Katie E. Lotterhos, Sam Yeaman, Jon Degner, Sally Aitken, Kathryn HodginsPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"
<p>Background: Physical linkage among genes shaped by different sources of selection is a fundamental aspect of genetic architecture. Theory predicts that evolution in complex environments selects for modular genetic architectures and high recombination rates among loci shaped by different sources of selection. However, limited data exist to test these predictions because the field lacks consensus for how to control for intercorrelated environmental variables. Here, we introduce a co-association network analysis, which clusters loci based on differing environmental associations, and use it to study the genetic architecture of local adaptation to climate in lodgepole pine (Pinus contorta). Results: We identified many modules of genes associated with distinct environments (aridity, freezing, geography), and discovered low recombination rates among some candidate genes in different modules. We observed limited evidence for environmental pleiotropic effects on distinct aspects of climate. We also found limited correspondence between the modularity of co-association networks and gene regulatory networks. We compared co-association networks to associations with principal components, and found the latter can lead to misinterpretation. Finally, we used simulations to illustrate the benefits and caveats of co-association networks. Conclusions: Co-association networks provided a useful framework for studying modularity. Our results supported the prediction that evolution to complex environments selects for modular genetic architectures, but some of our results went against the prediction that selection would increase recombination among loci experiencing different sources of selection. These results give new insight into evolutionary debates about the extent of modularity and pleiotropy in the evolution of genetic architectures.</p>
