A comprehensive framework for the delimitation of species within the Bemisia tabaci cryptic complex, a global pest-species group
2025
Wang, Hua-Ling | Lei, Teng | Wang, Xiaowei | Cameron, Stephen L. | Navas-Castillo, Jesús | Liu, Yin-Quan | Maruthi, M.N. | Omongo, Christopher A. | Delatte, Hélène | Lee, Kyeong-Yeoll | Krause-Sakate, Renate | Ng, James | Seal, Susan | Fiallo-Olivé, Elvira | Bushley, Kathryn | Colvin, John | Liu, Shu-Sheng
Identifying cryptic species poses a substantial challenge to both biologists and naturalists due to morphological similarities. Bemisia tabaci is a cryptic species complex containing more than 44 putative species; several of which are currently among the world's most destructive crop pests. Interpreting and delimiting the evolution of this species complex has proved problematic. To develop a comprehensive framework for species delimitation and identification, we evaluated the performance of distinct data sources both individually and in combination among numerous samples of the B. tabaci species complex acquired worldwide. Distinct datasets include full mitogenomes, single-copy nuclear genes, restriction site-associated DNA sequencing, geographic range, host speciation, and reproductive compatibility datasets. Phylogenetically, our well-supported topologies generated from three dense molecular markers highlighted the evolutionary divergence of species of the B. tabaci complex and suggested that the nuclear markers serve as a more accurate representation of B. tabaci species diversity. Reproductive compatibility datasets facilitated the identification of at least 17 different cryptic species within our samples. Native geographic range information provides a complementary assessment of species recognition, while the host range datasets provide low rate of delimiting resolution. We further summarized different data performances in species classification when compared with reproductive compatibility, indicating that combination of mtCOI divergence, nuclear markers, geographic range provide a complementary assessment of species recognition. Finally, we represent a model for understanding and untangling the cryptic species complexes based on the evidence from this study and previously published articles.
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