Department of Marine and Environmental Sciences, Northeastern Marine Science Center, 430 Nahant Rd, Nahant, MA, 01908, USA.
Department of Biological Sciences, University of Calgary, Calgary, AB, T2N1N4, Canada.
Genome Biol. 2018 Oct 5;19(1):157. doi: 10.1186/s13059-018-1545-7.
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.
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.
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.
经历不同选择压力的基因之间的连锁可能会降低自然选择的效率。理论预测,当局部适应是由复杂且不相关的压力驱动时,具有相似多效性效应的等位基因的连锁增加是有利的,而具有相反多效性效应的等位基因之间的重组增加是有利的。在这里,我们引入了一个框架,通过共关联网络分析来检验这些预测,该分析根据不同的关联对位点进行聚类。我们使用这个框架来研究基于与环境的关联的辐射松(Pinus contorta)对气候的局部适应的遗传结构。
我们确定了许多与不同环境相关的候选基因和 SNP 聚类,包括干旱和冻结方面,并发现不同聚类中的一些候选基因之间的重组率较低。只有少数基因包含影响不止一个气候方面的 SNP。共关联网络与基因调控网络之间的对应关系有限。我们进一步展示了与环境主成分的关联如何导致错误的解释。最后,模拟说明了共关联网络的优点和缺点。
我们的结果支持这样的预测,即不同的选择压力有利于不同的基因群的进化,每个基因群都与气候的不同方面相关。但我们的结果与不同选择源的基因座之间会有较高重组的预测相矛盾。这些结果为关于遗传结构进化中的模块性、多效性和连锁程度的进化争论提供了新的见解。