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Data from: Genotyping-in-Thousands by Sequencing panel development and application for high-resolution monitoring of introgressive hybridization within sockeye salmon

Cite this dataset

Chang, Sarah; Ward, Hillary; Elliott, Lucas; Russello, Michael (2022). Data from: Genotyping-in-Thousands by Sequencing panel development and application for high-resolution monitoring of introgressive hybridization within sockeye salmon [Dataset]. Dryad. https://doi.org/10.5061/dryad.z34tmpgg4

Abstract

Stocking programs have been widely implemented to re-establish extirpated fish species to their historical ranges; when employed in species with complex life histories, such management activities should include careful consideration of resulting hybridization dynamics with resident stocks and corresponding outcomes on recovery initiatives. Genetic monitoring can be instrumental for quantifying the extent of introgression over time, however, conventional markers typically have limited power for the identification of advanced hybrid classes, especially at the intra-specific level. Here, we demonstrate a workflow for developing, evaluating, and deploying a Genotyping-in-Thousands by Sequencing (GT-seq) SNP panel with the power to detect advanced hybrid classes to assess the extent and trajectory of intra-specific hybridization, using the sockeye salmon (Oncorhynchus nerka) stocking program in Skaha Lake, British Columbia, as a case study. Previous analyses detected significant levels of hybridization between the anadromous (sockeye) and freshwater resident (kokanee) forms of O. nerka, but were restricted to assigning individuals to pure-stock or “hybrid”. Simulation analyses indicated our GT-seq panel had high accuracy, efficiency and power (> 94.5%) of assignment to pure-stock sockeye salmon/kokanee, F1, F2, and B2 backcross-sockeye/kokanee. Re-analysis of 2016/2017 spawners previously analyzed using TaqMan assays and otolith microchemistry revealed shifts in assignment of some hybrids to adjacent pure-stock or B2-backcross classes, while new assignment of 2019 spawners revealed hybrids comprised 31% of the population, ~74% of which were B2-backcross or F2. Overall, the GT-seq panel development workflow presented here could be applied to virtually any system where genetic stock identification and intra-specific hybridization are important management parameters.

Methods

Genotyping-in-Thousands by sequencing (GT-seq) following Campbell et al. (2015) Molecular Ecology Resources as modified in Schmidt et al. (2020) Molecular Ecology Resources.

Usage notes

342_RADseq_baseline.vcf: vcf file of genotypic data at 342 SNPs for all baseline individuals used for panel development 

2016_and_2017_OKR_Onco.vcf: vcf file of genotypic data at 341 SNPs collected with GT-seq for 2016 and 2017 samples used for comparison with previous sequencing methods.

2019_OKR_Onco.vcf: vcf file of genotypic data at 341 SNPs collected with GT-seq for 2019 samples.

342_probeseqs_locusinfo.csv: text file containing sequences for the 342 loci where the retained SNPs are located, GT-seq genotyping input file

Onco_biodata.xlsx: spreadsheet containing individual metadata for all samples used including sample identifiers, date of sample collection, body length, and sex