Data from: Environmental effects on the structure of the G-matrix

Genetic correlations between traits determine the multivariate response to selection in the short term, and thereby play a causal role in evolutionary change. While individual studies have documented environmentally induced changes in genetic correlations, the nature and extent of environmental effects on multivariate genetic architecture across species and environments remain largely uncharacterized. We reviewed the literature for estimates of the genetic variance-covariance (G) matrix in multiple environments, and compared differences in G between environments to the divergence in G between conspecific populations (measured in a common garden). We found that the predicted evolutionary trajectory differed as strongly between environments as it did between populations. Between-environment differences in the underlying structure of G (total genetic variance and the relative magnitude and orientation of genetic correlations) were equal to or greater than between-population differences. Neither environmental novelty nor the difference in mean phenotype predicted these differences in G. Our results suggest that environmental effects on multivariate genetic architecture may be comparable to the divergence that accumulates over dozens or hundreds of generations between populations. We outline avenues of future research to address the limitations of existing data and characterize the extent to which lability in genetic correlations shapes evolution in changing environments.性状间的遗传相关决定了短期多变量选择响应，进而在演化改变中发挥因果作用。尽管已有单项研究记录了环境诱导的遗传相关变化，但跨物种与跨环境的环境因子对多变量遗传架构的影响本质与范围，在很大程度上仍未被系统阐明。我们检索了多环境下遗传方差-协方差（G）矩阵估算的相关文献，并将不同环境间的G矩阵差异，与同种种群（在同质园（common garden）中测定）间的G矩阵分化进行了对比分析。结果发现，不同环境间的预测演化轨迹差异，与种群间的轨迹差异同样显著。G矩阵内在结构（包括总遗传方差、遗传相关的相对大小与方向）的环境间差异，等于或大于种群间差异。无论是环境的新颖性，还是种群间的平均表型差异，均无法预测这些G矩阵差异。我们的研究结果表明，环境对多变量遗传架构的影响，或许可与种群间数十乃至数百代积累的遗传分化相媲美。最后，我们概述了未来的研究方向，以解决现有数据存在的局限性，并表征遗传相关的易变性在变化环境中对演化的塑造程度。