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.