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bioRxiv · 10.1101/022178

Low but significant genetic differentiation underlies biologically meaningful phenotypic divergence in a large Atlantic salmon population

Tutku Aykanat·Susan E Johnston·Panu Orell·Eero Niemelä·Jaakko Erkinaro·Craig R Primmer
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Abstract

Despite decades of research assessing the genetic structure of natural populations, the biological meaning of low yet significant genetic divergence often remains unclear due to a lack of associated phenotypic and ecological information. At the same time, structured populations with low genetic divergence and overlapping boundaries can potentially provide excellent models to study adaptation and reproductive isolation in cases where high resolution genetic markers and relevant phenotypic and life history information are available. Here, we combined SNP-based population inference with extensive phenotypic and life history data to identify potential biological mechanisms driving fine scale sub-population differentiation in Atlantic salmon (Salmo salar) from the Teno River, a major salmon river in Europe. Two sympatrically occurring sub-populations had low but significant genetic differentiation (FST = 0.018) and displayed marked differences in the distribution of life history strategies, including variation in juvenile growth rate, age at maturity and size within age classes. Large, late-maturing individuals were virtually absent from one of the two sub-populations and there were significant differences in juvenile growth rates and size-at-age after oceanic migration between individuals in the respective sub-populations. Our findings suggest that different evolutionary processes affect each sub-population and that hybridization and subsequent selection may maintain low genetic differentiation without hindering adaptive divergence.

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Tutku Aykanat, Susan E Johnston, Panu Orell, Eero Niemelä, Jaakko Erkinaro, Craig R Primmer. 2015-07-07. Low but significant genetic differentiation underlies biologically meaningful phenotypic divergence in a large Atlantic salmon population. https://doi.org/10.1101/022178

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