DISSERTATION RESEARCH: Evolutionary genetics of physiological variation in Ipomopsis aggregata: identifying QTL and measuring ecological selection in different environments

植物在光合作用中利用水分的效率是一项关键的生理特性，它决定了植物在哪里生存，以及它们生长和繁殖的好坏。本研究将遗传学和生态学的方法结合起来，以了解美洲原产的野生植物——绿多毛（Ipomopsis aggregata）的水分利用和相关生理性状的进化。本项目将研究1)控制水分利用及相关生理性状的基因数量；2)不同水源环境下的自然选择模式；3)环境如何在影响水资源利用的性状上形成种群间的差异。来自大型田间实验的基因型和生理性状数据将用于性状的遗传作图和选择测量。为了评估种群的遗传变异，将收集分布在整个分布范围内的天然种群的基因型和气候数据。该项目将阐明植物重要生理性状的遗传基础，并揭示这些性状的差异如何进化。这项工作还将为植物在不同气候和环境下所经历的压力提供数据。因此，研究结果将有助于预测气候变化对植物的影响。此外，该项目将为包括少数民族在内的本科生提供研究机会，并促进不同生物学领域的机构和研究人员之间的合作。

The efficiency with which plants use water during photosynthesis is a critical physiological trait that determines where plants can survive and how well they grow and reproduce. This research integrates genetic and ecological approaches to understand the evolution of water use and related physiological traits in Ipomopsis aggregata, a wildflower native to the United States. This project will investigate 1) the number of genes that control water use and related physiological traits; 2) patterns of natural selection in environments that differ in water availability; and 3) how the environment has shaped differences among populations in traits that affect water use. Genotype and physiological trait data from large field experiments will be used for genetic mapping of traits and measurements of selection. To assess population genetic variation, genotype and climatic data will be collected from natural populations across the range of I. aggregata. This project will elucidate the genetic basis of important physiological traits in plants, and show how differences in these traits may evolve. This work will also provide data on the stresses plants experience in different climates and environments. Therefore, results will be useful for predicting the effects of climate change on plants. Additionally, this project will provide research opportunities for undergraduates including minorities, and stimulate collaborations among institutions and researchers in different fields of biology.