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Genetic structure of Lycorma delicatula (Hemiptera: Fulgoridae) populations in Korea: implication for invasion processes in heterogeneous landscapes

Published online by Cambridge University Press:  08 March 2013

Marana Park ,
Kyung-Seok Kim  and
Joon-Ho Lee
Marana Park
Affiliation:
Entomology Program, Department of Agricultural Biotechnology, Seoul National University, Seoul, 151-921, Republic of Korea
Kyung-Seok Kim
Affiliation:
College of Veterinary Medicine, Seoul National University, Seoul, Republic of Korea
Joon-Ho Lee*
Affiliation:
Entomology Program, Department of Agricultural Biotechnology, Seoul National University, Seoul, 151-921, Republic of Korea Research Institute for Agriculture and Life Sciences, Seoul National University, Seoul, 151-921, Republic of Korea
*
*Author for correspondence Phone: +82 2 880 4705 Fax: +82 2 873 2319 E-mail: jh7lee@snu.ac.kr
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Abstract

Lycorma delicatula (White) was identified in 2004 as an invasive pest in South Korea, where it causes serious damage to vineyard crops. To investigate the population structure and dispersal pattern of L. delicatula in South Korea, we estimated the population genetic structure and gene flow among nine locations across the country using seven microsatellite markers. Although L. delicatula spread throughout most of its geographical range in South Korea within 5–7 years following invasion, its populations show evidence of genetic structuring across the range with a low but significant global FST (genetic differentiation across all populations) of 0.0474. Bayesian-based clustering analysis indicates the presence of at least three genetically unique populations in South Korea, including populations in northeastern South Korea, which show a distinct genetic background. However, isolation by distance suggests that populations in South Korea have not yet reached genetic equilibrium. Estimates of the historical rate of gene flow (Nem) indicate that relatively high rates of flow have been maintained among populations within the western region, which may indicate recent range expansion. A population assignment test using the first-generation migrant detection method suggested that long-distance dispersal of L. delicatula may have occurred over large areas of South Korea. More complex dispersal patterns may have occurred during L. delicatula invasion of heterogeneous landscapes in South Korea.

Keywords

Lycorma delicatulainvasive pestmicrosatellitegenetic structure
Type
Research Paper
Information
Bulletin of Entomological Research , Volume 103 , Issue 4 , August 2013 , pp. 414 - 424
Copyright
Copyright © Cambridge University Press 2013 

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References

Allendorf, F.W. & Lundquist, L.L. (2003) Introduction: population biology, evolution, and control of invasive species. Conservation Biology 17, 24–30.Google Scholar
Bohonak, A.J. (1999) Dispersal, gene flow, and population structure. Quarterly Review of Biology 74, 21–45.CrossRefGoogle ScholarPubMed
Chapuis, M.P. & Estoup, A. (2007) Microsatellite null alleles and estimation of population differentiation. Molecular Biology and Evolution 24, 621–631.Google Scholar
Cornuet, J.M. & Luikart, G. (1996) Description and power analysis of two tests for detecting recent population bottlenecks from allele frequency data. Genetics 144, 2001–2014.CrossRefGoogle ScholarPubMed
Cornuet, J.M., Piry, S., Luikart, G., Estoup, A. & Solignac, M. (1999) New methods employing multilocus genotypes to select or exclude populations as origins of individuals. Genetics 153, 1989–2000.Google Scholar
Di Rienzo, A., Peterson, A., Garza, J.C., Valdes, A., Slatkin, M. & Freimer, N.B. (1994) Mutational processes of simple-sequence repeat loci in human populations. Genetics 91, 3166–3170.Google Scholar
Don, R.H., Cox, P.T., Wainwright, B.J., Baker, K. & Mattick, J.S. (1991) ‘Touchdown’ PCR to circumvent spurious priming during gene amplification. Nucleic Acids Research 19, 4008.Google Scholar
Evanno, G., Regnaut, S. & Goudet, J. (2005) Detecting the number of clusters of individuals using the software structure: a simulation study. Molecular Ecology 14, 2611–2620.CrossRefGoogle ScholarPubMed
Fitzpatrick, B.M., Fordyce, J.A., Neimiller, L. & Reynolds, G. (2012) What can DNA tell us about biological invasions? Biological Invasions 14, 245–253.CrossRefGoogle Scholar
Garza, J.C. & Williamson, E.G. (2001) Detection of reduction in population size using data from microsatellite loci. Molecular Ecology 10, 305–318.CrossRefGoogle ScholarPubMed
Goudet, J. (2001) Fstat, a program to estimate and test gene diversities and fixation indices (Version 2.9.3). Available from http://www.unil.ch/izea/softwares/fstat.htmlGoogle Scholar
Han, J.M., Kim, H.J., Lim, E.J., Lee, S.H., Kwon, Y.J. & Cho, S.W. (2008) Lycorma delicatula (Hemiptera: Auchenorrhyncha: Fulgoridae: Aphaeninae) finally, but suddenly arrived in Korea. Entomological Research 38, 281–286.CrossRefGoogle Scholar
Harley, E.H. (2001) AGARst. A Program for Calculating Allele Frequencies, GST, and RST from Microsatellite Data, version 2. South Africa, University of Cape Town.Google Scholar
Hastings, A., Cuddington, K., Davies, K.F., Dugaw, C.J., Elmendorf, S., Freestone, A., Harrison, S., Holland, M., Lambrinos, J., Malvadkar, U., Melbourne, B.A., Moore, K., Taylor, C. & Thomson, D. (2005) The spatial spread of invasions: new developments in theory and evidence. Ecology Letters 8, 91–101.Google Scholar
Herborg, L.M., Weetman, D., Van Oosterhout, C. & Hänfling, B. (2007) Genetic population structure and contemporary dispersal patterns of a recent European invader, the Chinese mitten crab, Eriocheir sinensis. Molecular Ecology 16, 231–242.Google Scholar
Kim, J., Lee, E.H., Seo, Y.M. & Kim, N.Y. (2011) Cyclic behavior of Lycorma delicatula (Insecta: Hemiptera: Fulgoridae) on host plants. Journal of Insect Behavior 24, 423–435.Google Scholar
Kim, K.S. & Sappington, T.W. (2006) Molecular genetic variation of boll weevil populations in North America estimated with microsatellites: implications for patterns of dispersal. Genetica 127, 143–161.CrossRefGoogle ScholarPubMed
Kim, K.S., Ratcliffe, S.T., French, B.W. & Sappington, T.W. (2008) Utility of EST-derived SSRs as population genetics markers in a beetle. Journal of Heredity 99, 112–124.Google Scholar
Kim, K.S., Bagley, M.J., Coates, B.S., Hellmich, R.L. & Sappington, T.W. (2009) Spatial and temporal genetic analyses show high gene flow among European corn borer (Lepidoptera: Crambidae) populations across the central U.S. corn belt. Environmental Entomology 38, 1312–1323.Google Scholar
Kim, S.S. & Kim, T.W. (2005) Lycorma delicatula (White) (Hemiptera : Fulgoridae) in Korea. Lucanus 5, 9–10.Google Scholar
Lee, I.Y. & Uhm, K.B. (1993) Landing, settling and spreading of the rice water weevil in Korea. pp. 42–57in Hirai, K. (Ed.) Establishment, Spread, and Management of the Rice Water Weevil and Migratory Rice Insect Pests in East Asia. NARC, Tsukuba.Google Scholar
Lee, J.S., Kim, I.K., Koh, S.H., Cho, S.J., Jang, S.J., Pyo, S.H. & Choi, W.I. (2011) Impact of minimum winter temperature on Lycorma delicatula (Hemiptera: Fulgoridae) egg mortality. Journal of Asia-Pacific Entomology 14, 123–125.Google Scholar
Liu, G. (1939) Some extracts from the history of entomology in China. Psyche 46, 23–28.Google Scholar
Luikart, G., Allendorf, F., Cornuet, J.M. & Sherwin, W. (1998) Distortion of allele frequency distributions provides a test for recent population bottlenecks. Journal of Heredity 89, 238–247.Google Scholar
McRae, B.H. (2006) Isolation by resistance. Evolution 60, 1551–1561.Google Scholar
Miller, N., Estoup, A., Toepfer, S., Bourguet, D., Lapchin, L., Derridj, S., Kim, K.S., Reynaud, P., Furlan, L. & Guillemaud, T. (2005) Multiple transatlantic introductions of the western corn rootworm. Science 310, 992.Google Scholar
Ohta, T. & Kimura, M. (1973) A model of mutation appropriate to estimate the number of electrophoretically detectable alleles in a finite population. Genetical Research 22, 201–204.Google Scholar
Paetkau, D., Slade, R., Burden, M. & Estoup, A. (2004) Genetic assignment methods for the direct, real-time estimation of migration rate: a simulation-based exploration of accuracy and power. Molecular Ecology 13, 55–65.CrossRefGoogle Scholar
Park, J.D., Kim, M., Lee, S.G., Shin, S.C., Kim, J. & Park, I.K. (2009) Biological characteristics of Lycorma delicatula and the control effects of some insecticides. Korean Journal of Applied Entomology 48, 53–57.Google Scholar
Park, M., Kim, K.S. & Lee, J.H. (2012) Isolation and characterization of eight microsatellite loci from Lycorma delicatula (White) (Hemiptera: Fulgoridae) for population genetic analysis in Korea. Molecular Biology Reports 39, 5637–5641.Google Scholar
Park, S.D.E. (2001) Trypanotolerance in West African cattle and population genetic effects of selection. PhD thesis, University of Dublin, Dublin, Ireland.Google Scholar
Peakall, R. & Smouse, P.E. (2006) Genalex6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes 6, 288–295.Google Scholar
Piry, S., Luikart, G. & Cornuet, J.M. (1999) Bottleneck: a program for detecting recent effective population size reductions from allele data frequencies. Journal of Heredity 90, 502–503.Google Scholar
Piry, S., Alapetite, A., Cornuet, J.M., Paetkau, D., Baudouin, L. & Esop, A. (2004) Geneclass2: a software for genetic assignment and first-generation migrant detection. Journal of Heredity 95, 536–539.Google Scholar
Pritchard, J.K., Stephens, M. & Donnelly, P. (2000) Inference of population structure using multilocus genotype data. Genetics 155, 945–959.Google Scholar
Puth, L.M. & Post, D.M. (2005) Studying invasion: have we missed the boat? Ecology Letters 8, 715–721.Google Scholar
Rannala, B. & Mountain, J.L. (1997) Detecting immigration by using multilocus genotypes. Genetics 94, 9197–9201.Google Scholar
Raymond, M. & Rousset, F. (1995) An exact test for population differentiation. Evolution 49, 1280–1283.CrossRefGoogle ScholarPubMed
Rice, W.R. (1989) Analyzing tables of statistical tests. Evolution 43, 223–225.CrossRefGoogle ScholarPubMed
Rousset, F. (2000) Genetic differentiation between individuals. Journal of Evolutionary Biology 13, 58–62.Google Scholar
Van Oosterhout, C., Hutchinson, W.F., Wills, D.P.M. & Shipley, P. (2004) Micro-Checker: software for identifying and correcting genotyping errors in microsatellite data. Molecular Ecology Notes 4, 535–538.Google Scholar
Wahlund, S. (1928) Zusammensetzung von populationen und korrelationserscheinungen vom standpunkt der vererbungslehre aus betrachtet. Hereditas 11, 65–106.CrossRefGoogle Scholar
Wright, S. (1931) Evolution in Mendelian populations. Genetics 16, 290.Google Scholar
Wright, S. (1943) Isolation by distance. Genetic 28, 114–138.Google Scholar