Function-valued Traits in Natural Populations: Variation, Selection, and Evolution

华盛顿州立大学在理查德·戈穆尔凯维奇和帕特里克·卡特的指导下获得了一个奖项，以开发分析复杂性状的方法。参与该项目的其他人员有：Jay贝德尔（威斯康星州大学密尔沃基分校）、乔治Gilchrist（威廉和玛丽学院）、Nancy Heckman（不列颠哥伦比亚省大学）、Joel Kingsolver和Steve Marron（北卡罗来纳州大学）、Mark柯克帕特里克（德克萨斯大学）、Scott Pletcher（贝勒医学院）、Johanna施密特（布朗大学）。 生物学家有丰富的定量工具来分析性状的遗传和进化，只要性状可以通过一个或几个测量来描述。然而，在基础和应用生物学中具有核心重要性的许多复杂性状都是通过数学函数定量定义的，并且很少有方法可以用于分析。这些具有功能价值的性状包括基因表达谱、生活史模式、二维和三维形态形状以及对连续环境梯度的表型反应。经验主义者对函数值特征越来越感兴趣，但他们的研究产生了一系列尚未解决的实践和理论问题。为了解决这些问题，该奖项将整合多个学科的方法，包括统计学，数学建模和生物学。具体来说，这项工作将导致一个全面的框架，统计工具和数学模型分析功能价值的特质。该框架将被用来解决七个模型的经验系统，跨越了广泛的自然，现场和实验室系统的主要问题。这些调查将为新的和现有的数据，统计方法和数学理论产生一套广泛的经验结果。一个易于使用的软件包也将开发生物学家的研究涉及的问题，变化，选择和进化的功能值traits.Expected更广泛的影响：在这个建议中开发的方法可以应用到任何领域的生物学与复杂性状的变化有关。除了进化生物学，这包括应用领域，如医学遗传学，农业，野生动物管理，全球变化和保护遗传学。该项目的范围将包括植物和动物系统的分子，定量和生态遗传学，统计分析和数学建模。因此，拟议的跨学科研究和培训战略将提供一个出色的机会，培养本科生，研究生，博士后和建立研究人员谁跨越广泛的科学领域和方法，几乎所有的当代进化生物学的技能。

An award has been made to Washington State University under the direction of Richard Gomulkiewicz and Patrick Carter to develop ways to analyze complex traits. Other personnel involved in the project are: Jay Beder (University of Wisconsin, Milwaukee), George Gilchrist (College of William and Mary),Nancy Heckman (University of British Columbia),Joel Kingsolver and Steve Marron(University of North Carolina),Mark Kirkpatrick (University of Texas), Scott Pletcher (Baylor College of Medicine),Johanna Schmitt (Brown University). Biologists have a rich array of quantitative tools for analyzing the genetics and evolution of traits, provided the traits can be described by one or a few measurements. However, many complex traits of central importance in basic and applied biology are defined quantitatively by mathematical functions, and few methods exist for their analysis. These function-valued traits include gene expression profiles, life history patterns, two- and three-dimensional morphological shapes, and phenotypic responses to continuous environmental gradients. Empiricists are becoming increasingly interested in function-valued traits, but their studies have generated an expanding range of unresolved practical and theoretical questions. To address these issues, this award will integrate approaches from several disciplines, including statistics, mathematical modeling, and biology. Specifically, the work will lead to a comprehensive framework of statistical tools and mathematical models for analyzing function-valued traits. The framework will be used to address major questions in seven model empirical systems that span a broad spectrum of natural, field, and laboratory systems. These investigations will produce an extensive set of empirical results for new and existing data, statistical methods, and mathematical theory. An easy to use software package will also be developed for biologists whose research involves questions about variation, selection, and evolution of function-valued traits.Expected broader impacts: Methodologies developed in this proposal can be applied to any area of biology concerned with variation of complex traits. Besides evolutionary biology, this includes applied fields such as medical genetics, agriculture, wildlife management, global change, and conservation genetics. The scope of this project would include molecular, quantitative, and ecological genetics in plant and animal systems, statistical analysis, and mathematical modeling. As such, the proposed crosscutting research and training strategy will provide an outstanding opportunity to train undergraduates, graduate students, post-docs, and established researchers who span a wide range of scientific fields and approaches in virtually all the skills of contemporary evolutionary biology.