Genetic Variation, Simplicity, and Evolutionary Constraints for Function-Valued Traits
Genetic Variation, Simplicity, and Evolutionary Constraints for Function-Valued Traits
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功能价值性状的遗传变异、简单性和进化约束
作者：
J. Kingsolver;N. Heckman;Jonathan Zhang;P. Carter;Jennifer L. Knies;J. Stinchcombe;K. Meyer
理解遗传变异的模式和对连续反应规范、生长轨迹和其他函数值特征的限制是具有挑战性的。我们描述和说明了一种最新的分析方法，简单基础分析(SBA)，它使用遗传方差-协方差(G)矩阵来识别遗传变异的“简单”方向和具有直接生物学解释的遗传约束。我们讨论了由主成分分析(PCA)识别的特征向量(主成分)与由SBA识别的简单基(SB)向量之间的相似性。我们将这些方法应用于从10个热性能曲线和生长曲线研究中获得的估计G矩阵。我们的结果表明，所有年龄段的总体体型变化代表了生长曲线的大部分遗传差异。相比之下，在所有情况下，所有温度下整体性能的变化不到热性能曲线遗传差异的三分之一，在较高温度和较低温度下的性能之间的遗传权衡往往是重要的。这些分析还确定了生长曲线中早期和后期生长模式的潜在遗传限制。我们认为，SBA可以作为主成分分析的一个有用的补充或替代，用于识别生物可解释的遗传变异方向和函数值性状的限制。
Understanding the patterns of genetic variation and constraint for continuous reaction norms, growth trajectories, and other function-valued traits is challenging. We describe and illustrate a recent analytical method, simple basis analysis (SBA), that uses the genetic variance-covariance (G) matrix to identify “simple” directions of genetic variation and genetic constraints that have straightforward biological interpretations. We discuss the parallels between the eigenvectors (principal components) identified by principal components analysis (PCA) and the simple basis (SB) vectors identified by SBA. We apply these methods to estimated G matrices obtained from 10 studies of thermal performance curves and growth curves. Our results suggest that variation in overall size across all ages represented most of the genetic variance in growth curves. In contrast, variation in overall performance across all temperatures represented less than one-third of the genetic variance in thermal performance curves in all cases, and genetic trade-offs between performance at higher versus lower temperatures were often important. The analyses also identify potential genetic constraints on patterns of early and later growth in growth curves. We suggest that SBA can be a useful complement or alternative to PCA for identifying biologically interpretable directions of genetic variation and constraint in function-valued traits.