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DNA barcodes and reliable molecular identifications in a diverse group of invasive pests: lessons from Bactrocera fruit flies on variation across the COI gene, introgression, and standardization

View ORCID ProfileCamiel Doorenweerd, Michael San Jose, Luc Leblanc, Norman Barr, Scott Geib, Arthur Y.C. Chung, Julian Dupuis, Arni Ekayanti, Elaida R. Fiegalan, K.S. Hemachandra, M. Aftab Hossain, Chia-Lung Huang, Yu-Feng Hsu, Kimberly Y. Morris, Andi Maryani Mustapeng, Jerome Niogret, Thai Hong Pham, U.G.A.I. Sirisena, Daniel Rubinoff
doi: https://doi.org/10.1101/2020.11.23.394510
Camiel Doorenweerd
1University of Hawaii, College of Tropical Agriculture and Human Resources, Department of Plant and Environmental Protection Sciences, Entomology section, 3050 Maile Way, Honolulu, Hawaii, 96822-2231, USA
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  • ORCID record for Camiel Doorenweerd
  • For correspondence: camiel.doorenweerd@hawaii.edu
Michael San Jose
1University of Hawaii, College of Tropical Agriculture and Human Resources, Department of Plant and Environmental Protection Sciences, Entomology section, 3050 Maile Way, Honolulu, Hawaii, 96822-2231, USA
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Luc Leblanc
2University of Idaho, Department of Entomology, Plant Pathology and Nematology, 875 Perimeter Drive, MS2329, Moscow, Idaho, 83844-2329, United States
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Norman Barr
3United States Department of Agriculture, Animal and Plant Health Inspection Service, Plant Protection and Quarantine, Science & Technology, Mission Laboratory, 22675 N. Moorefield Road, Edinburg, Texas 78541, USA
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Scott Geib
4Tropical Crop and Commodity Protection Research Unit, Daniel K Inouye U.S. Pacific Basin Agricultural Center, USDA Agricultural Research Services, Hilo, Hawaii, USA
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Arthur Y.C. Chung
5Forest Research Centre, Forestry Department, P.O. Box 1407, 90715 Sandakan, Sabah, Malaysia
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Julian Dupuis
6University of Kentucky, Department of Entomology, S-225 Ag Science Center North, 1100 South Limestone, Lexington, Kentucky, 40546-0091, USA
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Arni Ekayanti
7Niogret Ecology Consulting LLC, Wotu, Luwu Timor, Sulawesi Seleaton 92971, Indonesia
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Elaida R. Fiegalan
8Department of Crop Protection, College of Agriculture, Central Luzon State University, Science City of Muñoz, Nueva Ecija 3119, Philippines
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K.S. Hemachandra
9Faculty of Agriculture, University of Peradeniya, Sri Lanka
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M. Aftab Hossain
10Insect Biotechnology Division, Institute of Flood and Radiation Biology, Bangladesh, Atomic Energy Commission, Dhaka-1349, Bangladesh
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Chia-Lung Huang
11Institute of Oceanography, Minjiang University, No. 200, Xiyuangong Road, Shangije Town, Minhou County, Fuzhou City, Fujian Province, China
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Yu-Feng Hsu
12Department of Life Science, National Taiwan Normal University, No. 88, Sec. 4, Tingzhou Road, Taipei, 116, Taiwan, ROC
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Kimberly Y. Morris
4Tropical Crop and Commodity Protection Research Unit, Daniel K Inouye U.S. Pacific Basin Agricultural Center, USDA Agricultural Research Services, Hilo, Hawaii, USA
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Andi Maryani Mustapeng
5Forest Research Centre, Forestry Department, P.O. Box 1407, 90715 Sandakan, Sabah, Malaysia
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Jerome Niogret
7Niogret Ecology Consulting LLC, Wotu, Luwu Timor, Sulawesi Seleaton 92971, Indonesia
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Thai Hong Pham
13Mientrung Institute for Scientific Research, Vietnam Academy of Science and Technology, 321 Huynh Thuc Khang, Hue, Vietnam
14Vietnam National Museum of Nature & Graduate School of Science and Technology, Hanoi, Vietnam
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U.G.A.I. Sirisena
15Department of Plant Sciences, Faculty of Agriculture, Rajarata University of Sri Lanka, Sri Lanka
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Daniel Rubinoff
1University of Hawaii, College of Tropical Agriculture and Human Resources, Department of Plant and Environmental Protection Sciences, Entomology section, 3050 Maile Way, Honolulu, Hawaii, 96822-2231, USA
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Abstract

The utility of a universal DNA ‘barcode’ fragment of 658 base pairs of the Cytochrome C Oxidase I (COI) gene for the recognition of all animal species has been a widely debated topic on theoretical and practical levels. Regardless of its challenges, large amounts of COI sequence data have been produced in the last two decades. To optimally use the data towards reliable species identification will require further steps to validate the method and reference libraries. The fruit fly tribe Dacini holds about a thousand species, of which eighty are pests of economic concern, including some of the world’s foremost fruit and vegetable pests, and there are many morphologically cryptic species complexes in the tribe. Where previous studies showed limited success in using COI to identify Dacini, our results with a highly curated morphological dataset indicate high congruence between morphology and COI: 90% of the species in our 5,576 sequences, 262-species global dataset can be identified with COI alone based on a monophyly criterion. However, in some key pest species belonging to complexes that were previously thought diagnosable with COI, we found that expanded sampling and independent validation of identifications using genomic data revealed introgression of mitochondrial DNA. We find that the informative SNPs are uniformly distributed across the COI gene, and we provide recommendations for standardization. We conclude that reliable molecular identifications with COI require extensive species coverage, population sampling, and genomics-supported reference identifications before they can be validated as a “diagnostic” marker for specific groups.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Data availability statement, All data underlying this study is made publicly available. Sample information, including collecting localities, identifier information and DNA sequences are available in BOLD dataset DOI:xxx.xxx, and the sequences are also available through NCBI Genbank accessions xxx–xxx. Dryad depository DOI:xxx.xxx contains the FASTA formatted alignment with COI sequences, the IQ-Tree generated maximum likelihood tree, the complete monophylizer output table and a spreadsheet with the latest global checklist for Dacini. Github project DOI: http://doi.org/10.5281/zenodo.3834896 ‘PyCOIstats’ contains the scripts used for analyzing the COI sequences.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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DNA barcodes and reliable molecular identifications in a diverse group of invasive pests: lessons from Bactrocera fruit flies on variation across the COI gene, introgression, and standardization
Camiel Doorenweerd, Michael San Jose, Luc Leblanc, Norman Barr, Scott Geib, Arthur Y.C. Chung, Julian Dupuis, Arni Ekayanti, Elaida R. Fiegalan, K.S. Hemachandra, M. Aftab Hossain, Chia-Lung Huang, Yu-Feng Hsu, Kimberly Y. Morris, Andi Maryani Mustapeng, Jerome Niogret, Thai Hong Pham, U.G.A.I. Sirisena, Daniel Rubinoff
bioRxiv 2020.11.23.394510; doi: https://doi.org/10.1101/2020.11.23.394510
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DNA barcodes and reliable molecular identifications in a diverse group of invasive pests: lessons from Bactrocera fruit flies on variation across the COI gene, introgression, and standardization
Camiel Doorenweerd, Michael San Jose, Luc Leblanc, Norman Barr, Scott Geib, Arthur Y.C. Chung, Julian Dupuis, Arni Ekayanti, Elaida R. Fiegalan, K.S. Hemachandra, M. Aftab Hossain, Chia-Lung Huang, Yu-Feng Hsu, Kimberly Y. Morris, Andi Maryani Mustapeng, Jerome Niogret, Thai Hong Pham, U.G.A.I. Sirisena, Daniel Rubinoff
bioRxiv 2020.11.23.394510; doi: https://doi.org/10.1101/2020.11.23.394510

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