Genetic stock identification of Atlantic salmon using single locus minisatellite DNA profiles

The successful application of genetic stock identification (GSI) in mixed fisheries for Pacific salmon species has demonstrated clearly the potential of the approach as an aid to effective management of salmonid populations. Low levels of genetic variability detectable by protein electrophoresis hav...

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Bibliographic Details
Published in:Journal of Fish Biology
Main Authors: Galvin, P., McKinnell, S., Taggart, J. B., Ferguson, A., O'Farrell, M., Cross, T. F.
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 1995
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Online Access:http://dx.doi.org/10.1111/j.1095-8649.1995.tb06055.x
https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fj.1095-8649.1995.tb06055.x
https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1095-8649.1995.tb06055.x
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Summary:The successful application of genetic stock identification (GSI) in mixed fisheries for Pacific salmon species has demonstrated clearly the potential of the approach as an aid to effective management of salmonid populations. Low levels of genetic variability detectable by protein electrophoresis have limited its utilization in Atlantic salmon Salmo salar management. However, recent developments in the detection of highly variable minisatellite loci, mean that the GSI technique is now applicable in this species. An extensive baseline survey of the River Shannon system in Ireland, involving a total of 1252 juvenile Atlantic salmon collected from nine tributaries, screened for three highly variable minisatellite DNA loci ( Ssa ‐A45/1, Ssa ‐A45/2/1 and Str ‐A9), presented a suitable database to assess this type of mixed fisheries approach. Allozyme analysis, carried out on the same fish, allowed the performance of GSI on minisatellite DNA data to be compared directly with conventional data using simulations. Initial tests involved the creation of ‘mixture samples’ of specified compositions from the database, to determine the bias involved and the degree of precision achievable in the estimation of the composition of the mixture sample. Iterations of this procedure, simulated resampling of a mixture stock, thus enabled bias and precision to be estimated. The effect of size of the mixture sample was also assessed in this way. It was then possible to examine the compositions of actual mixture samples (using minisatellite DNA analysis only), which consisted of 200 unmarked grilse (one sea‐winter) and 50 unmarked multi‐sea‐winter salmon, collected as they passed upstream through traps located near the base of the system. Sampling in this case involved the non‐destructive collection of adipose fin cores (an important consideration as valuable broodstock were involved). The initial analysis revealed that allozymes require much larger sample sizes than minisatellites to achieve comparable accuracy and precision. It also ...