Oncorhynchus kisutch genetic stock ID SNP baseline

Here we evaluate utility and comparability to established GSI platforms of at-sea stock identification of coho salmon Oncorhynchus kisutch based on targeted SNP amplicon sequencing on the minION platform during a high-sea winter expedition to the Gulf of Alaska. As long read sequencers are not optimized for short amplicons, 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.

If successfully implemented, Nanopore sequencing will provide an alternative method to the large-scale laboratory approach by providing mobile small batch genotyping to diverse stakeholders.

Methods

This SNP baseline used for genetic stock identification of coho salmon on the Oxford Nanopore minION is a combination of previously published baseline data from the Fisheries and Oceans Canada Molecular Genetics Laboratory at the Pacific Biological Station by Beacham et al. (datadryad.org/stash/dataset/doi:10.5061/dryad.msbcc2fvk; datadryad.org/stash/dataset/doi:10.5061/dryad.3g1r4v3; datadryad.org/stash/dataset/doi:10.5061/dryad.4md17).

Usage notes

An explanation of the SNP loci and alles can be found in Appendix Table A2 of Beacham, Terry D., et al. "Population and individual identification of coho salmon in British Columbia through parentage-based tagging and genetic stock identification: an alternative to coded-wire tags." Canadian Journal of Fisheries and Aquatic Sciences 74.9 (2017): 1391-1410 (doi.org/10.1139/cjfas-2016-0452). The database is foramted for use in rubias (github.com/eriqande/rubias).