QTL MAPPING IN THREESPINE STICKLEBACK

近年来，发育生物学和进化生物学的综合已成为研究的一个主要焦点。然而，在短期的进化过程中，调控基因座的等位基因频率变化的作用知之甚少。在这个项目中，我将利用一个特殊的机会，调查这些问题所提供的快速和广泛的形态进化种群之间的threespine刺鱼。当这种多骨鱼入侵淡水栖息地时，它经常进化出不同的身体，头部和颌骨形状，以利用不同的资源，同时失去多骨板和刺。我将构建一个遗传图谱或刺鱼和确定数量性状基因座（QTL）之间的祖先海洋和衍生的淡水形式的交叉。比较基因组学与研究充分的斑马鱼将允许我定义的分子基础的发展途径，导致不同的形态。然后进行原位表达分析，以将成体表型的变化与胚胎发生期间表达模式的变化联系起来。对斑马鱼和棘鱼的综合研究将大大增加我们对发育微进化的理解。更充分地了解发展的微观演变，将为人类健康带来重大收益。使用发育进化模型可以更好地理解某些人群中遗传疾病的发病率较高，并且可以使用从这些模型中获得的见解设计群体特异性治疗。此外，传染病发展演变的更多预测模型将允许靶向治疗，这将降低耐药病原体流行的可能性。

The synthesis of developmental and evolutionary biology has become a major focus of research over the pas several years. However, the role of allele frequency changes at regulatory loci during short-term evolution is poorly understood. In this project I will exploit a special opportunity to investigate these issues afforded by the rapid and extensive morphological evolution among populations of threespine stickleback. When this boney fish has invaded freshwater habitats it has often evolved divergent body, head and jaw shapes in order to exploit different resources, and concurrently lost boney plates and spines. I will construct a genetic map or stickleback and identify quantitative trait loci (QTLs) by using a cross between ancestral marine and derived freshwater forms. Comparative genomics with the well studied zebrafish will allow me to define the molecular basis of the development-pathways leading to divergent morphologies. In situ expression analyses will then be performed to link changes in adult phenotype to changes in expression patterns during embryogenesis. The synthesis of zebrafish and stickleback research will greatly increase our understanding of the microevolution of development. A fuller understanding of the microevolution of development promises significant gains for human health. Higher rates of genetic disorders in some human populations can be better understood using models of the evolution of development, and population specific treatments can be devised using insight gained from these models. Additionally, more predictive models of the developmental evolution of infectious diseases will allow targeted treatments that will decrease the probability of epidemics of drug resistant pathogens.