如何从基因组水平检测自然选择、中性过程和种群历史等力量对于生物微进化的影响是进化生物学所面临的挑战之一。广布于欧亚大陆的雉鸡（Phasianus colchicus）的不同地理种群具有明显的表型和遗传分化，形成对不同地理气候条件的适应，是研究物种分化和适应等微进化机制的理想物种。本项目拟采用基于高通量测序的简化基因组技术RAD-seq，结合生物信息学、种群遗传学方法对雉鸡的种群基因组学进行研究，系统性地探讨雉鸡分化过程中各种进化力量的模式与规律；特别是在基因组水平寻找与雉鸡表型变异及适应不同地理气候条件相关的候选基因，并在雉鸡世界分布区内的更大群体中验证这些基因的分布频率，旨在揭示广布生物遗传分化模式和适应机制。相关研究成果促进了对非模式生物微进化机制的深入理解，为建立与完善野生鸟类大规模种群基因组学和适应性进化研究提供可扩展性的解决方案，对保护和利用雉鸡种质资源具有重要价值。

Varied evolutionary forces, such as natural selection, neutral processes like genetic drift, as well as population demography can leave traces in the genome of an organism. To determine the relative importance of these forces on the non-model organisms at the molecular level is one of the challenges in current evolutionary biology. The Common Pheasant (Phasianus colchicus) is a widespread and abundant gamebird species in Eurasia. Different geographical populations diverged substantially in morphology, genetic and exhibit adaptation to contrasting climatic and conditions, e.g. lowland to plateau, northern temperate to tropic, monsoon to inland desert. Thus the common pheasant is an ideal species to investigate microevolution patterns and processes leading to intraspecific divergence and local adaptation. In the present project, we will use a novel Genotyping-by-Sequencing laboratory and analytical method, i.e. RAD-seq based on Next-Generation Sequencing technique to generate genome-wide single nucleotide polymorphisms for multiple representative geographical populations across China. Based on genomic sequence data, state-of-the-art bioinformatic and population genetic methods will be applied to investigate genomic patterns of population demography and local adaptation in unprecedented detail in the Common Pheasants. Moreover, we will identify candidate genes that might be associated with the morphological variations and climatic adaptation. Further some of selected candidate genes will be genotyped using Sanger sequencing for a larger data set covering in order to estimate their frequencies and geographic patterns. This work will contribute significantly to our understanding of the mechanisms of population divergence and the maintenance of genetic variability, and will therefore furnish novel insights into microevolution in non-model organisms. Findings of this project will provide genetic resources for common pheasants. Given the novel sequencing technology and comprehensive analytical framework applied herein, this project would also represent a repeatable research scheme that can be applied in population genomics studies in other wild species.