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Comparison of Three Genetic Methodologies....
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GRANT NUMBER:  NA66FD0042           NMFS NUMBER: 95-AKR-009

REPORT TITLE: Comparison of Three Genetic Methodologies for Stock Identification of Pink, Chum, and Sockeye Salmon in the North Pacific (Phase 1)

AUTHOR:  Gharrett, A.J.; Gray, A.K.; Churikov, D.; Matsuoka, M.P.; Luan, X.; and Brykov, V.

PUBLISH DATE: March 31, 1997

AVAILABLE FROM:  National Marine Fisheries Service, P.O. Box 21668, Juneau, Alaska 99802-1668.  PHONE: (907) 586-7280

ABSTRACT

Genetic variation is routinely used to identify origins of salmon caught in mixed fisheries, intercepted by foreign fisheries, and taken as bycatch in fisheries directed at other species.  Historically protein electrophoresis has been the primary tool, but the method has some drawbacks, such a limitation on the scope of the genetic variability resolved and requirement for quality tissue samples that often necessitates use of liquid nitrogen or dry ice the field.  DNA-based methods offer opportunity for exposing much more genetic variation and have less rigorous requirements for sample quality.  Here we describe the work we have conducted to determine the genetic markers we will use to acquire genetic data from and compare the nature of the genetic variation in populations of chum, sockeye, and both even-and odd-broodyear pink salmon. In this preliminary study, we screened subsamples of populations of those species for variation in mitochondrial DNA sequences and for variation at nuclear microsatellite DNA loci. The geographic distribution of samples screened spans the North Pacific Ocean from southern Southeast Alaska to Asia. Substantial mtDNA variation was resolved for all species and three variable microsatellite loci were found for each species. These results will be used to select markers that will be evaluated in larger sample sizes from more numerous populations in the next phase of the project. At the end of the project, variation resolved using both DNA-based and data from protein electrophoresis, parallel data sets from the same individual fish, will be compared and evaluated for their performance to detect stock structure. 

 
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