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Ommatissus lybicus (Hemiptera: Tropiduchidae), an economically important pest of date palm (Arecaceae) with highly divergent populations

Published online by Cambridge University Press:  03 April 2018

Abdoolnabi Bagheri ,
Yaghoub Fathipour ,
Majeed Askari-Seyahooei  and
Mehrshad Zeinalabedini
Abdoolnabi Bagheri
Affiliation:
Department of Entomology, Faculty of Agriculture, Tarbiat Modares University, P.O.Box 14115-336, Tehran, Iran
Yaghoub Fathipour*
Affiliation:
Department of Entomology, Faculty of Agriculture, Tarbiat Modares University, P.O.Box 14115-336, Tehran, Iran
Majeed Askari-Seyahooei
Affiliation:
Plant Protection Research Department, Hormozgan Agricultural and Natural Resources Research and Education Center, Agricultural Research Education and Extension Organization (AREEO), Bandar Abbas, Iran
Mehrshad Zeinalabedini
Affiliation:
Department of Systems Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research Education and Extension Organization (AREEO), Karaj, Iran
*
1Corresponding author: (e-mail: fathi@modares.ac.ir)
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Abstract

Ommatissus lybicus de Bergevin (Hemiptera: Tropiduchidae) is a key pest of date palm (Phoenix dactylifera Linnaeus; Arecaceae) with worldwide distribution and various management strategies. To study genetic diversity of date palm hopper, a series of experiments was conducted on genetic structure and genetic diversity of 15 geographic populations of O. lybicus (Abu Musa, Bam, Bushehr, Behbahan, Tezerj, Fin, Jiroft, Shahdad, Jahrom, Ghire Karzin, Ghasre Shirin, Iran; Pakistan; Oman; Egypt; and Tunisia) by amplified fragment length polymorphism, cytochrome c oxidase subunit I (COI), and 28S rRNA markers. Analysis of molecular variance analysis of amplified fragment length polymorphism data and COI sequences revealed a significant variation among O. lybicus populations (94.12% and 65.08% similarities for amplified fragment length polymorphism and COI, respectively). The 28S rDNA sequences from different populations were identical. Phylogenetic network inferred from amplified fragment length polymorphism data and COI sequences grouped two geographically close populations (Tezerj and Bam) in the two distinct clades while far apart geographical populations bunched in the same or close clades. These two populations experience repeated exposure to heavy pesticide applications annually. In conclusion, study of the genetic structure revealed a considerable variation between O. lybicus populations under intensive chemical strategies.

Type
Biodiversity & Evolution
Information
The Canadian Entomologist , Volume 150 , Issue 3 , June 2018 , pp. 378 - 392
Copyright
© Entomological Society of Canada 2018 

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Footnotes

Subject editor: Amanda Roe

References

Bagheri, A., Fathipour, Y., Askari-Seyahooei, M., and Zeinolabedini, M. 2016. How different populations and host plant cultivars affect two-sex life table parameters of the date palm hopper, Ommatissus lybicus (Hemiptera: Tropiduchidae). Journal of Agricultural Science and Technology, 18: 1606–1619.Google Scholar
Bagheri, A., Fathipour, Y., Askari-Seyahooei, M., and Zeinolabedini, M. 2017. Reproductive isolation among allopatric populations of date palm hopper, Ommatissus lybicus (Hemiptera: Tropiduchidae). Annals of the Entomological Society of America, 110: 337–343.Google Scholar
Ballman, E.S., Rugman-Jones, P.F., Stouthamer, R., and Hoddle, M.S. 2011. Genetic structure of Graphocephala atropunctata (Hemiptera: Cicadellidae) populations across its natural range in California reveals isolation by distance. Journal of Economic Entomology, 104: 279–287.Google Scholar
Berteaux, D., Reale, D., McAdam, A.G., and Boutin, S. 2004. Keeping pace with fast climate change: can Arctic life count on evolution? Integrative and Comparative Biology, 44: 140–151.Google Scholar
Bonin, A., Paris, M., Tetreau, G., David, J.P., and Despres, L. 2009. Candidate genes revealed by a genome scan for mosquito resistance to a bacterial insecticide: sequence and gene expression variation. BMC Genomics, 10: 551. https://doi.org/10.1186/1471-2164-10-551.Google Scholar
Brown, A.R., Hosken, D.J., Balloux, F., Bickley, L.K., Le Page, G., Owen, S.F., et al. 2009. Genetic variation, inbreeding and chemical exposure-combined effects in wildlife and critical considerations for ecotoxicology. Philosophical Transactions of the Royal Society B: Biological Sciences, 364: 3377–3390.Google Scholar
Chang, X., Zhong, D., Lo, E., Fang, Q., Bonizzoni, M., Wang, X., et al. 2016. Landscape genetic structure and evolutionary genetics of insecticide resistance gene mutation in Anopheles sinensis . Parasites & Vectors, 9: 228. https://doi.org/10.1186/s13071-016-1513-6.Google Scholar
Cifuentes, D., Chynoweth, R., and Bielza, P. 2011. Genetic study of Mediterranean and South American populations of tomato leafminer Tuta absoluta (Povolny 1994) (Lepidoptera: Gelechidae) using ribosomal and mitochondrial markers. Pest Management Science, 67: 1155–1162.Google Scholar
Clement, M., Posada, D., and Crandall, K.A. 2000. TCS: a computer program to estimate gene genealogies. Molecular Ecology, 9: 1657–1660.Google Scholar
Ellers, J. and Boggs, C.L. 2004. Functional ecological implications of intraspecific differences in wing melanization in Colias butterflies. Biological Journal of the Linnean Society, 82: 79–87.Google Scholar
Excoffier, L. and Lischer, H.E.L. 2010. Arlequin suite ver 3.5: a new series of programs to perform population genetic analyses under Linux and Window. Molecular Ecology Resources, 10: 564–567.Google Scholar
Fayet, A.L., Tobia, J.A., Hintzen, R.F., and Seddon, N. 2014. Immigration and dispersal are key determinants of cultural diversity in songbird population. Behavioral Ecology, 25: 744–753.Google Scholar
Folmer, O., Hoeh, W.R.M., Black, B., and Vrijenhoek, R.C. 1994. Conserved primers for PCR amplification of mitochondrial DNA from different invertebrate phyla. Molecular Marine Biology and Biotechnology, 3: 294–299.Google Scholar
Galtier, N., Nabholz, B., Glemin, S., and Hurst, G.D.D. 2009. Mitochondrial DNA as a marker of molecular diversity: a reappraisal. Molecular Ecology, 18: 4541–4550.Google Scholar
Hawthorne, D.J. 2001. AFLP-based genetic linkage map of the Colorado potato beetle Leptinotarsa decemlineata: sex chromosomes and a pyrethroid-resistance candidate gene. Genetics, 158: 695–700.Google Scholar
Hoffmann, A.A. and Sgro, C.M. 2011. Climate change and evolutionary adaptation. Nature, 470: 479–485.CrossRefGoogle ScholarPubMed
Howard, F.W., Giblin-Davis, R., Moore, D., and Abad, R. 2001. Insects on palms. Centre for Agriculture and Biosciences International. Centre for Agriculture and Bioscience International, Wallingford, Oxon, United Kingdom.Google Scholar
Huson, D.H. and Bryant, D. 2006. Application of phylogenetic networks in evolutionary studies. Molecular Biology and Evolution, 23: 254–267.Google Scholar
Jensen, J.L., Bohonak, A.J., and Kelley, S.T. 2005. Isolation by distance, web service. BMC Genetics, 6: 13. https://doi.org/10.1186/1471-2156-6-13.Google Scholar
Kavar, T., Pavlovcic, P., Susnik, S., Meglic, V., and Virant-Doberlet, M. 2006. Genetic differentiation of geographically separated populations of the southern green stink bug Nezara viridula (Hemiptera: Pentatomidae). Bulletin of Entomological Research, 96: 117–128.Google Scholar
Larget, B. and Simon, D.L. 1999. Markov chain Monte Carlo algorithms for the Bayesian analysis of phylogenetic trees. Molecular Biology and Evolution, 16: 750–759.Google Scholar
Larkin, M.A., Blackshields, G., Brown, N.P., Chenna, R., McGettigan, P.A., McWilliam, H., et al. 2007. Clustal W and Clustal X version 2.0. Bioinformatics, 23: 2947–2948.Google Scholar
Librado, P. and Rozas, J. 2009. DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics, 25: 1451–1452.Google Scholar
Mantel, N. 1967. The detection of disease clustering and a generalized regression approach. Cancer Research, 27: 209–220.Google Scholar
Mezghani, M., Bouktila, D., Kharrat, I., Makni, M., and Makni, H. 2012. Genetic variability of green citrus aphid populations from Tunisia, assessed by RAPD markers and mitochondrial DNA sequences. Entomological Science, 15: 171–179.Google Scholar
Nylander, J.A.A. 2004. MrModeltest V2. Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden.Google Scholar
Paradis, E., Claude, J., and Strimmer, K. 2004. Analyses of phylogenetics and evolution in R language. Bioinformatics, 20: 289–290.Google Scholar
Penton, E.H., Hebert, P.D.N., and Crease, T.J. 2004. Mitochondrial DNA variation in North American populations of Daphnia obtuse: continentalism or cryptic endemism? Molecular Ecology, 13: 97–107.Google Scholar
Piiroinen, S., Lindstrom, L., Lyytinen, A., Mappes, J., Chen, Y.H., Izzo, V., and Grapputo, A. 2013. Pre-invasion history and demography shape the genetic variation in the insecticide resistance-related acetylcholinesterase 2 gene in the invasive Colorado potato beetle. BMC Evolutionary Biology, 13: 13. https://doi.org/10.1186/1471-2148-13-13.Google Scholar
Reinecke, A., Karlovsky, P., and Zebit, C.P.W. 1998. Preparation and purification of DNA from insects for AFLP analysis. Insect Molecular Biology, 7: 95–99.Google Scholar
Ronquist, F. and Huelsenbeck, J.P. 2003. MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics, 19: 1572–1574.Google Scholar
Shah, A., Mohsin, A., Bodlah, I., and Hafez, Z. 2012. Dubas bug, Ommatissus lybicus (Tropiduchidae: Hemiptera) - a new record from Panjgur, Balochestan, Pakistan. Pakistan Journal of Zoology, 44: 1765–1769.Google Scholar
Takahiro, M. 2012. The genetic architecture of insecticide resistance within a natural population of Drosophila melanogaster . Open Journal of Genetics, 2: 90–94.Google Scholar
Templeton, A.R., Crandall, K.A., and Sing, C.F. 1992. A cladistic analysis of phenotypic associations with haplotypes inferred from restriction endonuclease mapping and DNA sequence data III. Cladogram estimation. Genetics, 132: 619–633.Google Scholar
Thaler, R., Brandstatter, A., Meraner, A., Chabicovsky, W., Parson, W., Zelger, R., et al. 2008. Molecular phylogeny and population structure of the codling moth (Cydia pomonella) in Central Europe: II. AFLP analysis reflects human-aided local adaptation of a global pest species. Molecular Phylogenetics and Evolution, 48: 838–849.Google Scholar
Timmermans, M.J.T.N., Ellers, J., Marien, J., Verhoef, S.C., Ferwerda, E.B., and Van Straalen, N.M. 2005. Genetic structure in Orchesella cincta (Collembola): strong subdivision of European populations inferred from mtDNA and AFLP markers. Molecular Ecology, 14: 2017–2024.CrossRefGoogle ScholarPubMed
Wang, M.L., Barkley, N.A., and Jenkin, T.M. 2009. Microsatellite markers in plant and insects. Part I: applications of biotechnology. Genes, Genomes and Genomics, 3: 54–67.Google Scholar
Weir, B.S. and Cockerham, C.C. 1984. Estimating F-statistics for the analysis of population structure. Evolution, 38: 1358–1370.Google Scholar
Wilson, M.R. 1986. The Auchenorrhyncha (Homoptera) associated with palms. Proceedings of the Second International Workshop on Leafhoppers and Plant Hoppers of Economic Importance, 28: 327–342.Google Scholar
Wilson, M.R. 1988. Records of Homoptera, Auchenorrhyncha from palms and associations with disease in coconuts. Oleagineux, 43: 247–253.Google Scholar
Zaid, A. 2002. Date palm cultivation. Food and Agriculture Organization, Plant Product Protection, Rome, Italy.Google Scholar