Location: Honey Bee Breeding, Genetics, and Physiology Research
Title: BeeID: A molecular tool that identifies honey bee subspecies from different geographic populationsAuthor
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DONTHU, RAVIKIRAN - Puerto Rico Science, Technology And Research Trust |
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MARCELINO, JOSE - University Of Florida |
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GIORDANO, ROSANNA - Puerto Rico Science, Technology And Research Trust |
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TAO, YUDONG - University Of Miami |
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WEBER, EVERETT - Dartmouth College |
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Avalos, Arian |
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BAND, MARK - University Of Illinois |
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AKRAIKO, TATSIANA - University Of Illinois |
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SHU-CHING, CHEN - University Of Missouri |
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REYES, MARIA - Florida International University |
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HAO, HAIPING - Johns Hopkins University School Of Medicine |
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ORTIZ-ALVARADO, YARIRA - University Of Puerto Rico |
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CUFF, CHARLES - University Of Puerto Rico |
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PÉREZ CLAUDIO, EDDIE - University Of Pittsburgh |
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SMITH-PARDO, ALLAN - Animal And Plant Health Inspection Service (APHIS) |
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Meikle, William |
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Evans, Jay |
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GIRAY, TUGRUL - University Of Puerto Rico |
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ABDELKADER, FATEN - University Of Carthage, Tunisia |
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ALLSOPP, MIKE - Agricultural Research Council Of South Africa |
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BALL, DANIEL - Forest Fruits Ltd |
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MORGADO, SUSANA - Meltagus, Tagus International Natural Park Beekeeping Association |
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BARJADZE, BARJADZE - Ilia State University |
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CORREA-BENITEZ, ADRIANA - The National Autonomous University Of Mexico |
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CHAKIR, AMINA - Universite Cadi Ayyad |
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BÁEZ, DAVID - Farmer |
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CHAVEZ, NABOR H - Cochabamba Beekeepers Federation |
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DALMON, ANNE - Inrae |
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DOUGLAS, ADRIAN - University Of Malta |
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FRACCICA, CARMEN - Florida Department Of Agriculture And Consumer Services |
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FERNÁNDEZ-MARÍN, HERMÓGENES - Institute Of Scientific Research And High Technology Services Of Panama |
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GALINDO-CARDONA, ALBERTO - National Scientific And Technical Research Council (CONICET) |
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GUZMAN-NOVOA, ERNESTO - University Of Guelph |
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HORSBURGH, ROBERT - Florida Department Of Agriculture And Consumer Services |
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KENCE, MERAL - Middle East Technical University |
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KILONZO, JOSEPH - International Centre Of Insect Physiology And Ecology |
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KÜKRER, MERT - Middle East Technical University |
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LE CONTE, YVES - Inrae |
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MAZZEO, GAETANA - University Of Catania |
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MOTA, FERNANDO - Farmer |
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MULI, ELLIUD - International Centre Of Insect Physiology And Ecology |
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OSKAY, DEVRIM - Namik Kemal University |
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RUIZ-MARTÍNEZ, JOSÉ - University Of Cordoba |
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OLIVERI, EUGENIA - Consultant |
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PICHKHAIA, IGOR - Chkhorotsku Local Historical Museum |
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ROMANE, ABDERRAHMANE - Universite Cadi Ayyad |
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SANCHEZ, CESAR - National Banana Corporation (CORBANA) |
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SIKOMBWA, EVANS - Forest Fruits Ltd |
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SATTA, ALBERTO - University Of Sassari |
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SCANNAPIECO, ALEJANDRA - National Scientific And Technical Research Council (CONICET) |
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STANFORD, BRANDI - Florida Department Of Agriculture And Consumer Services |
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SOROKER, VICTORIA - Agricultural Research Organization Of Israel |
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VELARDE, RODRIGO - Bolivian Apiculture Institute (IAB) |
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VERCELLI, MONICA - Consultant |
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HUANG, ZACHARY - Michigan State University |
Submitted to: Science Advances
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 8/1/2024 Publication Date: 8/27/2024 Citation: Donthu, R., Marcelino, J., Giordano, R., Tao, Y., Weber, E., Avalos, A., Band, M., Akraiko, T., Shu-Ching, C., Reyes, M.P., Hao, H., Ortiz-Alvarado, Y., Cuff, C.A., Pérez Claudio, E., Smith-Pardo, A.H., Meikle, W.G., Evans, J.D., Giray, T., Abdelkader, F.B., Allsopp, M., Ball, D., Morgado, S.B., Barjadze, B., Correa-Benitez, A., Chakir, A., Báez, D.R., Chavez, N.M., Dalmon, A., Douglas, A.B., Fraccica, C., Fernández-Marín, H., Galindo-Cardona, A., Guzman-Novoa, E., Horsburgh, R., Kence, M., Kilonzo, J., Kükrer, M., Le Conte, Y., Mazzeo, G., Mota, F., Muli, E., Oskay, D., Ruiz-Martínez, J.A., Oliveri, E., Pichkhaia, I., Romane, A., Sanchez, C.G., Sikombwa, E., Satta, A., Scannapieco, A.A., Stanford, B., Soroker, V., Velarde, R.A., Vercelli, M., Huang, Z. 2024. BeeID: A molecular tool that identifies honey bee subspecies from different geographic populations. Science Advances. https://doi.org/10.1186/s12859-024-05776-9. DOI: https://doi.org/10.1186/s12859-024-05776-9 Interpretive Summary: Identification tools are greatly needed for identifying honey bee population membership. Such tools are used in a variety of applications, from tracking pests, to monitoring existing populations. This manuscript introduces BeeID, a population identification platform that uses microfluidic chemistry and machine learning approaches in accurately discriminate among honey bee populations. This approach has a high degree of certainty in established populations even with a partial genetic profile. Prediction capacity is reduced though still reliable in admixed populations but retains a high degree of flexibility such that future data can be readily incorporated to improve results. This tool could be helpful in conservation, monitoring and regulatory capacity, towards the aim of maintaining healthy bee populations. Technical Abstract: Pollinators and other arthropods are experiencing a decline due to anthropogenic induced factors. Global trade is a potential source for the introduction of undesirable bee strains, their pathogens, and parasites. Tools are needed to determine the origin of invasive bees. Genomic data for economically and ecologically important organisms, including pollinators, is increasing, but its application for solving problems is limited. We introduce BeeID to identify honey bees. The tool utilizes a knowledge-based network and diagnostic SNPs identified by discriminant analysis of principle components and hierarchical agglomerative clustering. Test results of BeeID showed that it identifies African, Americas-Africanized, Asian, and European honey bees with a high degree of certainty even when samples lack the full 272 SNPs of BeeID. Its prediction capacity decreases with highly admixed samples. BeeID is a valuable tool to screen invasive honey bees. Its flexible design allows for future improvement via sample data additions from other localities. |