Modularity of genes involved in local adaptation to climate despite physical linkage

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 favored for alleles with similar pleiotropic effects, with increased recombination favored 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 identify many clusters of candidate genes and SNPs associated with distinct environments, including aspects of aridity and freezing, and discover low recombination rates among some candidate genes in different clusters. Only a few genes contain SNPs with effects on more than one distinct aspect of climate. There is limited correspondence between co-association networks and gene regulatory networks. We further show how associations with environmental principal components can lead to misinterpretation. Finally, simulations illustrate both benefits and caveats of co-association networks.

Conclusions: Our results support the prediction that different selection pressures favor 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.

研究背景：承受不同选择压力（selection pressure）的基因之间的连锁会降低自然选择的作用效率。理论预测，当局部适应（local adaptation）由复杂且非协变的胁迫（stress）驱动时，具有相似多效性效应（pleiotropic effects）的等位基因（allele）更易受到选择青睐，进而增强连锁；具有相反多效性效应的等位基因则更易受到选择青睐，从而提升重组率。本研究提出了一套基于共关联网络分析（co-association network analysis）的检验框架，该方法可基于不同的关联模式对基因座（locus）进行聚类。我们借助该框架，基于与环境的关联模式，研究了扭叶松（Pinus contorta）对气候的局部适应的遗传架构。

研究结果：本研究鉴定出多个与不同环境（包括干旱与低温相关性状）相关联的候选基因及单核苷酸多态性（Single Nucleotide Polymorphisms，SNPs）聚类模块，并发现不同聚类模块中的部分候选基因间存在低重组率。仅有少量基因携带的SNPs可同时影响多种不同的气候维度。共关联网络与基因调控网络之间仅存在有限的对应关系。本研究进一步阐明，与环境主成分的关联模式可能会导致解读偏差。最后，模拟实验验证了共关联网络分析的优势与局限性。

研究结论：本研究结果支持以下理论预测：不同的选择压力会促进对应不同气候维度的基因类群的演化。但本研究结果与"承受不同选择来源的基因座之间应存在高重组率"的理论预测相悖。本研究结果为遗传架构演化过程中关于模块化程度、多效性及连锁的进化生物学争论提供了新的视角。