Hostname: page-component-586b7cd67f-rcrh6 Total loading time: 0 Render date: 2024-11-22T08:50:38.137Z Has data issue: false hasContentIssue false
  • English
  • Français

New microsatellites revealed strong gene flow among populations of a new outbreak pest, Athetis lepigone (Möschler)

Published online by Cambridge University Press:  27 November 2017

W.-C. Zhu ,
J.-T. Sun ,
J. Dai ,
J.-R. Huang ,
L. Chen  and
X.-Y. Hong
W.-C. Zhu
Affiliation:
Department of Entomology, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
J.-T. Sun
Affiliation:
Department of Entomology, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
J. Dai
Affiliation:
Department of Entomology, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
J.-R. Huang
Affiliation:
Institute of Plant Protection, Henan Academy of Agricultural Sciences, Zhengzhou, Henan 450002, China
L. Chen
Affiliation:
Department of Entomology, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
X.-Y. Hong*
Affiliation:
Department of Entomology, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
*
*Author for correspondence Phone: +86-25-84395339 Fax: +86-25-84395339 E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Athetis lepigone (Möschler) (Lepidoptera: Noctuidae) is a new outbreak pest in China. Consequently, it is unclear whether the emergence and spread of the outbreak of this pest are triggered by rapid in situ population size increases in each outbreak area, or by immigrants from a potential source area in China. In order to explore the outbreak process of this pest through a population genetics approach, we developed ten novel polymorphic expressed sequence tags (EST)-derived microsatellites. These new microsatellites had moderately high levels of polymorphism in the tested population. The number of alleles per locus ranged from 3 to 19, with an average of 8.6, and the expected heterozygosity ranged from 0.269 to 0.783. A preliminary population genetic analysis using these new microsatellites revealed a lack of population genetic structure in natural populations of A. lepigone. The estimates of recent migration rate revealed strong gene flow among populations. In conclusion, our study developed the first set of EST-microsatellite markers and shed a new light on the population genetic structure of this pest in China.

Keywords

SSRgenetic diversitygenetic structure
Type
Research Papers
Information
Bulletin of Entomological Research , Volume 108 , Issue 5 , October 2018 , pp. 636 - 644
Check for updates
Copyright
Copyright © Cambridge University Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

†

These authors contributed equally to this work.

References

Agrawal, P.K. & Shrivastava, R. (2014) Molecular markers. pp. 25–39 in Ravi, I., Baunthiyal, M. & Saxena, J. (Eds) Advances in Biotechnology. India, Springer Press.Google Scholar
Carew, M., Gagliardi, B. & Hoffmann, A.A. (2013) Mitochondrial DNA suggests a single maternal origin for the widespread triploid parthenogenetic pest species, Paratanytarsus grimmii, but microsatellite variation shows local endemism. Insect Science 20, 345–357.Google Scholar
Chen, F., Ahmed, T., Liu, Y.Y., He, K.L. & Wang, Z.Y. (2014) Analysis of genetic diversity among different geographic populations of Athetis lepigone using ISSR molecular markers. Journal of Asia-Pacific Entomology 17, 793–798.Google Scholar
Chen, Y.X. (1999) Fauna Sinica, Lepidoptera: Noctuidae. Beijing, Science Press, pp. 753–754.Google Scholar
Delamaire, S., Esselink, G.D., Samiei, L., Courtin, C., Magnoux, E., Rousselet, J. & Smulders, M.J.M. (2010) Isolation and characterization of six microsatellite loci in the larch budmoth Zeiraphera diniana (Lepidoptera: Tortricidae). European Journal of Entomology 107, 267–269.Google Scholar
Endersby, N.M., Mckechnie, S.W., Ridland, P.M. & Weeks, A.R. (2006) Microsatellites reveal a lack of structure in Australian populations of the diamondback moth, Plutella xylostella (L.). Molecular Ecology 15, 107–118.Google Scholar
Excoffier, L. & Lischer, H.E.L. (2010) Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Molecular Ecology Resources 10, 564–567.Google Scholar
Excoffier, L., Hofer, T. & Foll, M. (2009) Detecting loci under selection in a hierarchically structured population. Heredity 103, 285–298.Google Scholar
Franklin, M.T., Ritland, C.E. & Myers, J.H. (2011) Genetic analysis of cabbage loopers, Trichoplusia ni (Lepidoptera: Noctuidae), a seasonal migrant in western North America. Evolutionary Applications 4, 89–99.Google Scholar
Fu, X., Liu, Y., Li, Y., Ali, A. & Wu, K. (2014) Does Athetis lepigone moth (Lepidoptera: Noctuidae) take a long-distance migration? Journal of Economic Entomology 107, 995–1002.Google Scholar
Gayathri Samarasekera, G.D., Bartell, N.V., Lindgren, B.S., Cooke, J.E., Davis, C.S., James, P.M., Coltman, D. W., Mock, K. E. & Murray, B. W. (2012) Spatial genetic structure of the mountain pine beetle (Dendroctonus ponderosae) outbreak in western Canada: historical patterns and contemporary dispersal. Molecular Ecology 21, 2931–2948.Google Scholar
Goudet, J. (2002) FSTAT Version 2.9.3.2 for windows: a computer program to calculate F-statistics. Available online at http://www2.unil.ch/popgen/softwares/fstatGoogle Scholar
Grabherr, M.G., Haas, B.J., Yassour, M., Levin, J.Z., Thompson, D.A., Amit, I., Adiconis, X., Fan, L., Raychowdhury, R., Zeng, Q., Chen, Z., Mauceli, E., Hacohen, N., Gnirke, A., Rhind, N., di Palma, F., Birren, B.W., Nusbaum, C., Lindblad-Toh, K., Friedman, N. & Regev, A. (2011) Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nature Biotechnology 29, 644–U130.Google Scholar
Guichoux, E., Lagache, L., Wagner, S., Chaumeil, P., Leger, P., Lepais, O., Lepoittevin, C., Malausa, T., Revardel, E., Salin, F. & Petit, R.J. (2011) Current trends in microsatellite genotyping. Molecular Ecology Resources 11, 591–611.Google Scholar
Harper, G.L., Maclean, N. & Goulson, D. (2003) Microsatellite markers to assess the influence of population size, isolation and demographic change on the genetic structure of the UK butterfly Polyommatus bellargus. Molecular Ecology 12, 3349–3357.Google Scholar
Hubisz, M.J., Falush, D., Stephens, M. & Pritchard, J.K. (2009) Inferring weak population structure with the assistance of sample group information. Molecular Ecology Resources 9, 1322–1332.Google Scholar
Hurst, G.D. & Jiggins, F.M. (2005) Problems with mitochondrial DNA as a marker in population, phylogeographic and phylogenetic studies: the effects of inherited symbionts. Proceedings of the Royal Society of London. Series B: Biological Sciences 272, 1525–1534.Google Scholar
Jensen, J.L., Bohonak, A.J. & Kelley, S.T. (2005) Isolation by distance, web service. BMC Genetics 6, 13.Google Scholar
Jiang, J.Y., Li, X.Q., Xu, Y.H., Li, Z.H., Zhang, Z.Y. & Xu, H. (2008) Preliminary studies on Athetis (Proxenus) lepigone. Plant Protection 34, 123–126.Google Scholar
Jiang, X.F., Luo, L.Z., Jiang, Y.Y., Zhang, Y.J., Zhang, L. & Wang, Z.Y. (2011) Damage characteristics and outbreak causes of Athetis lepigone in China. Plant Protection 37, 130–133.Google Scholar
Jombart, T. (2008) Adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics 24, 1403–1405.Google Scholar
Jombart, T., Devillard, S. & Balloux, F. (2010) Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genetics 11, 94.Google Scholar
Keyghobadi, N., Roland, J. & Strobeck, C. (1999) Influence of landscape on the population genetic structure of the alpine butterfly Parnassius smintheus (Papilionidae). Molecular Ecology 8, 1481–1495.Google Scholar
Kim, K.S., Cano-Rios, P. & Sappington, T.W. (2006) Using genetic markers and population assignment techniques to infer origin of boll weevils (Coleoptera: Curculionidae) unexpectedly captured near an eradication zone in Mexico. Environmental Entomology 35, 813–826.Google Scholar
Kobayashi, T., Sakurai, T., Sakakibara, M. & Watanabe, T. (2011) Multiple origins of outbreak populations of a native insect pest in an agro-ecosystem. Bulletin of Entomological Research 101, 313–324.Google Scholar
Kofler, R., Schloetterer, C. & Lelley, T. (2007) Sciroko: a new tool for whole genome microsatellite search and investigation. Bioinformatics 23, 1683–1685.Google Scholar
Li, H., Lang, K.L., Fu, H.B., Shen, C.P., Wan, F.H. & Chu, D. (2015) Analysis of expressed sequence tags (ESTs) from a normalized cDNA library and isolation of EST simple sequence repeats from the invasive cotton mealybug phenacoccus solenopsis. Insect Science 22, 761–767.Google Scholar
Li, L.T., Zhu, Y.B., Ma, J.F., Li, Z.Y. & Dong, Z.P. (2013) An analysis of the Athetis lepigone transcriptome from four developmental stages. PLoS ONE 8, e73911.Google Scholar
Loxdalel, H.D. & Lushai, G. (2001). Use of genetic diversity in movement studies of flying insects. pp. 361–368 in Woiwod, I.P., Reynolds, D.R. & Thomas, C.D. (Eds). Insect Movement: T: Mechanisms and Consequences. London, CABI.Google Scholar
Meglécz, E., Petenian, F., Danchin, E., Coeur d'Acier, A., Rasplus, J.Y. & Faure, E. (2004) High similarity between flanking regions of different microsatellites detected within each of two species of Lepidoptera: Parnassius apollo and Euphydryas aurinia. Molecular Ecology 13, 1693–1700.Google Scholar
Mikheyev, A.S., Vo, T., Wee, B., Singer, M.C. & Parmesan, C. (2010) Rapid microsatellite isolation from a butterfly by de novo transcriptome sequencing: performance and a comparison with AFLP-derived distances. PLoS ONE 5, e11212.Google Scholar
Peakall, R. & Smouse, P.E. (2012) Genalex 6.5: genetic analysis in excel. Population genetic software for teaching and research—an update. Bioinformatics 28, 2537–2539.Google Scholar
Porretta, D., Canestrelli, D., Bellini, R., Celli, G. & Urbanelli, S. (2007) Improving insect pest management through population genetic data: a case study of the mosquito Ochlerotatus caspius (Pallas). Journal of Applied Ecology 44, 682–691.Google Scholar
Pritchard, J.K., Stephens, M. & Donnelly, P. (2000) Inference of population structure using multilocus genotype data. Genetics 155, 945–959.Google Scholar
Puechmaille, S.J. (2016) The program STRUCTURE does not reliably recover the correct population structure when sampling is uneven: sub-sampling and new estimators alleviate the problem. Molecular Ecology Resources 16, 608.Google Scholar
R Development Core Team (2005) R: A Language and Environment for Statistical Computing. Vienna, Austria, R Foundation for Statistical Computing, 2005, ISBN:3-900051-07-0. Available online at http://www.R-project.orgGoogle Scholar
Rambaut, A., Suchard, M. & Drummond, A. (2013) Tracer v1.6. Available online at http://tree.bio.ed.ac.uk/software/tracer/Google Scholar
Rašić, G., Filipović, I., Weeks, A.R. & Hoffmann, A.A. (2014) Genome-wide SNPs lead to strong signals of geographic structure and relatedness patterns in the major arbovirus vector, Aedes aegypti. BMC Genomics 15, 275.Google Scholar
Raymond, M. & Rousset, F. (1995) GENEPOP (version 1.2): population genetics software for exact tests and ecumenicism. Journal of Heredity 86, 248–249.Google Scholar
Rozen, S. & Skaletsky, H. (2000) Primer3 on the WWW for general users and for biologist programmers. pp. 365–386. in Misener, S. & Krawetz, S. (Eds) Bioinformatics Methods and Protocols: Methods in Molecular Biology. Totowa, Humana Press.Google Scholar
Selkoe, K.A. & Toonen, R.J. (2006) Microsatellites for ecologists: a practical guide to using and evaluating microsatellite markers. Ecology Letters 9, 615–629.Google Scholar
Sinama, M., Dubut, V., Costedoat, C., Gilles, A., Junker, M., Malausa, T., Martin, J.-F., Neve, G., Pech, N., Schmitt, T., Zimmermann, M. & Meglecz, E. (2011) Challenges of microsatellite development in Lepidoptera: Euphydryas aurinia (Nymphalidae) as a case study. European Journal of Entomology 108, 261–266.Google Scholar
Sun, J.-T., Zhang, Y.-K., Ge, C. & Hong, X.-Y. (2011) Mining and characterization of sequence tagged microsatellites from the brown planthopper Nilaparvata lugens. Journal of Insect Science 11, 134.Google Scholar
Sun, J.T., Jiang, X.Y., Wang, M.M. & Hong, X.Y. (2014) Development of microsatellite markers for, and a preliminary population genetic analysis of, the white-backed planthopper. Bulletin of Entomological Research 104, 765–773.Google Scholar
Sun, J.T., Wang, M.M., Zhang, Y.K., Chapuis, M.P., Jiang, X.Y., Hu, G., Yang, X.M., Ge, C., Xue, X.F. & Hong, X.Y. (2015) Evidence for high dispersal ability and mito-nuclear discordance in the small brown planthopper, Laodelphax striatellus. Scientific Reports 5, 8045.Google Scholar
Tay, W.T., Behere, G.T., Batterham, P. & Heckel, D.G. (2010) Generation of microsatellite repeat families by RTE retrotransposons in lepidopteran genomes. BMC Evolutionary Biology 10, 144.Google Scholar
van Oosterhout, C., Hutchinson, W.F., Wills, D.P. & Shipley, P. (2004) Micro-checker: software for identifying and correcting genotyping errors in microsatellite data. Molecular Ecology Notes 4, 535–538.Google Scholar
Van't hof, A.E., Zwaan, B.J., Saccheri, I.J., Daly, D., Bot, A.N.M. & Brakefield, P.M. (2005) Characterization of 28 microsatellite loci for the butterfly Bicyclus anynana. Molecular Ecology Notes 5, 169–172.Google Scholar
Wang, J., Yu, Y., Zhao, N., Zhang, S.A., Zhao, X.H., Zhuang, Q.Y., Men, X.Y. & Li, L.L. (2013) The research progress of proxenus lepigone in China. Biological Disaster Science 36, 95–99.Google Scholar
Wang, Z.Y., Shi, J. & Dong, J.G. (2012) Reason analysis on Proxenus lepigone outbreak of summer corn region in the Yellow River, huai and Hai rivers plain and the countermeasures suggested. Journal of Maize Sciences 20, 132–134.Google Scholar
Wilson, G.A. & Rannala, B. (2003) Bayesian inference of recent migration rates using multilocus genotypes. Genetics 163, 1177–1191.Google Scholar
Yang, X.M., Sun, J.T., Xue, X.F., Li, J.B. & Hong, X.Y. (2012) Invasion genetics of the western flower thrips in China: evidence for genetic bottleneck, hybridization and bridgehead effect. PLoS ONE 7, e34567.Google Scholar
Zhang, D.X. (2004) Lepidopteran microsatellite DNA: redundant but promising. Trends in Ecology & Evolution 19, 507–509.Google Scholar
Zhang, J.J., Yang, J., Li, Y.C., Liu, N. & Zhang, R.Z. (2013) Genetic relationships of introduced Colorado potato beetle Leptinotarsa decemlineata populations in Xinjiang, China. Insect Science 20, 643–654.Google Scholar
Zhu, Y.B., Ma, J.F., Dong, L., Li, L.T., Jiang, J.Y., Li, Z.H., Dong, Z.P., Dong, J.G. & Wang, Q.Y. (2012) Analysis of genetic polymorphism of Athetis lepigone (Lepidoptera: Noctuidae) population from China base on mtDNA COI gene sequence. Acta Entomologica Sinica 55, 457–465.Google Scholar
Supplementary material: Image

Zhu et al supplementary material

Zhu et al supplementary material 1

Download Zhu et al supplementary material(Image)
Image 119.5 KB
Supplementary material: Image

Zhu et al supplementary material

Zhu et al supplementary material 2

Download Zhu et al supplementary material(Image)
Image 121.5 KB
Supplementary material: File

Zhu et al supplementary material

Zhu et al supplementary material 3

Download Zhu et al supplementary material(File)
File 16.6 KB