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Figure 1. 

Relationships between leaf traits. Scatter plots and histograms display the distribution of each trait. The red line overlaid on each histogram represents the density distribution. '*', '**' and '***' denote significant correlations at the 0.05, 0.01, and 0.001 levels, respectively. Red and blue asterisks represent positive and negative correlations, respectively.

Figure 2. 

Principal component analysis (PCA) and hierarchical clustering analysis based on leaf phenotype data. (a) The PCA plot showing the first and second principal components of P. cathayana genotypes, represented by color-coded points, and the relative importance of explanatory variables is indicated by vectors. (b) Clustering of P. cathayana populations into four categories based on leaf traits. (c) Comparison of four leaf shape categories^[28].

Figure 3. 

Selective sweep analysis visual line chart and frequency histogram. Genetic differentiation coefficient (Fst) and nucleotide diversity (π) were calculated by the sliding window method with a window size of 10 kb and a step size of 1 kb; XP-CLR has the same window size as Fst and π. The plots (a), (b) and (c) respectively represent the line graph and frequency histogram of Fst, π, and XP-CLR. In the line plot, the blue line and red line represent the top 5% and top 1% thresholds, respectively, and correspond to the blue and red shaded areas in the frequency histogram. The interval that passes the top 5% threshold lines in three methods is considered as the final candidate region for selective sweep.

Figure 4. 

Functional enrichment analysis of selective sweep candidate genes. (a) GO enrichment analysis of candidate genes, where the size of the points represents the number of genes, and the color of the points indicates significance level. BP, CC, MF respectively represent biological process, cellular component, and molecular function. (b) KEGG enrichment analysis of candidate genes, where the size of the points represents the number of genes, and the color of the points indicates significance level.

Figure 5. 

GEMMA multi-trait GWAS Manhattan plots and significant locus analysis. The plots (a), (b), (c), (d), and (e) correspond to the manhattan plots of LA_LP_LL_LW, LA_PL_SPAD, LI_LW_LL, LMF_LA_LP and RPL_LI_LMF, respectively. For ease of comparison, we have included the single-trait GWAS Manhattan plots of the traits in the figures. Each dot on the plot represents a SNP, with dot colors indicate single-trait or multi-trait associations. p_value were transformed into −log₁₀(p_value). SNPs above green lines passed bonferroni correction test (p ≤ 8.51 × 10⁻⁸). The red circle represents the detected loci in multiple trait combinations. (f) Analysis of genetic differentiation (Fst) and nucleotide diversity (π) near SNP 7__12437614. (g) Comparison of leaf phenotypes corresponding to three haplotypes at SNP 7__12437614, represented by mean values in a bar graph with standard deviation as the error. (h) Analysis of genetic differentiation (Fst) and nucleotide diversity (π) near SNP 18__14798104. (i) Comparison of leaf phenotypes between two haplotypes at SNP 18__14798104, represented by mean values in a bar graph with standard deviation as the error.

Figure 6. 

Candidate gene network visualization. Circles represent candidate genes, and the size of the circles indicates the number of associated traits. The color of the circles corresponds to different types of candidate genes. Lines represent the traits associated with genes and whether they are candidate genes for selective sweep.