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. 2022 May 25;289(1975):20220352.
doi: 10.1098/rspb.2022.0352. Epub 2022 May 18.

Age-dependent genetic architecture across ontogeny of body size in sticklebacks

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Age-dependent genetic architecture across ontogeny of body size in sticklebacks

Antoine Fraimout et al. Proc Biol Sci. .

Abstract

Heritable variation in traits under natural selection is a prerequisite for evolutionary response. While it is recognized that trait heritability may vary spatially and temporally depending on which environmental conditions traits are expressed under, less is known about the possibility that genetic variance contributing to the expected selection response in a given trait may vary at different stages of ontogeny. Specifically, whether different loci underlie the expression of a trait throughout development and thus providing an additional source of variation for selection to act on in the wild, is unclear. Here we show that body size, an important life-history trait, is heritable throughout ontogeny in the nine-spined stickleback (Pungitius pungitius). Nevertheless, both analyses of quantitative trait loci and genetic correlations across ages show that different chromosomes/loci contribute to this heritability in different ontogenic time-points. This suggests that body size can respond to selection at different stages of ontogeny but that this response is determined by different loci at different points of development. Hence, our study provides important results regarding our understanding of the genetics of ontogeny and opens an interesting avenue of research for studying age-specific genetic architecture as a source of non-parallel evolution.

Keywords: Pungitius; QTL mapping; genetic architecture; genetic correlation; heritability; ontogeny.

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Conflict of interest statement

We declare we have no competing interests.

Figures

Figure 1.
Figure 1.
Heritability and genetic correlations across ages. Strength of the genetic correlations (rG) of body size across ages is represented by the size and colour of each tile of the heatmap. Significance of the genetic correlation estimates is indicated in bold white text and non-significant values in italic white text. The posterior mode of the heritability for body size estimated from the multi-trait model (see 'Material and methods' and electronic supplementary material, figure S3) at each age is shown in the diagonal for each cross (black text). (Online version in colour.)
Figure 2.
Figure 2.
QTL-mapping results for age-specific body size. Results from the four-way QTL-mapping are shown for each cross (a–c) and for body size at each age (Week n). For each cross and each age, panels show whether the QTL are inherited from the sire (M) or the dam (F) along with the dominance effect (D) estimated from model [8] in the main text. Results are based on permutation and the significance threshold (dashed horizontal line) is shown on the logarithm scale (−log10(P); p = 0.05). Colours represent different chromosomes. (Online version in colour.)

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References

    1. Arendt J, Reznick DN. 2008. Convergence and parallelism reconsidered: what have we learned about the genetics of adaptation? Trends Ecol. Evol. 23, 26-32. (10.1016/j.tree.2007.09.011) - DOI - PubMed
    1. Stern DL, Orgogozo V. 2009. Is genetic evolution predictable? Science 323, 746-751. (10.1126/science.1158997) - DOI - PMC - PubMed
    1. Stern DL. 2013. The genetic causes of convergent evolution. Nat. Rev. Genet. 14, 751-764. (10.1038/nrg3483) - DOI - PubMed
    1. Mas A, Lagadeuc Y, Vandenkoornhuyse P. 2020. Reflections on the predictability of evolution: towards a conceptual framework. iScience 23, 101736. (10.1016/j.isci.2020.101736) - DOI - PMC - PubMed
    1. Linnen CR. 2018. Predicting evolutionary predictability. Mol. Ecol. 27, 2647-2650. (10.1111/mec.14716) - DOI - PubMed

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