Skip to main content
SpringerLink
Log in

Insilco Prediction and Characterization of microRNAs from Oncopeltus fasciatus (Hemiptera: Lygaeidae) Genome

  • Published:
Applied Biochemistry and Biotechnology Aims and scope Submit manuscript

Abstract

For studies on functional genomics, small RNAs, especially microRNAs (miRNAs), have emerged as a hot topic due to their importance in cellular and developmental processes. Identification of insect miRNAs largely depends on the availability of genomic sequences in the public domain. The large milkweed bug, Oncopeltus fasciatus (Dallas) is a hemimetabolous insect which has become a model hemipteran system for various molecular studies. In this study, we identified 96 candidate mature miRNAs from O. fasciatus genome using a blast search with the previously reported animal miRNAs. The secondary structure of predicted miRNA sequences was determined online using “mfold” web server and verified by calculating the minimal free energy index (MFEI). Six miRNAs let-7e, miR-133c, miR-219b, mir-466d, mir-669f, and mir-669l are reported for the first time in Insecta. Comparison of O. fasciatus mir-2 and mir-71 family clusters to those of diverse insect species showed that they are highly conserved. The phylogenetic analysis of miRNAs revealed the evolutionary relationship of conserved miRNAs of O. fasciatus with other insect species. Using a classical rule-based algorithm method, we predicted the possible targets of the new miRNAs. Our study not only identified the list of miRNAs in O. fasciatus but also provides a basic platform for developing novel pest management strategies based on artificial miRNAs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Asgari, S. (2013). MicroRNA functions in insects. Insect Biochemistry and Molecular Biology, 43, 388–397.

    Article  CAS  Google Scholar 

  2. Lagos-Quintana, M., Rauhut, R., Lendeckel, W., & Tuschl, T. (2001). Identification of novel genes coding for small expressed RNAs. Science, 294, 853–858.

    Article  CAS  Google Scholar 

  3. Agrawal, N., Sachdev, B., Rodrigues, J., Sree, K. S., & Bhatnagar, R. K. (2013). Development associated profiling of chitinase and microRNA of Helicoverpa armigera identified chitinase repressive microRNA. Scientific Reports, 3, 2292.

    Google Scholar 

  4. Zeng, Y., & Cullen, B. R. (2005). Efficient processing of primary microRNA hairpins by Drosha requires flanking non-structured RNA sequences. Journal of Biological Chemistry, 280, 27595–27603.

    Article  CAS  Google Scholar 

  5. Winter, J., & Diederichs, S. (2011). Argonaute proteins regulate microRNA stability: increased microRNA abundance by Argonaute proteins is due to microRNA stabilization. RNA Biology, 8, 1149–1157.

    Article  CAS  Google Scholar 

  6. Lee, I., Ajay, S. S., Yook, J. I., Kim, H. S., Hong, S. H., Kim, N. H., Dhanasekaran, S. M., Chinnaiyan, A. M., & Athey, B. D. (2009). New class of microRNA targets containing simultaneous 5′-UTR and 3′-UTR interaction sites. Genome Research, 19, 1175–1183.

    Article  CAS  Google Scholar 

  7. Jagadeeswaran, G., Zheng, Y., Sumathipala, N., Jiang, H., Arrese, E. L., Soulages, J. L., Zhang, W., & Sunkar, R. (2010). Deep sequencing of small RNA libraries reveals dynamic regulation of conserved and novel microRNAs and microRNA-stars during silkworm development. BMC Genomics, 11, 52.

    Article  Google Scholar 

  8. Alves e Silva, T. L., Vasconcellos, L. R. C., Lopes, A. H., & Souto-Padrón, T. (2013). The immune response of hemocytes of the insect Oncopeltus fasciatus against the flagellate Phytomonas serpens. PLoS ONE, 8, e72076.

    Article  CAS  Google Scholar 

  9. Liu, J., Lemonds, T. R., & Popadic, A. (2014). The genetic control of aposematic black pigmentation in hemimetabolous insects: insights from Oncopeltus fasciatus. Evolution & Development, 16, 270–277.

    Article  CAS  Google Scholar 

  10. Ewen-Campen, B., Shaner, N., Panfilio, K. A., Suzuki, Y., Roth, S., & Extavour, C. G. (2011). The maternal and early embryonic transcriptome of the large milkweed bug Oncopeltus fasciatus. BMC Genomics, 12, 61.

    Article  CAS  Google Scholar 

  11. Qu, J., Richards, S., Bandaranaike, D., Bellair, M., Blankenburg, K., Chao, H., Dinh, H., Doddapaneni, H., Downs, B., Dugan-Rocha, S., Elkadiri, S., Gnanaolivu, R., Hernandez, B., Javaid, M., Jayaseelan, J. C., Lee, S., Li, M., Ming, W., Munidasa, M., Muniz, J., Nguyen, L., Ongeri, F., Osuji, N., Pu, L. L., Puazo, M., Qu, C., Quiroz, J., Raj, R., Weissenberger, G., Xin, Y., Zou, X., Han, Y., Worley, K., Muzny, D., & Gibbs, R. (2014). NCBI-BioProject: PRJNA229125, whole genome assembly of oncopeltus fasciatus using multiple sequencing technologies (http://www.ncbi.nlm.nih.gov/bioproject/229125).

  12. Kozomara, A., & Griffiths-Jones, S. (2014). miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Research, 42, D68–D73.

    Article  CAS  Google Scholar 

  13. Hall, T. A. (1999). BioEdit: a user-friendly biological sequence alignment editor and analysis program for windows 95/98/NT. Nucleic Acids Symposium Series, 41, 95–98.

    CAS  Google Scholar 

  14. Ellango, R., Asokan, R., Mahmood, R., Ramamurthy, V. V., & Krishnakumar, N. K. (2014). Isolation of new microRNAs from the diamondback moth (Lepidoptera: yponomeutidae) genome by a computational method. Florida Entomologist, 97, 877–885.

    Article  CAS  Google Scholar 

  15. Zuker, M. (2003). Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Research, 31, 3406–3415.

    Article  CAS  Google Scholar 

  16. Singh, J., & Nagaraju, J. (2008). Insilco prediction and characterization of microRNAs from red flour beetle (Tribolium castaneum). Insect Molecular Biology, 17, 427–436.

    Article  CAS  Google Scholar 

  17. Ghosh, Z., Chakrabarti, J., & Mallick, B. (2007). miRNomics—the bioinformatics of microRNA genes. Biochemistry Biophysics Research Communication, 363, 6–11.

    Article  CAS  Google Scholar 

  18. Zhang, B. H., Pan, X. P., Cannon, C. H., Cobb, G. P., & Anderson, T. A. (2006). Computational identification of microRNAs and their targets. Computational Biology and Chemistry, 30, 395–407.

    Article  CAS  Google Scholar 

  19. Griffiths-Jones, S., Grocock, R. J., Van Dongen, S., Bateman, A., & Enright, A. J. (2006). miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Research, 34, D140–D144.

    Article  CAS  Google Scholar 

  20. Griffiths-Jones, S. (2004). The microRNA registry. Nucleic Acids Research, 32, D109–D111.

    Article  CAS  Google Scholar 

  21. Tamura, K., Stecher, G., Peterson, D., Filipski, A., & Kumar, S. (2013). MEGA6: molecular evolutionary genetics analysis version 6.0. Molecular Biology and Evolution, 30, 2725–2729.

    Article  CAS  Google Scholar 

  22. Enright, A. J., John, B., Gaul, U., Tuschl, T., Sander, C., & Marks, D. S. (2003). MicroRNA targets in Drosophila. Genome Biology, 5, R1.

    Article  Google Scholar 

  23. Rehmsmeier, M., Steffen, P., Hoechsmann, M., & Giegerich, R. (2004). Fast and effective prediction of microRNA/target duplexes RNA. RNA, 10, 1507–1517.

    Article  CAS  Google Scholar 

  24. Legeai, F., Rizk, G., Walsh, T., Edwards, O., Gordon, K., Lavenier, D., Leterme, N., Mereau, A., Nicolas, J., Tagu, D., & Jaubert-Possamai, S. (2010). Bioinformatic prediction, deep sequencing of microRNAs and expression analysis during phenotypic plasticity in the pea aphid, Acyrthosiphon pisum. BMC Genomics, 11, 281.

    Article  Google Scholar 

  25. Lau, N. C., Lim, L. P., Weinstein, E. G., & Bartel, D. P. (2001). An abundant class of tiny RNAs with probable regulatory roles in Caenorhabditis elegans. Science, 294, 858–862.

    Article  CAS  Google Scholar 

  26. Altuvia, Y., Landgraf, P., Lithwick, G., Elefant, N., Pfeffer, S., Aravin, A., Brownstein, M. J., Tuschl, T., & Margalit, H. (2005). Clustering and conservation patterns of human microRNAs. Nucleic Acids Research, 33, 2697–2706.

    Article  CAS  Google Scholar 

  27. Saini, H. K., Enright, A. J., & Griffiths-Jones, S. (2008). Annotation of mammalian primary microRNAs. BMC Genomics, 9, 564.

    Article  Google Scholar 

  28. Marco, A., Hui, J. H., Ronshaugen, M., & Griffiths-Jones, S. (2010). Functional shifts in insect microRNA evolution. Genome Biology and Evolution, 2, 686–696.

    Google Scholar 

  29. Biryukova, I., Ye, T., & Levashina, E. (2014). Transcriptome-wide analysis of microRNA expression in the malaria mosquito Anopheles gambiae. BMC Genomics, 15, 557.

    Article  Google Scholar 

  30. Shin, C., Nam, J.-W., Farh, K. K.-H., Chiang, H. R., Shkumatava, A., & Bartel, D. P. (2010). Expanding the microRNA targeting code: functional sites with centered pairing. Molecular Cell, 38, 789–802.

    Article  CAS  Google Scholar 

  31. Bartel, D. P. (2009). MicroRNAs: target recognition and regulatory functions. Cell, 23, 215–233.

    Article  Google Scholar 

  32. Rigoutsos, I. (2009). New tricks for animal microRNAs: targeting of amino acid coding regions at conserved and nonconserved sites. Cancer Research, 69, 3245–3248.

    Article  CAS  Google Scholar 

Download references

Acknowledgments

Our sincere thanks are due to the Director, Indian Institute of Horticultural Research, Bengaluru, India, for providing the facilities and encouragement. We gratefully acknowledge the financial support received from the Indian Council of Agricultural Research (ICAR), New Delhi through the XIIth plan Network Project on ORP-on Management of sucking pest on horticultural crops.

Author information

Authors and Affiliations

  1. Division of Biotechnology, Indian Institute of Horticultural Research (IIHR), Bangalore, 560089, KN, India

    R. Ellango & R. Asokan

  2. Division of Entomology, Indian Agricultural Research Institute (IARI), Pusa Campus, 110012, ND, India

    V. V. Ramamurthy

Authors
  1. R. Ellango
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. R. Asokan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. V. V. Ramamurthy
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to R. Ellango or R. Asokan.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Table S1

Oncopeltus fasciatus mature miRNA details. (XLS 47 kb)

Table S2

O. fasciatus precursor miRNA details. (XLS 39 kb)

Table S3

Prediction of possible targets of O. fasciatus miRNA. (XLS 32 kb)

Table S4

Both Miranda and RNA hybrid were used to predict the possible target for six ofa-miRNAs. (XLS 75 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ellango, R., Asokan, R. & Ramamurthy, V.V. Insilco Prediction and Characterization of microRNAs from Oncopeltus fasciatus (Hemiptera: Lygaeidae) Genome. Appl Biochem Biotechnol 179, 1393–1403 (2016). https://doi.org/10.1007/s12010-016-2072-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12010-016-2072-1

Keywords

Search

Navigation