High Throughput Genomics Applied to Identify Cumulative Impacts of Environmental and Biological Stressors on Salmon

Wednesday, August 20, 2014: 11:30 AM
205A (Centre des congrès de Québec // Québec City Convention Centre)
Kristi Miller , Pacific Biological Station, Fisheries and Oceans Canada, Nanaimo, BC, Canada
Scott G. Hinch , Centre for Applied Conservation Research and Department of Forest Sciences, University of British Columbia, Vancouver, BC, Canada
David A. Patterson , Freshwater Ecosystems Section, Fisheries and Oceans Canada, Burnaby, BC, Canada
Brian Riddell , Pacific Salmon Foundation, Vancouver, BC, Canada
Marc Trudel , Pacific Biological Station, Fisheries & Oceans Canada, Nanaimo, BC, Canada
Strahan Tucker , Pacific Biological Station, Fisheries and Oceans Canada, Nanaimo, BC, Canada
Amy Teffer , University of Victoria, Victoria, BC
Ken M. Jeffries , School of Veterinary Medicine, University of California, Davis, Davis, CA
Declines in productivity and abundance of wild salmon likely result from the cumulative and synergistic effects of multiple stressors.  Our research program applies molecular genetic and genomic technologies to build a greater understanding of factors that may undermine performance of wild salmon.  Functional genomic studies on wild-migrating salmon have revealed a high percentage of signatures involving strong differential immune stimulation; some may be associated with responses to infectious agents.  A microfluidic platform to quantitatively assess presence and load of over 90% of microparasites known to cause disease in salmon worldwide has been applied to identify pathogens potentially impacting wild salmon survival.  Microarrays and biomarkers to dozens of host immune- and stress-related genes are resolving the microbes associated with a strong host response, indicative of a disease state.   Biotelemetry studies have resolved viruses and parasites associated with reduced migration success.  The additional roles of predators and climate influencing population-level pathogen profiles are providing insight into ecological and evolutionary outcomes potentially associated with cumulative stressors.  In future, evolutionary drivers of variation in microparasite susceptibility will be incorporated into these “natural” studies by linking data on MHC variation or by taking a dQTL approach via NGS.