EAGER: Physiological Canalization and Individual Variation

早上人们醒来吃早餐，中午吃午餐，晚上吃晚餐。如果天气太热或太冷，就打开空调或炉子。 当人们生病或遭受撕裂伤时，他们会寻求抗生素治疗（如果合适）或卧床休息。然而，在野生远交生物种群的自然环境中，生命有许多意想不到的环境变化。对于鱼类Fundulus heteroclitus（本研究的重点），环境是不可预测的，而且变化极大。在它们的自然栖息地，底栖动物生活在一个不断变化的环境中，因为它们在北美沿海的河口上游觅食。在低潮时，它们要么在较深的潮汐小溪中，经历较低的海洋温度（10-25°C），要么，特别是在春季和夏季，可以暂时停留在温暖的潮汐池（25-35°C）的上河口。当它们随着潮水进入沼泽地时，它们每天都会经历盐度的变化，从最高浓度的海水（千分之33，ppt）到大雨时的不到3 ppt。这个应用程序的重点是环境变化如何影响mRNA表达的表型变异。本申请中提出的假设是，大多数自然种群存在的可变生态环境隐藏了许多变异。 反直觉的假设是，对于一个基因子集来说，对可变环境的生理反应限制了mRNA表达的个体间变异，从而掩盖了功能性遗传变异或多态性。如果是正确的，那么基因表达的生理渠道隐藏了遗传变异。因此，这项研究提供了一个新的视角，来了解如此多的隐藏遗传变异是如何产生的，以及为什么它会在自然种群中持续存在。没有旨在了解环境如何影响mRNA表达差异的先前分析，并且此类研究的主要障碍是估计差异需要具有大样本量的特定实验设计。这种应用克服了设计上的挑战，并将产生独特的统计分析，基因表达的方差是如何随环境变化的，进而影响进化过程。这项研究的根本重要性在于，它探索了许多遗传变异可能被隐藏的机制，并解决了如何在自然物种种群中保持大量的遗传变异。这些发现有可能极大地改变人们对在标准的、控制良好的实验室条件下进行的实验结果的看法，从而影响生理学、进化和人类健康研究。首先，对科学界的贡献包括关于基因表达、cDNA序列和近端启动子的大型数据集，这些数据集可用于代谢、生理适应和基因表达调控的其他研究。这些数据将以电子方式提供。第二，研究生将接受包括基因组学、生态学和生理学在内的各种生物学领域以及统计分析方面的培训。最后，本科生将通过与迈阿密大学的项目互动来吸引这个项目，该项目从代表性不足的群体中招募学生，并让他们参与实际的科学研究。

In the morning people wake up and have breakfast, they eat lunch around noon, and in the evening they eat dinner. If it is too hot, or too cold, one turns on the air conditioner or the furnace. When people are sick or suffering from a laceration, they seek treatment with antibiotics (if appropriate) or rest in bed. However, in the natural environment for wild outbred populations of organisms, life has many more unexpected environmental variations. For the fish Fundulus heteroclitus (the focus of this proposed study), the environment is both unpredictable and extremely variable. In their natural habitat Fundulus live in a constantly changing environment because they feed in the upper estuaries of coastal North America. At low tides they are either in deeper tidal creeks experiencing lower ocean temperatures (10-25°C) or, especially in spring and summer, can become temporarily lodged in the upper estuaries in warm tidal pools (25-35°C). They experience daily variation in salinity as they move with the tide up into marshes, from full strength seawater (33 parts per thousand, ppt) to less than 3 ppt if it is raining heavily. This application focuses on how environmental variation affects phenotypic variation in mRNA expression. The hypothesis proposed in this application is that much variation is hidden by the variable ecological settings where most natural populations exist. The counter-intuitive hypothesis is that for a subset of genes, the physiological responses to variable environments constrain inter-individual variation in mRNA expression, and in so doing mask functional genetic variation or polymorphisms. If correct, then physiological canalization of gene expression hides genetic variation. Thus, this research provides a novel perspective on how so much hidden genetic variation arises and why it persists in natural populations. There are no prior analyses aimed at understanding how the environment affects the variance in mRNA expression, and a major impediment to such studies is that estimating variance requires specific experimental designs with large sample sizes. This application overcomes the design challenges, and will yield unique statistical analyses of how the variance in gene expression is a function of the environment, and in turn affects evolutionary processes. The fundamental importance of this proposed research is that it explores mechanisms whereby much genetic variation may be hidden, and addresses how large amounts of genetic variation can be maintained in natural species populations. The findings have the potential to significantly alter views of the results of experiments conducted under standard, well-controlled laboratory conditions, and thus influence physiological, evolutionary and human health research.This research has broader impacts in three areas. First, contributions to the scientific community include a large dataset on gene expression, cDNA sequences, and proximal promoters that can be used in other studies on metabolism, physiological acclimation and the regulation of gene expression. These data will be made available publically. Second, a graduate student will be trained in a diversity of biological fields, including genomics, ecology and physiology, and in statistical analyses. Finally, undergraduate students will be attracted to this project through interactions with programs at the University of Miami that recruit students from underrepresented groups and engage them in hands-on scientific research.