Hostname: page-component-cd9895bd7-q99xh Total loading time: 0 Render date: 2024-12-27T09:18:52.908Z Has data issue: false hasContentIssue false
  • English
  • Français

Characterization of novel microsatellite markers for Hyphantria cunea and implications for other Lepidoptera

Published online by Cambridge University Press:  16 March 2015

L.J. Cao ,
J.B. Wen ,
S.J. Wei ,
J. Liu ,
F. Yang  and
M. Chen
L.J. Cao
Affiliation:
Beijing Key Laboratory for Forest Pest Control, College of Forestry, Beijing Forestry University, Beijing 100083, China
J.B. Wen
Affiliation:
Beijing Key Laboratory for Forest Pest Control, College of Forestry, Beijing Forestry University, Beijing 100083, China
S.J. Wei
Affiliation:
Institute of Plant and Environmental Protection, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
J. Liu
Affiliation:
Beijing Key Laboratory for Forest Pest Control, College of Forestry, Beijing Forestry University, Beijing 100083, China
F. Yang
Affiliation:
Beijing Key Laboratory for Forest Pest Control, College of Forestry, Beijing Forestry University, Beijing 100083, China
M. Chen*
Affiliation:
Beijing Key Laboratory for Forest Pest Control, College of Forestry, Beijing Forestry University, Beijing 100083, China
*
*Author for correspondence Phone/Fax: +86-010-6233-7731 E-mail: minch@bjfu.edu.cn
Get access Rights & Permissions [Opens in a new window]

Abstract

This is the first report of microsatellite markers (simple sequence repeats, SSR) for fall webworm, Hyphantria cunea (Drury) (Lepidoptera: Arctiidae), an important quarantine pest in some European and Asian countries. Here, we developed 48 microsatellite markers for H. cunea from SSR enrichment libraries. Sequences isolated from libraries were sorted into four categories and analyzed. Our results suggest that sequences classified as Grouped should not be used for microsatellite primer design. The genetic diversity of microsatellite loci was assessed in 72 individuals from three populations. The number of alleles per locus ranged from 2 to 5 with an average of 3. The observed and expected heterozygosities of loci ranged from 0 to 0.958 and 0 to 0.773, respectively. A total of 18 out of 153 locus/population combinations deviated significantly from Hardy–Weinberg equilibrium. Moreover, significant linkage disequilibrium was detected in one pair of loci (1275 pairs in total). In the neutral test, two loci were grouped into the candidate category for positive selection and the remainder into the neutral category. In addition, a complex mutation pattern was observed for these loci, and FST performed better than did RST for the estimation of population differentiation in different mutation patterns. The results of the present study can be used for population genetic studies of H. cunea.

Keywords

LepidopteraHyphantria cuneamicrosatellitemutation patternpopulation differentiation
Type
Research Papers
Information
Bulletin of Entomological Research , Volume 105 , Issue 3 , June 2015 , pp. 273 - 284
Check for updates
Copyright
Copyright © Cambridge University Press 2015 

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.)

References

Anderson, T.J., Su, X.Z., Roddam, A. & Day, K.P. (2000) Complex mutations in a high proportion of microsatellite loci from the protozoan parasite Plasmodium falciparum . Molecular Ecology 9, 1599–1608.Google Scholar
Antao, T., Lopes, A., Lopes, R.J., Beja-Pereira, A. & Luikart, G. (2008) LOSITAN: a workbench to detect molecular adaptation based on a Fst-outlier method. BMC Bioinformatics 9, 323.Google Scholar
Arias, R.S., Blanco, C.A., Portilla, M., Snodgrass, G.L. & Scheffler, B.E. (2011) First microsatellites from Spodoptera frugiperda (Lepidoptera: Noctuidae) and their potential use for population genetics. Annals of the Entomological Society of America 104, 576–587.Google Scholar
Ascunce, M.S., Yang, C.C., Oakey, J., Calcaterra, L., Wu, W.J., Shih, C.J., Goudet, J., Ross, K.G. & Shoemaker, D. (2011) Global invasion history of the fire ant Solenopsis invicta . Science 331, 1066–1068.CrossRefGoogle ScholarPubMed
Balloux, F. & Lugon-Moulin, N. (2002) The estimation of population differentiation with microsatellite markers. Molecular Ecology 11, 155–165.CrossRefGoogle ScholarPubMed
Bhargava, A. & Fuentes, F.F. (2010) Mutational dynamics of microsatellites. Molecular Biotechnology 44, 250–266.Google Scholar
Chapuis, M.P. & Estoup, A. (2007) Microsatellite null alleles and estimation of population differentiation. Molecular Biology and Evolution 24, 621–631.CrossRefGoogle ScholarPubMed
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
Dieringer, D. & Schlotterer, C. (2003) Microsatellite analyser (MSA): a platform independent analysis tool for large microsatellite data sets. Molecular Ecology Notes 3, 167–169.Google Scholar
Eisen, J.A. (1999) Mechanistic basis for microsatellite instability. pp. 34–48 in Goldstein, D.B. & Schlötterer, C. (Eds) Microsatellites: Evolution and Applications. Oxford, UK, Oxford University Press.Google Scholar
Endersby, N.M., McKechnie, S.W., Vogel, H., Gahan, L.J., Baxter, S.W., Ridland, P.M. & Weeks, A.R. (2005) Microsatellites isolated from diamondback moth, Plutella xylostella (L.), for studies of dispersal in Australian populations. Molecular Ecology Notes 5, 51–53.Google Scholar
Gomi, T., Muraji, M. & Takeda, M. (2004) Mitochondrial DNA analysis of the introduced fall webworm, showing its shift in life cycle in Japan. Entomological Science 7, 183–188.Google Scholar
Goodman, S.J. (1997) RST Calc: a collection of computer programs for calculating estimates of genetic differentiation from microsatellite data and determining their significance. Molecular Ecology 6, 881–885.CrossRefGoogle Scholar
Hardy, O.J. & Vekemans, X. (2002) SPAGeDi: a versatile computer program to analyse spatial genetic structure at the individual or population levels. Molecular Ecology Notes 2, 618–620.Google Scholar
Hoffman, J.I. & Nichols, H.J. (2011) A novel approach for mining polymorphic microsatellite markers in silico. PLoS ONE 6, e23283.Google Scholar
Ishiguro, N. & Tsuchida, K. (2006) Polymorphic microsatellite loci for the rice stem borer, Chilo suppressalis (Walker) (Lepidoptera: Crambidae). Applied Entomology and Zoology 41, 565–568.Google Scholar
Ji, Y.J., Zhang, D.X., Hewitt, G.M., Kang, L. & Li, D.M. (2003) Polymorphic microsatellite loci for the cotton bollworm Helicoverpa armigera (Lepidoptera: Noctuidae) and some remarks on their isolation. Molecular Ecology Notes 3, 102–104.Google Scholar
Karl, I., Hoffmann, K.H. & Fischer, K. (2010) Food stress sensitivity and flight performance across phosphoglucose isomerase enzyme genotypes in the sooty copper butterfly. Population Ecology 52, 307–315.Google Scholar
Kijas, J., Fowler, J., Garbett, C. & Thomas, M. (1994) Enrichment of microsatellites from the citrus genome using biotinylated oligonucleotide sequences bound to streptavidin-coated magnetic particles. Biotechniques 16, 656–662.Google Scholar
Kohany, O., Gentles, A.J., Hankus, L. & Jurka, J. (2006) Annotation, submission and screening of repetitive elements in Repbase: RepbaseSubmitter and Censor. BMC Bioinformatics 7, 474.CrossRefGoogle ScholarPubMed
Konecny, A., Estoup, A., Duplantier, J.M., Bryja, J., Ba, K., Galan, M., Tatard, C. & Cosson, J.F. (2013) Invasion genetics of the introduced black rat (Rattus rattus) in Senegal, West Africa. Molecular Ecology 22, 286–300.Google Scholar
Malausa, T., Gilles, A., Meglécz, E., Blanquart, H., Duthoy, S., Costedoat, C., Dubut, V., Pech, N., CASTAGNONE-SERENO, P. & Delye, C. (2011) High-throughput microsatellite isolation through 454 GS-FLX Titanium pyrosequencing of enriched DNA libraries. Molecular Ecology Resources 11, 638–644.CrossRefGoogle ScholarPubMed
Matsuoka, Y., Mitchell, S., Kresovich, S., Goodman, M. & Doebley, J. (2002) Microsatellites in Zea–variability, patterns of mutations, and use for evolutionary studies. Theoretical and Applied Genetics 104, 436–450.Google Scholar
Meglécz, E. (2007) MICROFAMILY (version 1): a computer program for detecting flanking-region similarities among different microsatellite loci. Molecular Ecology Notes 7, 18–20.Google Scholar
Meglécz, E., Petenian, F., Danchin, E., D'Acier, A.C., 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
Meglécz, E., Anderson, S., Bourguet, D., Butcher, R., Caldas, A., Cassel-Lundhagen, A., d'Acier, A., Dawson, D., Faure, N. & Fauvelot, C. (2007) Microsatellite flanking region similarities among different loci within insect species. Insect Molecular Biology 16, 175–185.CrossRefGoogle ScholarPubMed
Meglécz, E., Costedoat, C., Dubut, V., Gilles, A., Malausa, T., Pech, N. & Martin, J.F. (2010) QDD: a user-friendly program to select microsatellite markers and design primers from large sequencing projects. Bioinformatics 26, 403–404.Google Scholar
Park, S.D.E. (2001) Trypanotolerance in west African cattle and the population genetic effects of selection. PhD Dissertation, University of Dublin, Ireland.Google Scholar
Perera, O.P., Blanco, C.A., Ballard, L., Silva-Brandao, K.L., Domingues, F.A. & Abel, C.A. (2011) Evaluation of anonymous and expressed sequence tag-derived polymorphic microsatellite markers in the tobacco budworm, Heliothis virescens (Lepidoptera: Noctuidae). Southwestern Entomologist 36, 287–294.Google Scholar
Petenian, F., Meglécz, E., Genson, G., Rasplus, J.Y. & Faure, E. (2005) Isolation and characterization of polymorphic microsatellites in Parnassius apollo and Euphydryas aurinia (Lepidoptera). Molecular Ecology Notes 5, 243–245.Google Scholar
Sambrook, J., Russell, D.W. & Russell, D.W. (2001) Molecular Cloning: a Laboratory Manual (3-volume set). Cold Spring Harbor, New York, USA, Cold Spring Harbor Laboratory Press.Google Scholar
Schuelke, M. (2000) An economic method for the fluorescent labeling of PCR fragments. Nature Biotechnology 18, 233–234.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. & Meglécz, E. (2011) Challenges of microsatellite development in Lepidoptera: Euphydryas aurinia (Nymphalidae) as a case study. European Journal of Entomology 108, 261–266.Google Scholar
Slatkin, M. (1995) A measure of population subdivision based on microsatellite allele frequencies. Genetics 139, 457–462.Google Scholar
Sullivan, G.T. & Ozman-Sullivan, S.K. (2012) Tachinid (Diptera) parasitoids of Hyphantria cunea (Lepidoptera: Arctiidae) in its native North America and in Europe and Asia – a literature review. Entomologica Fennica 23, 181–192.CrossRefGoogle Scholar
Takahashi, J., Kikuchi, T., Ohnishi, H. & Tsuji, K. (2005) Isolation and characterization of 10 microsatellite loci in the Ponerinae ant Pachycondyla luteipes (Hymenoptera: Formicidae). Molecular Ecology Notes 5, 749–751.CrossRefGoogle Scholar
Tamura, K., Peterson, D., Peterson, N., Stecher, G., Nei, M. & Kumar, S. (2011) MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Molecular Biology and Evolution 28, 2731–2739.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.CrossRefGoogle ScholarPubMed
Techen, N., Arias, R.S., Glynn, N.C., Pan, Z., Khan, I.A. & Scheffler, B.E. (2010) Optimized construction of microsatellite-enriched libraries. Molecular Ecology Resources 10, 508–515.Google Scholar
Thompson, J.D., Higgins, D.G. & Gibson, T.J. (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Research 22, 4673–4680.Google Scholar
Tsuchida, K., Saigo, T., Tsujita, S., Takeuchi, K., Ito, N. & Sugiyama, M. (2003) Polymorphic microsatellite loci for the Japanese paper wasp, Polistes chinensis antennalis (Hymenoptera: Vespidae). Molecular Ecology Notes 3, 384–386.CrossRefGoogle 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
Wang, X.W., Trigiano, R.N., Windham, M.T., Devries, R.E., Scheffler, B.E., Rinehart, T.A. & Spiers, J.M. (2007) A simple PCR procedure for discovering microsatellites from small insert libraries. Molecular Ecology Notes 7, 558–561.Google Scholar
Weir, B.S. & Cockerham, C.C. (1984) Estimating F-statistics for the analysis of population structure. Evolution, 1358–1370.Google Scholar
Yang, X.M., Sun, J.T., Xue, X.F., Zhu, W.C. & Hong, X.Y. (2012) Development and characterization of 18 novel EST-SSRs from the western flower thrips, Frankliniella occidentalis (Pergande). International Journal of Molecular Sciences 13, 2863–2876.Google Scholar
Zhang, D.X. (2004) Lepidopteran microsatellite DNA: redundant but promising. Trends in Ecology and Evolution 19, 507–509.Google Scholar
Supplementary material: File

Cao supplementary material

Table S1

Download Cao supplementary material(File)
File 117.8 KB