Introduction
The integration of plant–disease association data with phylogenetic comparative methods provides a powerful framework for identifying candidate plant species associated with specific therapeutic indications. The Hot Ancestry Score (HAS), implemented in the pm4mp R package, prioritizes candidate species by combining phylogenetic relationships with plant–disease association data. However, HAS relies on a fixed reference phylogeny for scoring and assumes that all inferred ancestral relationships are equally reliable, regardless of differences in node support among clades. As a consequence, signals derived from weakly supported nodes may influence species prioritization as strongly as those supported by robust phylogenetic evidence.
Methods
We introduce the weighted Hot Ancestry Score (wHAS), a support-weighted extension of HAS that incorporates phylogenetic node support into species prioritization. Rather than modifying the ancestral scoring scheme, wHAS weights the contribution of each hot ancestor to the final species score according to the statistical support of its corresponding clade. Node support is derived from bootstrap proportions. This preserves the simplicity of HAS while down-weighting signals associated with poorly supported evolutionary relationships.
Results
Following the analytical framework of the original study, we evaluate wHAS on the Superasterids using selected disease categories previously analysed in pm4mp. Comparisons between HAS and wHAS show differences in species prioritization, particularly in clades characterized by lower statistical support, where weighting has a greater influence on final species scores.
Conclusions
By incorporating phylogenetic node support into HAS, wHAS provides a simple, statistically informed, and biologically interpretable extension for phylogeny-guided medicinal plant bioprospecting while remaining fully compatible with user-defined reference phylogenies. The framework is extendable to alternative measures of phylogenetic support, including Bayesian posterior probabilities.