Pleiotropy: patterns, mechanisms, and evolutionary consequences

项目总结 PI研究计划的长期目标是了解分子遗传机制和 表型变异和进化的驱动力。多效性是最常见但却最不为人所知的 遗传学中的现象。它指的是观察到一个突变会影响多个表型性状。 多效性可能是协调的，也可能是拮抗的，这取决于突变对多个性状的影响 方向相同或相反(当方向可对齐时)。多效性的，尤指对抗性的 多效性，被广泛引用于衰老、癌症、遗传病、性行为的解释和模型中。 冲突、合作、进化约束、适应、新功能化和物种形成等 一些事情。这个项目解决了我们对多效性理解中的三个关键差距：模式、机制和 进化的后果。首先，虽然零突变的环境多效性已经被广泛地 研究发现，对于非零突变来说，情况并非如此。该项目将使用高吞吐量方法来 确定一个酵母RNA基因和四个蛋白质基因在12个环境中的体内适应情况。 每个景观将包括20,000个基因类型，为诱导一般情况提供前所未有的大量数据 环境多效性原则。更重要的是，这些数据将允许推断健身效果 一个环境中的突变与另一个环境中的突变，这将有助于解释和预测 自然界的进化。第二，虽然多效性通常是从突变的角度来研究的，但另一种 硬币的另一面是经常受到相同突变影响的表型特征之间的关系。 密度依赖的种群增长的最大增长率r和承载能力K是关键的生活史 许多生态和进化理论的基础特征，并与抗击 病原体和肿瘤。虽然r和K通常被认为是负相关的，但r-K两者都是权衡 “交易”已经被观察到了。然而，这些关系中的每一个都不是在什么情况下 这些关系的原因也没有得到很好的理解。这些问题将在酵母中由 影响r和K的数量性状基因座定位及500个单基因缺失菌株的r和K估算 在多种环境中，然后对影响R和K的生物过程进行建模。第三，如果突变 在一个环境中有很大的好处在其他环境中通常是有害的，一个适应环境的人口 尽管有持续而强烈的选择，但对不断变化的环境的适应性替代可能很少。 该项目将使用酵母在恒定和变化中的实验进化来验证上述假设 环境。如果得到支持，这一假设将深刻改变我们对 从种内和种间比较估计的非同义/同义替换率比率， 影响对遗传漂移和正向选择在分子进化中的相对作用的评估。

PROJECT SUMMARY The long-term objective of the PI's research program is to understand the molecular genetic mechanisms and driving forces of phenotypic variation and evolution. Pleiotropy is one of the most common yet least understood phenomena in genetics. It refers to the observation that one mutation impacts multiple phenotypic traits. Pleiotropy may be concordant or antagonistic, depending on whether the mutational effects on multiple traits are in the same or opposite directions (when the directions are alignable). Pleiotropy, especially antagonistic pleiotropy, is widely invoked in explanations and models of senescence, cancer, genetic disease, sexual conflict, cooperation, evolutionary constraint, adaptation, neofunctionalization, and speciation, among other things. This project addresses three key gaps in our understanding of pleiotropy: patterns, mechanisms, and evolutionary consequences. First, while the environmental pleiotropy of null mutations has been extensively studied, the same is not true for non-null mutations. This project will use a high-throughput method to determine the in vivo fitness landscapes of one yeast RNA gene and four protein genes in 12 environments. Each landscape will include >20,000 genotypes, providing unprecedentedly large data for inducing general principles of environmental pleiotropy. More importantly, these data will allow inferring fitness effects of mutations in one environment from those in another, which will be instrumental in explaining and predicting evolution in nature. Second, while pleiotropy is typically studied from the perspective of mutations, the other side of the coin is the relationship between phenotypic traits that are often impacted by the same mutations. Maximum growth rate r and carrying capacity K of density-dependent population growth are key life-history traits fundamental to many ecological and evolutionary theories and are directly relevant to combating pathogens and tumors. Although r and K are generally thought to be negatively correlated, both r-K tradeoffs and "tradeups" have been observed. However, neither the conditions under which each of these relationships occur nor the causes of these relationships are well understood. These questions will be addressed in yeast by mapping quantitative trait loci influencing r and K and estimating the r and K of 500 single-gene deletion strains in multiple environments, followed by modeling of biological processes impacting r and K. Third, if mutations with large benefits in one environment are generally deleterious in other environments, a population adapting to a changing environment may have few adaptive substitutions, despite continuous and strong selections. This project will test the above hypothesis using experimental evolution of yeast in constant vs. changing environments. If supported, this hypothesis will profoundly alter our interpretation of the nonsynonymous/synonymous substitution rate ratio estimated from intra and interspecific comparisons, impacting the assessment of the relative roles of genetic drift and positive selection in molecular evolution.