Applied Entomology and Zoology

, Volume 54, Issue 1, pp 141–145 | Cite as

Rapid development and characterization of EST-SSR markers for the honey locust seed beetle, Megabruchidius dorsalis (Coleoptera: Bruchidae), using de novo transcriptome analysis based on next-generation sequencing

  • Kako OhbayashiEmail author
  • Naoko Ishikawa
  • Yoshikuni Hodoki
  • Yasukazu Okada
  • Shin-ichi Nakano
  • Motomi Ito
  • Masakazu Shimada
Technical Note


We developed 10 novel simple sequence repeat markers from expressed sequence tags for the honey locust seed beetle, Megabruchidius dorsalis Fåhraeus 1839 (Coleoptera: Bruchidae, using de novo transcriptome analysis based on next-generation sequencing. In a M. dorsalis Harataima (Kanagawa-pref.) population, the number of alleles per locus ranged from 2 to 6, with an average of 4.0. Observed and expected heterozygosities ranged from 0.13 to 0.72 and 0.17 to 0.72, respectively. We initially developed 11 novel markers, but one was eliminated because it showed significant linkage disequilibrium with another locus after Bonferroni correction. To check the applicability of the remaining 10 markers, we used them to analyze two additional geographic populations (Yashima, Akita-pref., and Kameoka, Kyoto-pref.). Mean numbers of alleles per locus in the Yashima and Kameoka populations were 2.6 and 2.9, respectively, with corresponding mean observed heterozygosities of 0.36 and 0.52. These results based on the two additional populations confirm that our developed markers worked efficiently. The simple sequence repeat markers developed from expressed sequence tags in the present study should, therefore, be useful for explicating the population genetic structure of M. dorsalis and for future paternal analyses.


EST-SSR marker A honey locust seed beetle Genetic structure Paternal analysis 



We acknowledge Dr N Nakahama (The University of Tokyo) for valuable comments and Drs H Kurota and K Takakura for sampling points. This research is partly supported by JSPS KAKENHI Grant Numbers 17H04612 to MS and 18H04815, 17H05938, 17K19381 to YO and by Joint Usage/Research Grant of Center for Ecological Research (2017jurc-cer04, 2018jurc-cer04), Kyoto University to MS.


  1. Bai XD, Zhang W, Orantes L, Jun TH, Mittapalli O, Mian MAR, Michel AP (2010) Combining next-generation sequencing strategies for rapid molecular resource development from an invasive aphid species, Aphis glycines. Plos One 5:e11370CrossRefGoogle Scholar
  2. Blacket MJ, Robin C, Good RT, Lee SF, Miller AD (2012) Universal primers for fluorescent labelling of PCR fragments-an efficient and cost-effective approach to genotyping by fluorescence. Mol Ecol Resour 12:456–463CrossRefGoogle Scholar
  3. Brownstein MJ, Carpten JD, Smith JR (1996) Modulation of non-templated nucleotide addition by Taq DNA polymerase: primer modifications that facilitate genotyping. Biotechniques 20:1004–1010CrossRefGoogle Scholar
  4. Cook N, Aziz N, Hedley PE, Morris J, Milne L, Karley AJ, Hubbard SF, Russell JR (2011) Transcriptome sequencing of an ecologically important graminivorous sawfly: a resource for marker development. Conserv Genet Resour 3:789–795CrossRefGoogle Scholar
  5. Duan CX, Li DD, Sun SL, Wang XM, Zhu ZD (2014) Rapid development of microsatellite markers for Callosobruchus chinensis using illumina paired-end sequencing. Plos One 9:e95458CrossRefGoogle Scholar
  6. Duan XL, Wang K, Su S, Tian RZ, Li YT, Chen MH (2017) De novo transcriptome analysis and microsatellite marker development for population genetic study of a serious insect pest, Rhopalosiphum padi (L.) (Hemiptera: Aphididae). Plos One 12:e0172513CrossRefGoogle Scholar
  7. Faircloth BC (2008) MSATCOMMANDER: detection of microsatellite repeat arrays and automated, locus-specific primer design. Mol Ecol Resour 8:92–94CrossRefGoogle Scholar
  8. Fritzsche K, Arnqvist G (2015) The effects of male phenotypic condition on reproductive output in a sex role-reversed beetle. Anim Behav 102:209–215CrossRefGoogle Scholar
  9. Furaov VN, Nazarenko VYu (2015) Invasive species Megabruchidius dorsalis (Coleoptera, Chrysomelidae, Bruchinae)- a new record in the Fauna of Ukraine. Vestnik Zoologii 49:286Google Scholar
  10. Ishikawa N, Sakaguchi S, Ito M (2016) Development and characterization of SSR markers for Aster savatieri (ASTERACEAE). Appl Plant Sci 4:1500143CrossRefGoogle Scholar
  11. Kim H, Rodriguez-Saona C, Kwon DH, Park S, Kang TJ, Kim SJ, Hong KJ, Lee HS (2015) Development and characterization of 12 microsatellite loci from the blueberry gall midge Dasineura oxycoccana (Diptera: Cecidomyiidae). Appl Entomol Zool 50:415–418CrossRefGoogle Scholar
  12. Korotyaev BA (2016) First records of an east asian seed beetle Megabruchidius dorsalis fåhraeus (Coleoptera, Bruchidae) from Germany and the black sea coast of the crimea and caucasus. Entomol Rev 96:460–461CrossRefGoogle Scholar
  13. Kurota H, Shimada M (2001) Photoperiod- and temperature-dependent induction of larval diapause in a multivoltine bruchid, Bruchidius dorsalis. Entomol Exp Appl 99:361–369CrossRefGoogle Scholar
  14. Loope KJ (2015) Queen killing is linked to high worker–worker relatedness in a social wasp. Curr Biol 25:2976–2979CrossRefGoogle Scholar
  15. Morimoto K (1990) A synopsis of the Bruchid fauna of Japan. In: Fujii K, Gatehouse AMR, Johnson CD, Mitchel R, Yoshida T (eds) Bruchids and legumes: economics, ecology and coevolution. Springer, Dordrecht, pp 131–140CrossRefGoogle Scholar
  16. Parthiban S, Govindaraj P, Senthilkumar S (2018) Comparison of relative efficiency of genomic SSR and EST-SSR markers in estimating genetic diversity in sugarcane. 3 Biotech 8:144CrossRefGoogle Scholar
  17. Peakall R, Smouse PE (2012) GenAlEx 6.5: genetic analysis in excel. Population genetic software for teaching and research-an update. Bioinformatics 28:2537–2539CrossRefGoogle Scholar
  18. Pinto LR, Oliveira KM, Marconi T, Garcia AAF, Ulian EC, De Souza AP (2006) Characterization of novel sugarcane expressed sequence tag microsatellites and their comparison with genomic SSRs. Plant Breed 125:378–384CrossRefGoogle Scholar
  19. Raymond M, Rousset F (1995) GENEPOP (version-1.2)—population-genetics software for exact tests and ecumenicism. J Hered 86:248–249CrossRefGoogle Scholar
  20. Sakaguchi S, Ito M (2014) Development and characterization of EST-SSR markers for the Solidago virgaurea complex (ASTERACEAE) in the Japanese archipelago. Appl Plant Sci 2:1400035CrossRefGoogle Scholar
  21. Schwarz D, Robertson HM, Feder JL, Varala K, Hudson ME, Ragland GJ, Hahn DA, Berlocher SH (2009) Sympatric ecological speciation meets pyrosequencing: sampling the transcriptome of the apple maggot Rhagoletis pomonella. Bmc Genomics 10:633CrossRefGoogle Scholar
  22. Shimada M, Kurota H, Toquenaga Y (2001) Regular distribution of larvae and resource monopolization in the seed beetle Bruchidius dorsalis infesting seeds of the Japanese honey locust Gleditsia japonica. Popul Ecol 43:245–252CrossRefGoogle Scholar
  23. Takakura K (1999) Active female courtship behaviour and male nutritional contribution to female fecundity in Bruchidius dorsalis (Fahraeus) (Coleoptera: Bruchidae). Res Popul Ecol 41:269–273CrossRefGoogle Scholar
  24. Temreshev II, Valiyeva BG (2016) Megabruchidius dorsalis Fahreus, 1839 invasive species in the fauna of seed-beetles (Coleoptera, Chrysomelidae, Bruchinae) of Kazakhstan. Euroasian Entomol J 15:139–142Google Scholar
  25. Untergasser A, Nijveen H, Rao X, Bisseling T, Geurts R, Leunissen JAM (2007) Primer3Plus, an enhanced web interface to primer3. Nucleic Acids Res 35:W71–W74CrossRefGoogle Scholar
  26. Van Oosterhout C, Hutchinson WF, Wills DPM, Shipley P (2004) MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data. Mol Ecol Notes 4:535–538CrossRefGoogle Scholar

Copyright information

© The Japanese Society of Applied Entomology and Zoology 2019

Authors and Affiliations

  1. 1.Center for Ecological ResearchKyoto UniversityOtsuJapan
  2. 2.Department of General System Studies, Graduate School of Arts and ScienceThe University of TokyoTokyoJapan
  3. 3.Department of Biological SciencesTokyo Metropolitan UniversityTokyoJapan

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