Signatures of selection in embryonic transcriptomes of lizards adapting in parallel to cool climate

Nathalie Feiner, Alfredo Rago, Geoffrey M. While, Tobias Uller

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Populations adapting independently to the same environment provide important insights into the repeatability of evolution at different levels of biological organization. In the 20th century, common wall lizards (Podarcis muralis) from southern and western Europe were introduced to England, north of their native range. Nonnative populations of both lineages have adapted to the shorter season and lower egg incubation temperature by increasing the absolute rate of embryonic development. Here, we tested if this adaptation is accompanied by signatures of directional selection in the transcriptomes of early embryos and, if so, if nonnative populations show adaptive convergence. Embryos from nonnative populations exhibited gene expression profiles consistent with directional selection following introduction, but different genes were affected in the two lineages. Despite this, the functional enrichment of genes that changed their expression following introduction showed substantial similarity between lineages, and was consistent with mechanisms that should promote developmental rate. Moreover, the divergence between nonnative and native populations was enriched for genes that were temperature-responsive in native populations. These results indicate that small populations are able to adapt to new climatic regimes, but the means by which they do so may largely be determined by founder effects and other sources of genetic drift.

    Original languageEnglish
    Pages (from-to)67-81
    Number of pages15
    JournalEvolution
    Volume72
    Issue number1
    DOIs
    Publication statusPublished - 2018 Jan 1

    Subject classification (UKÄ)

    • Evolutionary Biology

    Free keywords

    • Climate
    • convergent evolution
    • lizard
    • nonnative
    • thermal adaptation
    • transcriptomics

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