Phenotypic, Genotypic, and Ecological Determinants of Reproductive Success in Natural Populations

任何种群的遗传历史和当前结构都可以用它的谱系来表示。在研究自然种群的交配行为和遗传传播、管理不同基因型的圈养动物的繁殖性能、检查亲代印记对觅食行为的影响方面，系谱分析已成为越来越重要的组成部分。或者测量亲属之间的相互作用对个体的包容性适合度的影响。迄今为止，大多数此类研究都是通过叶绿体和线粒体基因组进行母系遗传的，这种方法忽略了整个谱系的重要组成部分父系遗传。研究人员开发了另一种方法，利用核标记对母系和父系血统进行统计推断。他们的策略是使用足够多的遗传标记来排除所有的后代，只考虑一个。然而，先前的研究表明，需要大量的多态标记来确定每个后代的父亲身份。在许多有趣的应用中，对亲子鉴定问题的严格排除性解决方案是无法实现的。目的是发展统计/遗传估计程序，然后用它们来分析男性对黄斑chamaelium luteum和Silene alba的生殖贡献。比父母谱系更有趣的是表型、基因型和生态决定因素的生殖贡献。研究人员将开发统计方法来阐明这些因素。

The genetic history and current structure of any population can be represented in terms of its genealogy. Genealogical analysis has become an increasingly important component of studies of mating behavior and genetic dispersal in natural populations and in the management of captive animal reproductive performance of different genotypes, in examining the impact of parental imprinting on foraging behavior, or in measuring the effects of interactions among relatives on the inclusive fitness of individuals. Most such efforts to date have maternal descent through chloroplast and mitochondria genomes, an approach that ignores paternal descent, a substantial part of the overall pedigree. The investigators have developed an alternative approach that uses nuclear markers to make statistical inferences about both maternal and paternal lineages. Their strategy is to employ enough genetic markers to exclude all but one make from consideration for each offspring. Previous work has shown, however, that a very large number of polymorphic markers is required to assign paternity categorically for each and every offspring. A strictly exclusionary solution to the problem of parentage assessment is not attainable in many interesting applications. The objective is to develop statistical/genetic estimation procedures and then to use them to analyze male reproductive contributions for Chamaelirium luteum and Silene alba. More interesting than the parentage spectrum are the phenotypic, genotypic, and ecological determinants of reproductive contributions. The investigators will develop statistical methods to elucidate such factors.