Estimates of molecular convergence reveal pleiotropic genes underlying adaptive variation across teleost fish

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Teleosts are the most diverse group of vertebrates on earth. Their diversity is a testament to the combined effects of genetic, developmental, and evolutionary forces. However, disentangling the interactions between these forces is challenging due to the complexity of the genotype-phenotype relationship and the masking of adaptive genetic signals by genetic noise. Estimates of molecular convergence where changes in the sequence of protein-coding genes lead to identical amino acid substitution across multiple lineages provide strong evidence of adaptive evolution. In this study, we estimated signals for molecular convergence in protein-coding genes across 143 teleost genomes to identify genes and processes that experienced adaptive changes. We find that genes with signals of molecular convergence are implicated in diverse processes ranging from embryonic development, tissue morphogenesis, metabolism, to hormone and heat response. Some convergent substitutions are located on functionally important sites on proteins potentially providing the molecular basis for adaptations to hypoxia, salinity fluctuations, and varying skeletal morphologies. Additionally, single-cell RNA sequencing data from zebrafish showed that the convergent genes have dynamic expression across various cell types during embryonic development. These results highlight the functional importance of the convergent genes as well as their pleiotropic nature. Although traditionally considered a source of genetic constraint, we argue that adaptation via changes in pleiotropic genes are particularly advantageous during periods of ecological shifts. We present the pleiotropic release model which describes how adaptive variation on pleiotropic genes can have large fitness effects, allowing organisms to overcome selective pressures during periods of ecological shifts.

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  1. Thank you for your interest in our preprint.

    A well-resolved time-calibrated tree is essential for comparative studies. Constructing phylogenies requires careful attention to multiple aspects of the data such as deciding on the breadth of species or depth of genes. As a result, we used the tree estimated from timetree which synthesises data from multiple publications (where the objective was to infer relationships) to construct the tree.

    If we constructed the tree ourselves, any error in the construction would be propagated to the convergence analysis. Although the omegaC metric is robust to topological errors, for the sake of thoroughness we decided to use a phylogeny from timetree as it better representation of our current knowledge of species relationships.

  2. We ran the analysis using a rooted time-calibrated species tree obtained from 33.

    What was the rationale for using a tree from as opposed inferring one from the gene families?

    I imagine that a comparing the effects of using timetree vs. an inferred tree on CSUBST outputs would be enlightening. Such a comparison could be an empirical way to assess the effects of topological error in this data set (and would be a nice complement to some of the analyses in Fukushima and Pollock).