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Development of a Standardized DNA Database for Chinook Salmon
Author(s) -
Seeb L. W.,
Antonovich A.,
Banks M. A.,
Beacham T. D.,
Bellinger M. R.,
Blankenship S. M.,
Campbell M. R.,
Decovich N. A.,
Garza J. C.,
Guthrie C. M.,
Lundrigan T. A.,
Moran P.,
Narum S. R.,
Stephenson J. J.,
Supernault K. J.,
Teel D. J.,
Templin W. D.,
Wenburg J. K.,
Young S. F.,
Smith C. T.
Publication year - 2007
Publication title -
fisheries
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.725
H-Index - 79
eISSN - 1548-8446
pISSN - 0363-2415
DOI - 10.1577/1548-8446(2007)32[540:doasdd]2.0.co;2
Subject(s) - chinook wind , oncorhynchus , fishery , stock assessment , microsatellite , geography , fisheries management , commission , population , biology , fish <actinopterygii> , allele , business , fishing , demography , genetics , finance , sociology , gene
An international multi‐laboratory project was conducted to develop a standardized DNA database for Chinook salmon ( Oncorhynchus tshawytscha ). This project was in response to the needs of the Chinook Technical Committee of the Pacific Salmon Commission to identify stock composition of Chinook salmon caught in fisheries during their oceanic migrations. Nine genetics laboratories identified 13 microsatellite loci that could be reproducibly assayed in each of the laboratories. To test that the loci were reproducible among laboratories, blind tests were conducted to verify scoring consistency for the nearly 500 total alleles. Once standardized, a dataset of over 16,000 Chinook salmon representing 110 putative populations was constructed ranging throughout the area of interest of the Pacific Salmon Commission from Southeast Alaska to the Sacramento River in California. The dataset differentiates the major known genetic lineages of Chinook salmon and provides a tool for genetic stock identification of samples collected from mixed fisheries. A diverse group of scientists representing the disciplines of fishery management, genetics, fishery administration, population dynamics, and sampling theory are now developing recommendations for the integration of these genetic data into ocean salmon management.