Importance of Acclimatory and Adaptive Response to the Environment

第一部分：动物如何在不断变化的环境条件下生存和繁荣取决于它们的生理反应和基因的适应性变化。生理反应包括动物一生中代谢率和影响新陈代谢的蛋白质的变化。这些可逆的、非遗传的变化在不断变化的环境中缓冲了个人的健康。然而，这些生理反应是有限的，动物可能会进化出影响它们新陈代谢的基因变化，提高它们的存活率。这项研究调查了生理变化和适应性变化之间的相互作用，以更好地了解影响健康和健身的机制。这项研究利用新的DNA测序技术来确定环境之间1万种遗传差异，并将这些差异与基因表达的测量相关联。这项研究的数据将向社会通报在各种环境中增强健康的基因和基因表达。这项研究包括对来自不同经济和社会背景的本科生和高中生的培训。第二部分：为了提高我们预测气候变化反应的能力，我们需要了解适应反应的相对重要性和适应差异的可能性。虽然已经有几个很好的脊椎动物类群之间的热适应分化模型和许多驯化反应的例子，但很少有研究考察驯化反应和适应分化之间的相互作用。为了检验这种相互作用，这项研究首先测量了新陈代谢的变化和热习服的影响，然后使用这些测量中的变化来询问mRNA和DNA变化的重要性。这项研究的两个主要目标是利用测序的基因分型提供数万个单核苷酸多态，并应用RNA-Seq来测量大多数表达的基因，以确定1)三个热排出物群体之间的核苷酸差异是否具有相似的适应性差异，以及2)mRNA表达的适应性和适应性变化是否影响相同的基因座。我们的预测是，mRNA表达的适应性和适应性变化涉及不同的基因，许多基因座可以影响代谢的变化，因此不同的群体将有不同的mRNA表达模式，从统计学上解释代谢的变化，同样，与mRNA表达或代谢变化相关的SNPs在不同的群体中也将不同。这些预测表明，由于参与生理反应的基因座与受适应性分化影响的基因座不同，与涉及相同的基因座相比，适应性变化的可能性更大。此外，我们预测有许多不同的方式来实现新陈代谢的变化，这意味着有许多不同的多态基因座可以作用于选择。提供支持或否定这些假说的数据将增强我们对进化生理学的理解，从而显著影响我们预测气候变化对物种丰度和生存的影响的能力。

Part 1: How animals survive and prosper under changing environmental conditions depends on both their physiological responses and adaptive changes in their genes. Physiological responses include changes in the metabolic rates and the proteins that affect metabolism during the animal's lifetime. These reversible, non-genetic changes buffer an individual's health in a changing environment. Yet, there are limits to these physiological responses, and animals may evolve genetic changes that affect their metabolism and enhance their survival. This research investigates the interaction between physiological and adaptive changes to better understand the mechanisms affecting health and fitness. This research takes advantage of new DNA sequencing technologies to define 10,000s of genetic differences among environments and relate these to measures of gene expression. The data from this research will inform society about the genes and gene expression that enhances health in a variety of environments. Included in this research is the training of undergraduate and high-school students from a diversity of economic and social backgrounds. Part 2:To enhance our ability to predict responses to climate change, we need to understand the relative importance of acclimatory responses and the potential for adaptive divergence. Although there are several good vertebrate models for thermal adaptive divergence among taxa and many acclimation response examples, few studies examine the interaction between acclimatory responses and adaptive divergence. To examine this interaction, this research first measures derived changes in metabolism and the effect of thermal acclimation and then uses the variation in these measures to interrogate the importance of mRNA and DNA variation. Two major goals of this proposed research are to utilize genotyping by sequencing to provide tens of thousands of single nucleotide polymorphisms and apply RNA-Seq to measure most expressed genes to determine if 1) nucleotide divergence among the three thermal effluent populations share similar adaptive divergence and 2) acclimatory and adaptive changes in mRNA expression affect the same loci. Our predictions are that acclimatory and adaptive changes in mRNA expression involve different genes, that many loci can effect a change in metabolism and thus different populations will have different mRNA expression patterns that statistically explain the variation in metabolism, and similarly, that the SNPs associated with changes in mRNA expression or metabolism will differ in different populations. These predictions suggest that because the loci involved in physiological responses are different from those affected by adaptive divergence, there is greater potential for adaptive change than if the same loci were involved. Additionally, we predict that there are many different ways to achieve a change in metabolism, which means that there are many different polymorphic loci that selection can act on. Providing the data to support or reject these hypotheses would enhance our understanding of evolutionary physiology and thus significantly influence our ability to predict climate change effects on species' abundance and survival.