Pleiotropy—when a single mutation affects multiple traits—is a controversial topic with far-reaching implications. Pleiotropy plays a central role in debates about how complex traits evolve and whether biological systems are modular or are organized such that every gene has the potential to affect many traits. Pleiotropy is also critical to initiatives in evolutionary medicine that seek to trap infectious microbes or tumors by selecting for mutations that encourage growth in some conditions at the expense of others. Research in these fields, and others, would benefit from understanding the extent to which pleiotropy reflects inherent relationships among phenotypes that correlate no matter the perturbation (vertical pleiotropy). Alternatively, pleiotropy may result from genetic changes that impose correlations between otherwise independent traits (horizontal pleiotropy). We distinguish these possibilities by using clonal populations of yeast cells to quantify the inherent relationships between single-cell morphological features. Then, we demonstrate how often these relationships underlie vertical pleiotropy and how often these relationships are modified by genetic variants (quantitative trait loci [QTL]) acting via horizontal pleiotropy. Our comprehensive screen measures thousands of pairwise trait correlations across hundreds of thousands of yeast cells and reveals ample evidence of both vertical and horizontal pleiotropy. Additionally, we observe that the correlations between traits can change with the environment, genetic background, and cell-cycle position. These changing dependencies suggest a nuanced view of pleiotropy: biological systems demonstrate limited pleiotropy in any given context, but across contexts (e.g., across diverse environments and genetic backgrounds) each genetic change has the potential to influence a larger number of traits. Our method suggests that exploiting pleiotropy for applications in evolutionary medicine would benefit from focusing on traits with correlations that are less dependent on context.

多效性——当一个突变影响多个性状时——是一个具有深远影响的有争议的话题。多效性在关于复杂性状如何进化以及生物系统是否是模块化的或组织起来使得每个基因都有可能影响许多性状的争论中发挥着核心作用。多效性对于进化医学的倡议也至关重要，这些倡议试图通过选择在某些条件下促进生长而牺牲其他条件下的突变来捕获传染性微生物或肿瘤。这些领域和其他领域的研究将受益于了解多效性在多大程度上反映了无论扰动如何都相关的表型之间的内在关系（垂直多效性）。或者，多效性可能是由遗传变化引起的，遗传变化在其他独立性状之间强加了相关性（水平多效性）。我们通过使用酵母细胞的克隆群体来量化单细胞形态特征之间的内在关系来区分这些可能性。然后，我们证明了这些关系如何频繁地成为垂直多效性的基础，以及这些关系如何经常被通过水平多效性作用的遗传变异（数量性状位点 [QTL]）修改。我们的全面筛选测量了数十万个酵母细胞中的数千个成对性状相关性，并揭示了垂直和水平多效性的充分证据。此外，我们观察到性状之间的相关性会随着环境、遗传背景和细胞周期位置的变化而变化。这些不断变化的依赖性提出了对多效性的微妙看法：生物系统在任何给定环境下都表现出有限的多效性，但跨环境（例如，跨不同的环境和遗传背景），每个遗传变化都有可能影响更多的性状。我们的方法表明，利用多效性在进化医学中的应用将受益于关注具有较少依赖于背景的相关性特征。