## 4 Materials and Methods
### Phylogenetic Analysis and Divergence Time Estimation  
For phylogenetic analysis, we utilized 10 _Phylot alca_ cp genomes, with _A. clematidea_ as the outgroup. The cp genomes were aligned using MAFFT v7 [96], which ensures accurate alignments, particularly in regions with moderate divergence, and provides high-quality results for plant genome analysis. The aligned sequences were then used to extract CDSs for further analysis. The extracted CDSs were refined using Gblocks v5 [97] to remove poorly aligned and highly variable regions. To determine the most suitable nucleotide substitution model, jModelTest v2.1.10 [98] and the GTR+I+G model was selected based on the Akaike information criterion (AIC). Using this model, we constructed an ML tree using MEGA11 [86], performing 1000 bootstrap replicates to assess the robustness of the tree topology, a number typically sufficient to provide reliable support values while balancing computational efficiency. A BI tree was generated using MrBayes v3.2.6 [99], running the Markov Chain Monte Carlo (MCMC) algorithm for 5,000,000 generations, with two independent runs of two chains each. The analysis was performed on a desktop computer equipped with a 13 th Gen Intel(R) Core(TM) i5-13400F processor (2.50 GHz) (Intel, Santa Clara, CA, USA), 32 GB of RAM, and Windows 11 Education (64-bit). The total computation time was approximately 12 h. Trees were sampled every 100,000 generations, with the first 25% discarded as burn-ins. A 50% majority-rule consensus tree was used to estimate the posterior probabilities of phylogenetic relationships. To estimate the divergence times of _Phylotacca_ species, we selected 14 species, including those closely related to _P. acinosa_, based on the analysis of 76 CDSs extracted from their cp genomes. Species names and accession numbers of the cp genomes used in the divergence time analysis are summarized in Table S8. The settings for phylogenetic inference and divergence time estimation were configured using the BEAUti interface as follows. For nucleotide substitution, we applied the GTR+I model. A Yule tree prior, which assumes a constant speciation rate across the entire phylogeny, was used to model species diversification, making it suitable for species-level divergence analyses. In addition, a log-normal relaxed molecular clock model was employed to allow mutation rates to vary over time rather than assuming a constant rate of molecular evolution. Divergence times in the phylogenetic tree were calibrated using both fossil-based and molecular clock evidence, with four calibration points incorporated based on estimates from a previous study by [PERSON] et al. [1]. The divergence between _A. clematidea_ and _Phylotacca_ was set at 59.56 Ma. Divergence between _P. dioica_ and other _Phylotacca_ species was estimated to have occurred at 20.30 Ma. The divergence of the clade containing _P. acinosa_ was estimated at 13.72 Ma, whereas the split between _P. americana_ and the remaining _Phylotacca_ species was estimated at 10.95 Ma. Each calibration point was used to constrain the corresponding nodes in the divergence time tree with the 95% highest posterior density (HPD) interval applied. The MCMC analysis was conducted over 50 million generations with a 10% burn-in and sampling every 500 generations. Analysis was performed using BEAST v1.856 [100], a comprehensive software package for Bayesian evolutionary analysis, and posterior estimates, including effective sample sizes (ESS) and parameter convergence, which were assessed using Tracer v1.7 [101]. In addition, we summarized the posterior distribution of trees by estimating the average node heights, means, and 95% HPD intervals using TreeAnnotator v1.7 [101]. The resulting phylogenetic trees and divergence times were visualized using FigTree v1.4.4 [102], thus facilitating a detailed evaluation of evolutionary relationships and divergence time estimates across the sampled species.