Genetic Stock Identification of Russian Honey Bees

2010 ◽  
Vol 103 (3) ◽  
pp. 917-924 ◽  
Author(s):  
Lelania Bourgeois ◽  
Walter S. Sheppard ◽  
H. Allen Sylvester ◽  
Thomas E. Rinderer
Keyword(s):  
Honey Bees ◽  
Stock Identification ◽  
Genetic Stock ◽  
Genetic Stock Identification ◽  
Russian Honey Bees

Comprehensive microsatellite baseline for genetic stock identification of Atlantic salmon (Salmo salar L.) in northernmost Europe

2017 ◽  
Vol 74 (8) ◽  
pp. 2159-2169 ◽  
Author(s):  
Mikhail Ozerov ◽  
Juha-Pekka Vähä ◽  
Vidar Wennevik ◽  
Eero Niemelä ◽  
Martin-A. Svenning ◽  
...  
Keyword(s):  
Atlantic Salmon ◽  
Salmo Salar ◽  
Stock Identification ◽  
Genetic Stock ◽  
Atlantic Salmon Salmo Salar ◽  
Genetic Stock Identification

Genetic Stock Identification of Steelhead in the Columbia River Basin: An Evaluation of Different Molecular Markers

2004 ◽  
Vol 24 (2) ◽  
pp. 672-685 ◽  
Author(s):  
Gary A. Winans ◽  
Melanie M. Paquin ◽  
Donald M. Van Doornik ◽  
Bruce M. Baker ◽  
Perry Thornton ◽  
...  
Keyword(s):  
Molecular Markers ◽  
River Basin ◽  
Columbia River ◽  
Columbia River Basin ◽  
Stock Identification ◽  
Genetic Stock ◽  
Genetic Stock Identification

Genetic Stock Identification Reveals That Angler Harvest Is Representative of Cryptic Stock Proportions in a High‐Profile Kokanee Fishery

2019 ◽  
Vol 39 (3) ◽  
pp. 415-425
Author(s):  
Hillary G. M. Ward ◽  
Paul J. Askey ◽  
Tyler Weir ◽  
Karen K. Frazer ◽  
Michael A. Russello
Keyword(s):  
Stock Identification ◽  
Genetic Stock ◽  
High Profile ◽  
Genetic Stock Identification

scholarly journals Development of molecular markers for genetic stock identification of chum salmon

2002 ◽  
Vol 68 (sup1) ◽  
pp. 353-356 ◽  
Author(s):  
SYUITI ABE ◽  
SHUNPEI SATO ◽  
HIROYUKI KOJIMA ◽  
JUNKO ANDO ◽  
HIRONORI ANDO ◽  
...  
Keyword(s):  
Molecular Markers ◽  
Chum Salmon ◽  
Stock Identification ◽  
Genetic Stock ◽  
Genetic Stock Identification

scholarly journals Genetic stock identification of Atlantic salmon and its evaluation in a large population complex

2017 ◽  
Vol 74 (3) ◽  
pp. 327-338 ◽  
Author(s):  
Juha-Pekka Vähä ◽  
Jaakko Erkinaro ◽  
Morten Falkegård ◽  
Panu Orell ◽  
Eero Niemelä
Keyword(s):  
Atlantic Salmon ◽  
Large Population ◽  
Identification Accuracy ◽  
Lower Sensitivity ◽  
Stock Identification ◽  
Genetic Structuring ◽  
Genetic Stock ◽  
Factors Affecting ◽  
Genetic Stock Identification ◽  
Genetic Structure And Diversity

Addressing biocomplexity in fisheries management is a challenge requiring an ability to differentiate among distinct populations contributing to fisheries. We produced extensive genetic baseline data involving 36 sampling locations and 33 microsatellite markers, which allowed characterization of the genetic structure and diversity in a large Atlantic salmon (Salmo salar) population complex of the River Teno system, northernmost Europe. Altogether, we identified 28 hierarchically structured and genetically distinct population segments (global FST = 0.065) corresponding exceptionally well with their geographical locations. An assessment of factors affecting the stock identification accuracy indicated that the identification success is largely defined by the interaction of genetic divergence and the baseline sample sizes. The choice between the two statistical methods tested for performance in genetic stock identification, ONCOR and cBAYES, was not critical, albeit the latter demonstrated slightly higher identification accuracy and lower sensitivity to population composition of the mixture sample. The strong genetic structuring among populations together with a powerful marker system allowed for accurate stock identification of individuals and enabled assessment of stock compositions contributing to mixed-stock fisheries.

scholarly journals In-field genetic stock identification of overwintering coho salmon in the Gulf of Alaska: Evaluation of Nanopore sequencing for remote real-time deployment

2021 ◽  
Author(s):  
Christoph M. Deeg ◽  
Ben J. G. Sutherland ◽  
Tobi J. Ming ◽  
Colin Wallace ◽  
Kim Jonsen ◽  
...  
Keyword(s):  
Real Time ◽  
Coho Salmon ◽  
Gulf Of Alaska ◽  
Amplicon Sequencing ◽  
Stock Identification ◽  
Nanopore Sequencing ◽  
Genetic Stock ◽  
Genetic Stock Identification ◽  
Batch Sizes ◽  
Sequencing Platforms

Genetic stock identification (GSI) by single nucleotide polymorphism (SNP) sequencing has become the gold standard for stock identification in Pacific salmon, which are found in mixed-stocks during the oceanic phase of their lifecycle. Sequencing platforms currently applied require large batch sizes and multi-day processing in specialized facilities to perform genotyping by the thousands. However, recent advances in third-generation single-molecule sequencing platforms, like the Oxford Nanopore minION, provide base calling on portable, pocket-sized sequencers and hold promise for the application of real-time, in-field stock identification on variable batch sizes. Here we report and evaluate utility and comparability of at-sea stock identification of coho salmon Oncorhynchus kisutch based on targeted SNP amplicon sequencing on the minION platform during the International Year of the Salmon Signature Expedition to the Gulf of Alaska in the winter of 2019. Long read sequencers are not optimized for short amplicons, therefore we concatenate amplicons to increase coverage and throughput. Nanopore sequencing at-sea yielded stock assignment for 50 of the 80 assessed individuals. Nanopore-based SNP calls agreed with Ion Torrent based genotypes in 83.25%, but assignment of individuals to stock of origin only agreed in 61.5% of individuals highlighting inherent challenges of Nanopore sequencing, such as resolution of homopolymer tracts and indels. However, poor representation of assayed coho salmon in the queried baseline dataset contributed to poor assignment confidence on both platforms. Future improvements will focus on lowering turnaround time, accuracy, throughput, and cost, as well as augmentation of the existing baselines, specifically in stocks from coastal northern BC and Alaska. If successfully implemented, Nanopore sequencing will provide an alternative method to the large-scale laboratory approach. Genotyping by amplicon sequencing in the hands of diverse stakeholders could inform management decisions over a broad expanse of the coast by allowing the analysis of small batches in remote areas in near real-time.

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