This course comprehensively covers the core content and analytical techniques of population evolution research. Chapter 1 provides an overview of the concept of population evolution and its applications in the origins of domestication, environmental adaptation, and genetic exploration. Chapter 2 explains the key points of experimental design, including sample collection strategies, subgroup and sample size requirements, sequencing depth selection (diploid ≥ 10X, homologous polyploid ≥ 30X), and the applicable scenarios of resequencing and simplified genomics. Chapters 3 to 5 respectively introduce three core dimension reduction and clustering methods: phylogenetic trees (NJ/ML, showing population stratification and evolutionary relationships), principal component analysis (PCA, eliminating outlier samples, and intuitively presenting genetic structure), and population structure analysis (STRUCTURE/ADMIXTURE, inferring individual genetic admixture and the optimal number of clusters). Chapters 6 to 9 delve into the calculation and selection of population genetic parameters and signals detection: nucleotide diversity (Pi, measuring the level of variation within the population), fixation index (Fst, quantifying the degree of differentiation between populations), selective sweep analysis (detecting positive selection signals, combined with Pi reduction and Fst increase), and linkage disequilibrium decay (LDdecay, comparing recombination rates and domestication intensity between different populations). The course emphasizes parameter interpretation and biological significance, providing systematic guidance for population history inference, domestication gene exploration, and adaptive evolution research.