115-14 Population Genomics of Brook Trout: A Quest for Adaptive Variation Among Populations Exhibiting Prodigious Genetic Differentiation at Neutral Loci

Tim L. King , Leetown Science Center, U.S. Geological Survey, Kearneysville, WV
Barbara A. Lubinski , Leetown Science Center, U.S. Geological Survey, Kearneysville, WV
Steve Moore , Great Smoky Mountains National Park, National Park Service, Gatlinburg, TN
Matt Kulp , Great Smoky Mountians National Park, National Park Service, Gatlinburg, TN
Jeb Wofford , Shenandoah National Park, National Park Service, Luray, VA
Jay R. Stauffer Jr. , Wildlife and Fisheries Science, Penn State University, University Park, PA
Casey Weathers , Wildlife and Fisheries Science, Penn State University, University Park, PA
Louis Bernatchez , Département de Biology, Université Laval, Québec, QC, Canada
Resource managers must plan for an evolutionary future for trust species, as such, ecological and evolutionary processes—those that maintain genetic diversity and provide the raw material for evolution and adaptation of populations—must be explicitly identified.  Contemporary genomic technology offers great promise for exploring the mechanistic basis of adaptive evolution in a model system.  Brook trout (Salvelinus fontinalis) are rich in ecologically and evolutionarily interesting traits (e.g., multiple life history forms; broad latitudinal and elevational distribution; and prodigious gene differentiation (neutral loci) at all spatial scales) that vary between interfertile individuals.  Given that both neutral drift and natural selection govern the variance of traits among demographically distinct entities, we are employing a research framework that involves quantifying neutral (i.e., differentiation due to genetic distance) and adaptive genetic variation (measured by mass gene expression profiling) among ecologically and evolutionarily distinct brook trout.  We have collaborated in an extensive survey of neutral allelic variation at 13 microsatellite DNA loci in >13,000 S. fontinalis sampled from 370 collections comprising the species’ native range (and including five national parks).  Traditional population genetic analyses identified prodigous levels of genetic differentiation at all spatial scales.  Coalescence-based analyses also illuminated previously undetected demographic histories and evolutionary relationships among populations.  We are now in the process of assembling and annotating a transcriptome (de novo), and performing mass gene expression profiling.  Findings from a case study from Great Smoky Mountains National Park and an overall study update will be presented.