Modeling evolution of quantitative traits with finite locus effects in structured populations

结构化群体中具有有限位点效应的数量性状演化建模

• 批准号: 0201173
• 负责人: Judith Miller
• 金额: --
• 依托单位: Georgetown University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-06-01 至 2008-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0201173&HistoricalAwards=false
• 关键词: Modeling; evolution; quantitative; traits; finite

Recent advances in quantitative genetics show that there is a distribution of locus effects on quantitative traits, with some loci (henceforth called QTLs) explaining a large proportion of the genotypic trait variance and others having minor but detectable effects on phenotype. For QTL results to be incorporated into existing theory, a crucial task is to develop models of quantitative trait variation that allow for a finite number of loci with finite effects. In this project, such models are developed and analyzed. Our theoretical work focuses on diffusion models, i.e. models in which both time and allele frequencies are continuous. The models developed are compared with previously-derived models, with the results of simulations, and with experimental data, with the aim of identifying models useful for predicting quantitative trait evolution in natural and agricultural populations. The results of the analysis and simulations are used to create statistical tests for the action of selection on quantitative traits in populations. Quantitative traits are among the most conspicuous features of organisms, features that we immediately recognize. Examples abound, including the height of humans, the number of ears on a corn plant or the weight of piglets in a litter. The study of quantitative traits and their genetic basis is fundamental to our understanding of evolutionary biology as well as to applied genetics such as animal and plant breeding. Using recently developed technology, it is now possible to identify regions of the genome that contribute to quantitative traits. Such "QTL mapping" studies have revealed discrepancies between the data and classical theories intended to explain the contribution of individual genes to such traits. This project aims to extend our theoretical understanding of quantitative traits, and to use the theory developed to create practical statistical methods for analyzing quantitative trait data. This grant is made under the Joint DMS/NIGMS Initiative to Support Research Grants in the Area of Mathematical Biology. This is a joint competition sponsored by the Division of Mathematical Sciences (DMS) at the National Science Foundation and the National Institute of General Medical Sciences (NIGMS) at the National Institutes of Health.

数量遗传学的最新进展表明，数量性状的基因座效应存在一定的分布，一些基因座（以下称为QTL）解释了大部分的基因型性状变异，而另一些基因座对表型的影响较小，但可检测到。对于QTL结果被纳入现有的理论，一个至关重要的任务是开发模型的数量性状变异，允许有限数量的基因座有限的影响。在这个项目中，这样的模型开发和分析。我们的理论工作主要集中在扩散模型，即时间和等位基因频率都是连续的模型。开发的模型进行比较，与以前派生的模型，模拟的结果，并与实验数据，其目的是确定用于预测自然和农业人口的数量性状进化的模型。分析和模拟的结果被用来创建数量性状的选择在人群中的作用的统计测试。 数量性状是生物体最显著的特征之一，我们可以立即识别这些特征。例如，人类的身高，玉米植株上的穗数或一窝小猪的重量。数量性状及其遗传基础的研究是我们理解进化生物学以及应用遗传学（如动物和植物育种）的基础。利用最近开发的技术，现在可以确定基因组中对数量性状有贡献的区域。这样的“QTL作图”研究揭示了数据和经典理论之间的差异，这些理论旨在解释单个基因对这些性状的贡献。该项目旨在扩展我们对数量性状的理论理解，并使用所开发的理论来创建用于分析数量性状数据的实用统计方法。这项赠款是根据联合DMS/NIGMS倡议，以支持研究赠款在数学生物学领域。这是一项由美国国家科学基金会数学科学部（DMS）和美国国立卫生研究院国家普通医学科学研究所（NIGMS）赞助的联合竞赛。