Understanding the mechanisms by which populations adapt to their environments is a fundamental aim in biology. However, it remains challenging to identify the genetic basis of traits, provide evidence of genetic changes and quantify phenotypic responses. Age at maturity in Atlantic salmon represents an ideal trait to study contemporary adaptive evolution as it has been associated with a single locus in the vgll3 region and has also strongly changed in recent decades. Here, we provide an empirical example of contemporary adaptive evolution of a large-effect locus driving contrasting sex-specific evolutionary responses at the phenotypic level. We identified an 18% decrease in the vgll3 allele associated with late maturity in a large and diverse salmon population over 36 years, induced by sex-specific selection during sea migration. Those genetic changes resulted in a significant evolutionary response only in males, due to sex-specific dominance patterns and vgll3 allelic effects. The vgll3 allelic and dominance effects differed greatly in a second population and were likely to generate different selection and evolutionary patterns. Our study highlights the importance of knowledge of genetic architecture to better understand fitness trait evolution and phenotypic diversity. It also emphasizes the potential role of adaptive evolution in the trend towards earlier maturation observed in numerous Atlantic salmon populations worldwide.
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The data supporting the findings of this study are available in the Dryad Digital Repository with the identifier doi:10.5061/dryad.7hm4708.
Losos, J. B. Ecological character displacement and the study of adaptation. Proc. Natl Acad. Sci. USA 97, 5693–5695 (2000).
Andrew, R. L. et al. A road map for molecular ecology. Mol. Ecol. 22, 2605–2626 (2013).
Sharpe, D. M. T. & Hendry, A. P. Life history change in commercially exploited fish stocks: an analysis of trends across studies. Evol. Appl. 2, 260–275 (2009).
Teplitsky, C. & Millien, V. Climate warming and Bergmann’s rule through time: is there any evidence? Evol. Appl. 7, 156–168 (2014).
Gienapp, P., Teplitsky, C., Alho, J. S., Mills, J. A. & Merilä, J. Climate change and evolution: disentangling environmental and genetic responses. Mol. Ecol. 17, 167–178 (2008).
Merilä, J. & Hendry, A. P. Climate change, adaptation, and phenotypic plasticity: the problem and the evidence. Evol. Appl. 7, 1–14 (2014).
Merilä, J. & Hoffmann, A. A. in Oxford Research Encyclopedia of Environmental Science (ed. Shugart, H.) https://doi.org/10.1093/acrefore/9780199389414.013.136 (Oxford Univ. Press, New York, 2016).
Savolainen, O., Lascoux, M. & Merilä, J. Ecological genomics of local adaptation. Nat. Rev. Genet. 14, 807–820 (2013).
Crnokrak, P. & Roff, D. A. Dominance variance: associations with selection and fitness. Heredity 75, 530–540 (1995).
Barson, N. J. et al. Sex-dependent dominance at a single locus maintains variation in age at maturity in salmon. Nature 528, 405–408 (2015).
Liang, Y. et al. A gene network regulated by the transcription factor VGLL3 as a promoter of sex-biased autoimmune diseases. Nat. Immunol. 18, 152–160 (2017).
Fleming, I. A. Reproductive strategies of Atlantic salmon: ecology and evolution. Rev. Fish Biol. Fish. 6, 349–416 (1996).
Mank, J. E. Population genetics of sexual conflict in the genomic era. Nat. Rev. Genet. 18, 721–730 (2017).
Chaput, G. Overview of the status of Atlantic salmon (Salmo salar) in the North Atlantic and trends in marine mortality. ICES J. Mar. Sci. 69, 1538–1548 (2012).
Erkinaro, J. et al. Life history variation across four decades in a diverse population complex of Atlantic salmon in a large subarctic river. Can. J. Fish. Aquatic Sci. https://doi.org/10.1139/cjfas-2017-0343 (2018).
Otero, J. et al. Contemporary ocean warming and freshwater conditions are related to later sea age at maturity in Atlantic salmon spawning in Norwegian rivers. Ecol. Evol. 2, 2192–2203 (2012).
Crozier, L. G. & Hutchings, J. A. Plastic and evolutionary responses to climate change in fish. Evol. Appl. 7, 68–87 (2014).
Vähä, J.-P., Erkinaro, J., Niemelä, E. & Primmer, C. R. Temporally stable genetic structure and low migration in an Atlantic salmon population complex: implications for conservation and management. Evol. Appl. 1, 137–154 (2008).
Heinimaa, S. & Heinimaa, P. Effect of the female size on egg quality and fecundity of the wild Atlantic salmon in the sub-Arctic River Teno. Boreal Environ. Res. 9, 55–62 (2004).
Jonsson, B., Jonsson, N. & Albretsen, J. Environmental change influences the life history of salmon Salmo salar in the North Atlantic Ocean. J. Fish Biol. 88, 618–637 (2016).
Ohlberger, J., Ward, E. J., Schindler, D. E. & Lewis, B. Demographic changes in Chinook salmon across the Northeast Pacific Ocean. Fish Fish. 19, 533–546 (2018).
Friedland, K. D. et al. The recruitment of Atlantic salmon in Europe. ICES J. Mar. Sci. 66, 289–304 (2009).
Frainer, A. et al. Climate-driven changes in functional biogeography of Arctic marine fish communities. Proc. Natl Acad. Sci. USA 114, 12202–12207 (2017).
Kortsch, S. et al. Climate change alters the structure of Arctic marine food webs due to poleward shifts of boreal generalists. Proc. R. Soc. B 282, 20151546 (2015).
Jensen, A. J. et al. Cessation of the Norwegian drift net fishery: changes observed in Norwegian and Russian populations of Atlantic salmon. ICES J. Mar. Sci. 56, 84–95 (1999).
Kuparinen, A. & Hutchings, J. A. Genetic architecture of age at maturity can generate either directional or divergent and disruptive harvest-induced evolution. Phil. Trans. R. Soc. B 372, 20160035 (2016).
Hjermann, D. Ø., Ottersen, G. & Stenseth, N. C. Competition among fishermen and fish causes the collapse of Barents Sea capelin. Proc. Natl Acad. Sci. USA 101, 11679–11684 (2004).
Ghalambor, C. K., McKay, J. K., Carroll, S. P. & Reznick, D. N. Adaptive versus non-adaptive phenotypic plasticity and the potential for contemporary adaptation in new environments. Funct. Ecol. 21, 394–407 (2007).
Schindler, D. E. et al. Population diversity and the portfolio effect in an exploited species. Nature 465, 609–612 (2010).
Vähä, J.-P., Erkinaro, J., Niemelä, E. & Primmer, C. R. Life-history and habitat features influence the within-river genetic structure of Atlantic salmon. Mol. Ecol. 16, 2638–2654 (2007).
Vähä, J.-P., Erkinaro, J., Falkegård, M., Orell, P. & Niemelä, E. Genetic stock identification of Atlantic salmon and its evaluation in a large population complex. Can. J. Fish. Aquat. Sci. 74, 327–338 (2016).
Report of the Working Group on North Atlantic Salmon (WGNAS) (International Council for the Exploration of the Sea, 2013).
Pritchard, V. L. et al. Genomic signatures of fine-scale local selection in Atlantic salmon suggest involvement of sexual maturation, energy homeostasis, and immune defence-related genes. Mol. Ecol. 27, 2560–2575 (2018).
Report of the Workshop on Age Determination of Salmon (WKADS) (International Council for the Exploration of the Sea, 2011).
Niemelä, E. et al. Temporal variation in abundance, return rate and life histories of previously spawned Atlantic salmon in a large subarctic river. J. Fish Biol. 68, 1222–1240 (2006).
Niemelä, E. et al. Previously spawned Atlantic salmon ascend a large subarctic river earlier than their maiden counterparts. J. Fish Biol. 69, 1151–1163 (2006).
Aykanat, T., Pritchard, V. L., Lindqvist, M. & Primmer, C. R. From population genomics to conservation and management: a workflow for targeted analysis of markers identified using genome-wide approaches in Atlantic salmon. J. Fish Biol. 89, 2658–2679 (2016).
Falush, D., Stephens, M. & Pritchard, J. K. Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164, 1567–1587 (2003).
Evanno, G., Regnaut, S. & Goudet, J. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol. Ecol. 14, 2611–2620 (2005).
Earl, D. A. & vonHoldt, B. M. STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv. Genet. Resour. 4, 359–361 (2012).
Jakobsson, M. & Rosenberg, N. A. CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics 23, 1801–1806 (2007).
Goudet, J., Raymond, M., De Meeüs, T. & Rousset, F. Testing differentiation in diploid populations. Genetics 144, 1933–1940 (1996).
Wood, S. N. Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. J. R. Stat. Soc. B 73, 3–36 (2011).
R Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2017).
Venables, W. N. & Ripley, B. D. Modern Applied Statistics With S (Springer, New York, 2002).
Fox, J. Effect displays in R for generalised linear models. J. Stat. Softw. 8, 1–27 (2003).
Tataru, P., Simonsen, M., Bataillon, T. & Hobolth, A. Statistical inference in the Wright–Fisher model using allele frequency data. Syst. Biol. 66, e30–e46 (2017).
Wright, S. Evolution in Mendelian populations. Genetics 16, 97–159 (1931).
Fisher, R. A. The Genetical Theory of Natural Selection (Clarendon, Oxford, 1930).
Brooks, S. P. B. & Gelman, A. G. General methods for monitoring convergence of iterative simulations. J. Comput. Graph. Stat. 7, 434–455 (1998).
Lenth, R. V. Least-squares means: the R package lsmeans.J. Stat. Softw. 69, 1–33 (2016).
Gompert, Z. Bayesian inference of selection in a heterogeneous environment from genetic time-series data. Mol. Ecol. 25, 121–134 (2016).
Foll, M., Shim, H. & Jensen, J. D. WFABC: a Wright–Fisher ABC-based approach for inferring effective population sizes and selection coefficients from time-sampled data. Mol. Ecol. Resour. 15, 87–98 (2015).
Waples, R. S. A bias correction for estimates of effective population size based on linkage disequilibrium at unlinked gene loci. Conserv. Genet. 7, 167–184 (2006).
Do, C. et al. NeEstimator v2: re-implementation of software for the estimation of contemporary effective population size (Ne) from genetic data. Mol. Ecol. Resour. 14, 209–214 (2014).
Waples, R. S. & Yokota, M. Temporal estimates of effective population size in species with overlapping generations. Genetics 175, 219–233 (2007).
Belgorodski, N., Greiner, M., Tolksdorf, K. & Schueller, K. rriskDistributions: Fitting Distributions to Given Data or Known Quantiles R package version 2.0 (R Foundation for Statistical Computing, 2017).
Allendorf, F. W. & Luikart, G. Conservation and the Genetics of Populations (Blackwell, Oxford, 2007).
Plummer, M. JAGS Version 4.3.0 User Manual (2017); http://www.stat.yale.edu/~jtc5/238/materials/jags_4.3.0_manual_with_distributions.pdf
We thank numerous fishers who participated in the collection of scales and phenotypic information over the 40-year study period, E. Niemelä for starting the programme and looking after contacts with fishers, J. Kuusela for organizing the collection of samples from the archive, and several scale readers—especially J. Haantie. This project received funding from the Academy of Finland (projects numbers 284941, 286334, 307593, 302873 and 318939) as well as the European Research Council under the European Union’s Horizon 2020 research and innovation programme (grant agreement number 742312) and the University of Helsinki.
The authors declare no competing interests.
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Czorlich, Y., Aykanat, T., Erkinaro, J. et al. Rapid sex-specific evolution of age at maturity is shaped by genetic architecture in Atlantic salmon. Nat Ecol Evol 2, 1800–1807 (2018). https://doi.org/10.1038/s41559-018-0681-5
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