Modularity of genes involved in local adaptation to climate despite physical linkage
Abstract
This preprint has been reviewed and recommended by Peer Community In Evolutionary Biology (<ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://doi.org/10.24072/pci.evolbiol.100050">https://doi.org/10.24072/pci.evolbiol.100050</ext-link>)
Background
Linkage among genes experiencing different selection pressures can make natural selection less efficient. Theory predicts that when local adaptation is driven by complex and non-covarying stresses, increased linkage is favoured for alleles with similar pleiotropic effects, with increased recombination favoured among alleles with contrasting pleiotropic effects. Here, we introduce a framework to test these predictions with a co-association network analysis, which clusters loci based on differing associations. We use this framework to study the genetic architecture of local adaptation to climate in lodgepole pine (Pinus contorta), based on associations with environments.
Results
We identified many clusters of candidate genes and SNPs associated with distinct environments (aspects of aridity, freezing, etc.), and discovered low recombination rates among some candidate genes in different clusters. Only a few genes contained SNPs with effects on more than one distinct aspect of climate. There was limited correspondence between co-association networks and gene regulatory networks. We further showed how associations with environmental principal components can lead to misinterpretation. Finally, simulations illustrated both benefits and caveats of co-association networks.
Conclusions
Our results supported the prediction that different selection pressures favored the evolution of distinct groups of genes, each associating with a different aspect of climate. But our results went against the prediction that loci experiencing different sources of selection would have high recombination among them. These results give new insight into evolutionary debates about the extent of modularity, pleiotropy, and linkage in the evolution of genetic architectures.
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