Center for Genomics and Systems Biology, Department of Biology, New York University, New York, New York, United States of America.
Center for Mechanisms of Evolution, Biodesign Institutes, School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America.
PLoS Biol. 2020 Aug 17;18(8):e3000836. doi: 10.1371/journal.pbio.3000836. eCollection 2020 Aug.
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.
当单个突变影响多个性状时，就会出现多效性——这是一个具有深远影响的争议性话题。多效性在关于复杂性状如何进化以及生物系统是模块化的还是组织化的，以至于每个基因都有可能影响许多性状的争论中起着核心作用。多效性对于进化医学中的一些举措也至关重要，这些举措试图通过选择在某些条件下促进生长而在其他条件下牺牲生长的突变来捕获传染性微生物或肿瘤。在这些领域和其他领域的研究将受益于理解多效性在多大程度上反映了表型之间的固有关系，这些关系无论受到何种干扰（垂直多效性）都会相关。或者，多效性可能是由于遗传变化导致的，这些变化在本来独立的性状之间产生相关性（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固有关系，从而区分这些可能性。然后，我们展示了这些关系在多大程度上是垂直多效性的基础，以及这些关系在多大程度上被通过水平多效性作用的遗传变异（数量性状位点[QTL]）所改变。我们的全面筛选测量了数十万酵母细胞中的数千对性状相关性，并揭示了垂直多效性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可以随环境、遗传背景和细胞周期位置而变化。这些变化的依赖性表明了对多效性的一种细微看法：在任何给定的情况下，生物系统都表现出有限的多效性，但在不同的情况下（例如，在不同的环境和遗传背景下），每个遗传变化都有可能影响更多的性状。我们的方法表明，为了在进化医学中的应用而利用多效性，最好关注那些与上下文依赖性较小的性状。
