Genomic analysis of feeding behavior and fitness in Drosophila

描述(申请人提供)：虽然能量平衡是喂养行为的核心，但决定是否进食不仅仅是一个饥饿的问题。在食物往往稀缺的自然环境中，评估获取食物的收益超过寻找和获取食物的能源成本或风险，以及决定是寻找食物还是留在原地保存能量对生存至关重要。然而，寻找食物决策行为的遗传和分子基础，以及它们在适应中的功能意义，人们还知之甚少。我们提出了一种自下而上的方法：从果蝇明确的行为开始，利用果蝇丰富的遗传工具和基因组资源，这些行为对于果蝇的觅食决策是必不可少的。此外，苍蝇是生存能力研究的理想对象，可以研究不同环境条件下的遗传变异、决策差异和适应性差异之间的关系。我们已经迈出了关键的一步，并设计了新的分析方法。在这一应用中，我们将优化以下定量分析方法。在1)需要工作的小额免费奖励或大额奖励；2)小额奖励或大额奖励但可获得率相对较低；3)伴随着获得有毒食物的潜在风险的小额奖励或大额奖励；以及4)即时小额奖励或延迟大额奖励之间的选择。我们将利用生活在非洲的不同黑腹果蝇种群之间在遗传和行为方面的自然差异。我们将为每个决策行为建立200个来自非洲原始菌株的极端行为表型的重组近交系。我们将进行QTL定位，并找出影响食物选择、决策和适合度差异的QTL。然后，我们将使用RNAi转基因株系来识别导致上述行为变异的特定基因和变体。虽然我们的研究最有可能直接与临床相关的是肥胖，但它将对神经经济学、一般行为的遗传基础、进化论和生态学产生更广泛的影响。

DESCRIPTION (provided by applicant): Although energy homeostasis is central in feeding behavior, the decision to eat is not merely a question of hunger. In a natural environment in which food is often scarce, evaluating the benefit of gaining food over the energy cost or risk in seeking and acquiring food, and the decision to either seek food or stay put and conserve energy is essential for survival. However, the genetic and molecular basis of food-seeking decision-making behaviors, and their functional significance in fitness are poorly understood. We propose a bottom-up approach: starting from well-defined behaviors that are essential for food-seeking decision-making in Drosophila, taking advantage of its rich genetic tools and genomic resources. Moreover, flies are ideal for viability studies to examine the relations between genetic variations, differences in decision- making and differences in fitness under different environmental conditions. We have already taken the critical step and designed novel assays. We will optimize the following assays for quantitative analysis in this application. Decision-making in choosing between 1) small free reward or large reward that requires work; 2) small reward or large reward with a relatively low probability in its availability; 3) small reward or large reward that is paired with potential risks of getting noxious food; and 4) immediate small reward or delayed large reward. We will take advantage of natural variation in genetics and behaviors between different D. melanogaster populations living in African. We will establish 200 recombinant inbred strains derived from original African strains with extreme behavioral phenotypes for each decision-making behavior. We will perform QTL mapping and identify QTLs that contribute to the variations in food-seeking decision-making and fitness. We will then use RNAi transgenic lines to identify specific genes and variants responsible for the above behavioral variations. Although the most likely immediate clinical relevance of our study is obesity, it will have a much broader impact on neuroeconomics, the genetic basis of behavior in general, evolution and ecology.