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A comprehensive framework for the delimitation of species within the Bemisia tabaci cryptic complex, a global pest-species group.
Wang, Hua-Ling; Lei, Teng; Wang, Xiao-Wei; Cameron, Stephen; 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.
Afiliación
  • Wang HL; College of Forestry, Hebei Agricultural University, Baoding, Hebei Province, China.
  • Lei T; The Ministry of Agriculture Key Laboratory of Molecular Biology of Crop Pathogens and Insects, Institute of Insect Sciences, Zhejiang University, Hangzhou, China.
  • Wang XW; Natural Resources Institute, University of Greenwich, Kent, UK.
  • Cameron S; College of Life Sciences, Taizhou University, Taizhou, Zhejiang Province, China.
  • Navas-Castillo J; The Ministry of Agriculture Key Laboratory of Molecular Biology of Crop Pathogens and Insects, Institute of Insect Sciences, Zhejiang University, Hangzhou, China.
  • Liu YQ; Department of Entomology, Purdue University, West Lafayette, IN, USA.
  • Maruthi MN; Instituto de Hortofruticultura Subtropical y Mediterránea "La Mayora" (IHSM-UMA-CSIC), Consejo Superior de Investigaciones Científicas, Malaga, Spain.
  • Omongo CA; The Ministry of Agriculture Key Laboratory of Molecular Biology of Crop Pathogens and Insects, Institute of Insect Sciences, Zhejiang University, Hangzhou, China.
  • Delatte H; Natural Resources Institute, University of Greenwich, Kent, UK.
  • Lee KY; National Crops Resources Research Institute, Kampala, Uganda.
  • Krause-Sakate R; CIRAD, UMR PVBMT CIRAD, Pôle de Protection des Plantes, Saint-Pierre, France.
  • Ng J; School of Applied Biosciences, Kyungpook National University, Daegu, Republic of Korea.
  • Seal S; UNESP, Faculdade de Ciências Agronômicas, Botucatu, Brazil.
  • Fiallo-Olivé E; Department of Microbiology and Plant Pathology, University of California, Riverside, CA.
  • Bushley K; Natural Resources Institute, University of Greenwich, Kent, UK.
  • Colvin J; Instituto de Hortofruticultura Subtropical y Mediterránea "La Mayora" (IHSM-UMA-CSIC), Consejo Superior de Investigaciones Científicas, Malaga, Spain.
  • Liu SS; USDA Agricultural Research Service, 17123, Emerging Pests and Pathogens Research Unit, Ithaca, NY, USA.
Insect Sci ; 2024 Apr 01.
Article en En | MEDLINE | ID: mdl-38562016
ABSTRACT
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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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Insect Sci Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Australia

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Insect Sci Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Australia