Pleiotropy, the control of multiple phenotypes by a single locus, is expected to slow the rate of adaptation by increasing the chance that beneficial alleles also have deleterious effects. However, a prediction arising from classical theory of quantitative trait evolution states that pleiotropic alleles may have a selective advantage when phenotypes are distant from their selective optima. We examine the role of pleiotropy in regulating adaptive differentiation among populations of common ragweed (Ambrosia artemisiifolia); a species that has recently expanded its North American range due to human-mediated habitat change. We employ a phenotype-free approach by using connectivity in gene networks as a proxy for pleiotropy. First, we identify loci bearing footprints of local adaptation, and then use genotype-expression mapping and co-expression networks to infer the connectivity of the genes. Our results indicate that the putatively adaptive loci are highly pleiotropic, as they are more likely than expected to affect the expression of other genes, and they reside in central positions within the gene networks. We propose that the conditionally advantageous alleles at these loci avoid the cost of pleiotropy by having large phenotypic effects that are beneficial when populations are far from their selective optima. We further use evolutionary simulations to show that these patterns are in agreement with a model where populations face novel selective pressures, as expected during a range expansion. Overall, our results suggest that highly connected genes may be targets of positive selection during environmental change, even though they likely experience strong purifying selection in stable selective environments.

多效性，即通过单个基因座控制多种表型，预计会通过增加有益等位基因也产生有害影响的机会来减缓适应速度。然而，经典数量性状进化理论的预测表明，当表型远离其选择最佳值时，多效性等位基因可能具有选择优势。我们研究了多效性在调节普通豚草（ Ambrosia artemisiifolia ）种群适应性分化中的作用；由于人类介导的栖息地变化，该物种最近扩大了其北美范围。我们采用无表型的方法，利用基因网络中的连接性作为多效性的代表。首先，我们确定带有局部适应足迹的基因座，然后使用基因型表达作图和共表达网络来推断基因的连接性。我们的结果表明，假定的适应性基因座具有高度多效性，因为它们比预期更有可能影响其他基因的表达，并且它们位于基因网络内的中心位置。我们提出，这些位点上的条件有利等位基因通过具有大的表型效应来避免多效性的成本，当群体远离其选择最佳值时，这些表型效应是有益的。我们进一步使用进化模拟来表明，这些模式与种群面临新的选择压力的模型是一致的，正如在范围扩张期间所预期的那样。总的来说，我们的结果表明，高度连接的基因可能是环境变化期间正选择的目标，尽管它们可能在稳定的选择环境中经历强烈的净化选择。