Data from: Compensatory evolution in RNA secondary structures increases substitution rate variation among sites

There is growing evidence that interactions between biological molecules (e.g., RNA-RNA, protein-protein, RNA-protein) place limits on the rate and trajectory of molecular evolution. Here, by extending Kimura's model of compensatory evolution at interacting sites, we show that the ratio of transition to transversion substitutions (κ) at interacting sites should be equal to the square of the ratio at independent sites. Because transition mutations generally occur at a higher rate than transversions, the model predicts that κ should be higher at interacting sites than at independent sites. We tested this prediction in 10 RNA secondary structures by comparing phylogenetically derived estimates of κ in paired sites within stems (κ(p)) and unpaired sites within loops (κ(u)). Eight of the 10 structures showed an excellent match to the quantitative predictions of the model, and 9 of the 10 structures matched the qualitative prediction κ(p) > κ(u). Only the Rev response element from the human immunovirus (HIV) genome showed the reverse pattern, with κ(p) < κ(u). Although a variety of evolutionary forces could produce quantitative deviations from the model predictions, the reversal in magnitude of κ(p) and κ(u) could be achieved only by violating the model assumption that the underlying transition (or transversion) mutation rates were identical in paired and unpaired regions of the molecule. We explore the ability of the APOBEC3 enzymes, host defense mechanisms against retroviruses, which induce transition mutations preferentially in single-stranded regions of the HIV genome, to explain this exception to the rule. Taken as a whole, our findings suggest that kappa may have utility as a simple diagnostic to evaluate proposed secondary structures.

越来越多的证据表明，生物分子间的相互作用（例如RNA-RNA、蛋白质-蛋白质、RNA-蛋白质）会制约分子进化的速率与进化轨迹。在此，我们通过拓展交互位点的木村补偿进化模型（Kimura's model of compensatory evolution），证明了交互位点的转换与颠换替换比值（κ）应等于独立位点该比值的平方。由于转换突变的发生速率通常高于颠换突变，该模型预测交互位点的κ值应高于独立位点。我们通过比较茎区配对位点（κ_p）与环区非配对位点（κ_u）的系统发育推导κ估计值，在10种RNA二级结构中验证了这一预测。10种结构中有8种与模型的定量预测高度吻合，10种中有9种符合κ_p > κ_u的定性预测。仅来自人类免疫缺陷病毒（Human Immunodeficiency Virus，HIV）基因组的Rev应答元件呈现相反模式，即κ_p < κ_u。尽管多种进化力量可导致与模型预测的定量偏差，但κ_p与κ_u的数值反转仅能通过违背模型假设来实现——即分子配对区与非配对区的基础转换（或颠换）突变速率并不相同。我们探讨了APOBEC3酶——宿主抗逆转录病毒防御机制，可优先在HIV基因组单链区诱导转换突变——能否解释这一反常现象。总体而言，我们的研究结果表明，κ可作为一种简便的诊断工具，用于评估已提出的RNA二级结构。