Original Article

Genetic architecture of gene transcription in two Atlantic salmon (Salmo salar) populations

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Abstract

Gene expression regulation has an important role in short-term acclimation and long-term adaptation to changing environments. However, the genetic architecture of gene expression has received much less attention than that of traditional phenotypic traits. In this study, we used a 5 × 5 full-factorial breeding design within each of two Atlantic salmon (Salmo salar) populations to characterize the genetic architecture of gene transcription. The two populations (LaHave and Sebago) are being used for reintroduction efforts into Lake Ontario, Canada. We used high-throughput quantitative real-time PCR to measure gene transcription levels for 22 genes in muscle tissue of Atlantic salmon fry. We tested for population differences in gene transcription and partitioned the transcription variance into additive genetic, non-additive genetic and maternal effects within each population. Interestingly, average additive genetic effects for gene transcription were smaller than those reported for traditional phenotypic traits in salmonids, suggesting that the evolutionary potential of gene transcription is lower than that of traditional traits. Contrary to expectations for early life stage traits, maternal effects were small. In general, the LaHave population had higher additive genetic effects for gene transcription than the Sebago population had, indicating that the LaHave fish have a higher adaptive potential to respond to the novel selection pressures associated with reintroduction into a novel environment. This study highlights not only the profound variation in gene transcription possible among salmonid populations but also the among-population variation in the underlying genetic architecture of such traits.

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Acknowledgements

We thank C Wilson, W Sloan, S Ferguson and B Lewis for their help and support at the Ontario Ministry of Natural Resources and Forestry (OMNRF) Codrington Research Facility. We thank C Black and A Smith for their assistance for sample collection. We thank R Hepburn for his help with the running of OpenArray chips. This work was supported by Natural Sciences and Engineering Research Council (NSERC) of Canada funding to DDH (Discovery and Strategic Project Grant) and TEP (Strategic Project Grant).

Author information

Affiliations

  1. Great Lakes Institute for Environmental Research, University of Windsor, Windsor, Ontario, Canada

    • X He
    • , T E Pitcher
    •  & D D Heath
  2. Department of Biology, Western University, London, Ontario, Canada

    • A L S Houde
  3. Department of Biological Sciences, University of Windsor, Windsor, Ontario, Canada

    • T E Pitcher

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Competing interests

The authors declare no conflict of interest.

Corresponding author

Correspondence to D D Heath.

Supplementary information

Supplementary Information accompanies this paper on Heredity website (http://www.nature.com/hdy)