Abstract
The ability to differentiate life history variants is vital for estimating fisheries management parameters, yet traditional survey methods can be inaccurate in mixed-stock fisheries. Such is the case for kokanee, the freshwater resident form of sockeye salmon (Oncorhynchus nerka), which exhibits various reproductive ecotypes (stream-, shore-, deep-spawning) that co-occur with each other and/or anadromous O. nerka in some systems across their pan-Pacific distribution. Here, we developed a multi-purpose Genotyping-in-Thousands by sequencing (GT-seq) panel of 288 targeted single nucleotide polymorphisms (SNPs) to enable accurate kokanee stock identification by geographic basin, migratory form, and reproductive ecotype across British Columbia, Canada. The GT-seq panel exhibited high self-assignment accuracy (93.3%) and perfect assignment of individuals not included in the baseline to their geographic basin, migratory form, and reproductive ecotype of origin. The GT-seq panel was subsequently applied to Wood Lake, a valuable mixed-stock fishery, revealing high concordance (>98%) with previous assignments to ecotype using microsatellites and TaqMan® SNP genotyping assays, while improving resolution, extending a long-term time-series, and demonstrating the scalability of this approach for this system and others.
Highlights
Freshwater fish populations have declined 83% over the past forty years as a result of the cumulative effects of overfishing, habitat degradation, climate change, dams and other migration barriers [1,2,3]
We used previously published genotypic data at 7,347 single nucleotide polymorphisms (SNPs) [35] collected via restriction siteassociated DNA sequencing (RADseq) from stream, shore- and deep-spawning kokanee and anadromous sockeye salmon distributed across three geographic basins (Columbia, Skeena, and Fraser) in British Columbia
The finalized SNP pool (n = 547) before primer design included those that exhibited the highest divergence across geographic basin (n = 102), migratory form (n = 87), reproductive ecotype (n = 182), or overlapped across multiple comparisons (n = 176)
Summary
Freshwater fish populations have declined 83% over the past forty years as a result of the cumulative effects of overfishing, habitat degradation, climate change, dams and other migration barriers [1,2,3]. Mixed-stock fisheries present a further challenge for management as stock specific parameters are required to set harvest targets while meeting spawning escapement goals [6]. Genetic stock identification (GSI) techniques have been developed to assess stock proportions by delineating individuals by genetic origin and considering barriers to gene flow [8,9,10]. Genetic stock identification panels have previously featured allozymes [11], microsatellites [12], and mitochondrial DNA [13, 14] as genetic markers of choice, but suffer from limited statistical power for precise estimates of stock composition within some species [15, 16]. Recent advances in massively parallel DNA sequencing ( known as generation sequencing; NGS) have made great strides in improving speed and reducing costs of obtaining genetic data, providing opportunities for the development and application of novel genotyping approaches ideal for fisheries management applications [17]
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