A Phylogenetically Informed Comparative Analysis of the SWEET Sugar Transporter Family Across Angiosperms

Background/Objectives: The SWEET (Sugars Will Eventually be Exported Transporters) family mediates sugar efflux and underpins phloem loading, seed filling, stress adaptation, and plant–pathogen interactions. Genome-wide surveys have accumulated rapidly but remain fragmented and rarely phylogenetically informed. This study separates conserved evolutionary trends from sampling-driven artifacts. Methods: Four SWEET families were identified in original analyses and combined with genome-wide records from the literature. The 104 records were consolidated to one record per species, yielding 85 species from 39 families (59 non-monocots, 26 monocots). Gene count, physicochemical properties, and subcellular localization were analyzed using Mann–Whitney U and Kruskal–Wallis tests, Spearman correlations, and principal component analysis, complemented by phylogenetic generalized least squares (PGLS) and multi-layered sensitivity analyses. Results: Non-monocots showed nominally higher SWEET gene counts than monocots (27.25 vs. 20.15; p = 0.021), but this difference did not persist under PGLS (p = 0.373; λ = 0.467). Family-level variation was non-significant after consolidation (p = 0.101). Physicochemical properties (midranges of isoelectric point (pI), molecular weight (MW), amino acid length, and transmembrane helix count) showed no detectable broad group-level differentiation between monocots and non-monocot angiosperms (pI midrange 7.92 ± 0.52; MW midrange 30.60 ± 8.57 kDa) and carried a weak phylogenetic signal. All 55 species with localization data showed at least one plasma-membrane prediction, and localization classes did not differ between the two groups (p = 0.328). Three gene-count correlations with minimum-range physicochemical variables were identified as likely order-statistics artifacts. Conclusions: Apparent clade differences in SWEET gene number largely reflect phylogenetic non-independence. This sensitivity-tested analysis provides a methodological framework for plant gene-family comparative research.