The present study is part of a larger effort to understand the biology of lake trout ecotypes in Lake Superior and represents a collaborative effort of a number of investigators in different fields. The analysis of growth, morphometry and the ecological significance of these results was a joint effort of several authors including Dan Rosauer, a fishery biologist at the Great Lakes WATER Institute (GLWI), Shawn Sitar, a fishery biologist with the Michigan DNR with interests in population dynamics and Great Lakes deepwater ecology, and Chuck Bronte a fishery biologist and data analyst at the U.S. Fish and Wildlife Service who has been working for 25 years on the biology and restoration of lake trout in the Laurentian Great Lakes. The bioinformatic analysis of the Roche 454 dataset and the supporting qPCR analysis and interpretation was also a joint effort of several authors including Steven Roberts, an assistant professor at the University of Washington, who is a comparative physiologist using transcriptomic approaches to examine how aquatic organisms respond to changes in environmental conditions, Crystal Simchick, a molecular biologist in the Goetz laboratory, and a bioinformaticist, Giles Goetz, working at the GLWI with interests in the analysis of global genome datasets. The lipid analysis and interpretation was accomplished by Ron Johnson, a research chemist at NOAA interested in lipid dynamics and reproduction in fish, and Cheryl Murphy an assistant professor at Michigan State University interested in how changes in the physiology of an individual fish translate to population and/or community level changes. The lead author, Rick Goetz, is a research scientist at the GLWI working in several areas of fish biology including the molecular basis of phenotypic differentiation in fish. The last author, Simon MacKenzie, is a faculty member of the Universitat Autonoma de Barcelona (Spain) with interests in using global genome approaches to address basic biological problems in fish biology. He and the lead author designed and implemented the pyrosequencing approach used in this study.
A genetic basis for the phenotypic differentiation between siscowet and lean lake trout (Salvelinus namaycush)
Article first published online: 10 FEB 2010
© 2010 Blackwell Publishing Ltd
Special Issue: Next Generation Molecular Ecology
Volume 19, Issue Supplement s1, pages 176–196, March 2010
How to Cite
GOETZ, F., ROSAUER, D., SITAR, S., GOETZ, G., SIMCHICK, C., ROBERTS, S., JOHNSON, R., MURPHY, C., BRONTE, C. R. and MACKENZIE, S. (2010), A genetic basis for the phenotypic differentiation between siscowet and lean lake trout (Salvelinus namaycush). Molecular Ecology, 19: 176–196. doi: 10.1111/j.1365-294X.2009.04481.x
- Issue published online: 10 FEB 2010
- Article first published online: 10 FEB 2010
- Received 30 June 2009; revision received 15 September 2009; accepted 28 September 2009
- Lake Superior;
- lake trout;
- phenotypic differentiation;
In Lake Superior there are three principal forms of lake trout (Salvelinus namaycush): lean, siscowet and humper. Wild lean and siscowet differ in the shape and relative size of the head, size of the fins, location and size of the eyes, caudal peduncle shape and lipid content of the musculature. To investigate the basis for these phenotypic differences, lean and siscowet lake trout, derived from gametes of wild populations in Lake Superior, were reared communally under identical environmental conditions for 2.5 years. Fish were analysed for growth, morphometry and lipid content, and differences in liver transcriptomics were investigated using Roche 454 GS-FLX pyrosequencing. The results demonstrate that key phenotypic differences between wild lean and siscowet lake trout such as condition factor, morphometry and lipid levels, persist in these two forms when reared in the laboratory under identical environmental conditions. This strongly suggests that these differences are genetic and not a result of environmental plasticity. Transcriptomic analysis involving the comparison of hepatic gene frequencies (RNA-seq) and expression (quantitative reverse transcription–polymerase chain reaction (qPCR)) between the two lake trout forms, indicated two primary gene groups that were differentially expressed; those involving lipid synthesis, metabolism and transport (acyl-CoA desaturase, acyl-CoA binding protein, peroxisome proliferator-activated receptor gamma, and apolipoproteins), and those involved with immunity (complement component C3, proteasome, FK506 binding protein 5 and C1q proteins). The results demonstrate that RNA-seq can be used to identify differentially expressed genes; however, some discrepancies between RNA-seq analysis and qPCR indicate that methods for deep sequencing may need to be refined and/or different RNA-seq platforms utilized.