development of GeoM methods could be useful in identifying second-generation fish from nature as a nonmolecular approach.Read More: http://www.esajournals.org/doi/abs/10.1890/14-1905.1

Place, publisher, year, edition, pages
2015. Vol. 25, no 6, 1618-1629 p.
National Category
Ecology
Identifiers
URN: urn:nbn:se:uu:diva-242002DOI: 10.1890/14-1905.1OAI: oai:DiVA.org:uu-242002DiVA: diva2:782080
Available from: 2015-01-19 Created: 2015-01-19 Last updated: 2017-12-05Bibliographically approved

Open Access in DiVA

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