DISSERTATION RESEARCH: Elucidating the genomic signature of mate competition in a pipefish using a population genomics approach

这项研究旨在了解成人的行为如何决定哪些基因从父母传递给后代，以及这些过程在一个物种的种群中是如何变化的。这些目标将通过比较单个管鱼种群中成人及其后代的自然遗传变异来解决。这项研究还将在广泛的地理范围内量化多个种群的遗传变异，这将提供有关种群间生殖模式变化的数据。焦点生物是在瑞典发现的直鼻管鱼，Nerophis ophidion，该项目利用最近的DNA测序技术来分析整个基因组的遗传变异。这个物种令人感兴趣，因为雌性为获得配偶而激烈竞争，雄性为发育中的后代提供所有照顾。该项目涉及生物学和遗传学的一个主要课题，即生命周期中不同阶段的行为如何影响基因如何从一代传递到下一代。此外，使用新的测序技术比较成人和后代之间的遗传变异的分析方法是20世纪70年代的数学模型和新的统计方法的新颖结合。这种方法可广泛应用于许多领域和许多物种，包括作为一种诊断工具，了解哪些压力正在影响受威胁和濒危物种，以及了解人类疾病的多代影响。

This study aims to understand how adult behavior can determine which genes are passed from parents to offspring and how these processes vary among populations within a species. These goals will be addressed by comparing the natural genetic variation in adults and their offspring within a single population of pipefish. This study will also quantify genetic variation in multiple populations across a broad geographic range, which will provide data regarding how reproductive patterns vary among populations. The focal organism is the straight-nosed pipefish, Nerophis ophidion, which is found in Sweden, and the project takes advantage of recent advances in DNA sequencing technology to analyze the genetic variation at the scale of the entire genome. This species is of interest because females compete intensely for access to mates and the males provide all care for the developing offspring. This project addresses a major subject in biology and genetics, namely how behaviors at different stages during the life cycle affect how genes are passed on from one generation to the next. Additionally, the analytical approach of comparing genetic variation between adults and offspring using new sequencing technologies is a novel combination of a mathematical model from the 1970's and new statistical methods. This approach could have broad applications in many fields and for many species, including as a diagnostic tool for understanding what pressures are affecting threatened and endangered species and for understanding multi-generational effects of human diseases.