Published on 05 August 2011 |

Version 1

Data from: Detection of outlier loci and their utility for fisheries management

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Russello, Michael A;Kirk, Stephanie L;Frazer, Karen K;Askey, Paul J

Description

Genetics-based approaches have informed fisheries management for decades, yet remain challenging to implement within systems involving recently diverged stocks or where gene flow persists. In such cases, genetic markers exhibiting locus-specific (“outlier”) effects associated with divergent selection may provide promising alternatives to loci that reflect genome-wide (“neutral”) effects for guiding fisheries management. Okanagan Lake kokanee (Oncorhynchus nerka), a fishery of conservation concern, exhibits two sympatric ecotypes adapted to different reproductive environments, however, previous research demonstrated the limited utility of neutral microsatellites for assigning individuals. Here, we investigated the efficacy of an outlier-based approach to fisheries management by screening >11,000 expressed sequence tags for linked microsatellites and conducting genomic scans for kokanee sampled across seven spawning sites. We identified eight outliers among 52 polymorphic loci that detected ecotype-level divergence, whereas there was no evidence of divergence at neutral loci. Outlier loci exhibited the highest self-assignment accuracy to ecotype (92.1%), substantially outperforming 44 neutral loci (71.8%). Results were robust among-sampling years, with assignment and mixed composition estimates for individuals sampled in 2010 mirroring baseline results. Overall, outlier loci constitute promising alternatives for informing fisheries management involving recently diverged stocks, with potential applications for designating management units across a broad range of taxa.

Citations (1)

Mentions (0)

Metrics

Dataset Index

2.2

FAIR Score

77%

Citations

1

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Dryad

Assigned Domain

Subfield

Genetics

Field

Biochemistry, Genetics and Molecular Biology

Domain

Life Sciences

Confidence Score

42%

Source

Scholar Data Model

Keywords

Oncorhynchus nerka

Normalization Factors

FT

13.46

CTw

1.00

MTw

1.00