Volume 8, Issue 15 (6-2017)                   Res Anim Prod 2017, 8(15): 161-170 | Back to browse issues page


XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

(2017). Detecting of Functional Short Non-Coding RNAs using Bioinformatics Methods in Sheep and Goat . Res Anim Prod. 8(15), 161-170. doi:10.29252/rap.8.15.161
URL: http://rap.sanru.ac.ir/article-1-767-en.html
Abstract:   (4992 Views)

MicroRNAs (miRNAs) are small non-coding RNAs that have functional roles in post-transcriptional modification. They regulate gene expression by an RNA interfering pathway through cleavage or inhibition of the translation of target mRNA. Numerous miRNAs have been described for their important functions in developmental processes in numerous animals, but there is limited information about sheep and goat miRNAs. Sheep and goat are ideal model organisms for biological and comparative genomics studies in ruminants. Identification of miRNAs is crucial to understanding their biological mechanism. Computational identification approaches can supplement experimental approaches to quickly identify ncRNAs in novel genomes, chiefly miRNAs that are transcribed under particular conditions in specific cell types. Currently, machine learning approaches have been employed to predict novel miRNAs. In this study, we present a new SVM-based classifier. It demonstrated high accuracy, balanced sensitivity and specificity for the miRNA datasets, thus representing an ideal tool for miRNA identification from transcriptome sequencing data. In this research, we generated an optimized feature subset including 20 features using a support vector machine, and we developed a c # program to compute the features in the training sequences. In this study, an intelligent SVM model with RBF kernel and the SMO learning algorithm was the best classifier for predicting microRNA genes in sheep and goat. Sensitivity and specificity of this model were 88% and 85% respectively. Then, expressed sequence tag (EST) analysis was performed for finding sheep and goat mature miRNAs. Chromosome 1 was scanned for finding miRNA potential region. In sheep 23 miRNA genes and, in goat 15 miRNAs had been discovered by homology searching. Our finding demonstrate that the Sheep and goat miRNA sequences can be supplied useful information for investigating biological roles of miRNAs in ruminants.

Full-Text [PDF 471 kb]   (4706 Downloads)    
Type of Study: Research | Subject: Special
Received: 2017/06/17 | Accepted: 2017/06/17

References
1. Ambros, V. 2004. The functions of animal micrornas. Nature, 431: 350-355. [DOI:10.1038/nature02871]
2. Ambros, V., B. Bartel, D.P. Bartel, C.B. Burge, J.C. Carrington, X. Chen, G. Dreyfuss, S.R. Eddy, S. Griffiths-Jones and M. Marshall. 2003. A uniform system for microrna annotation. Rna, 9: 277-279. [DOI:10.1261/rna.2183803]
3. Barozai, M.Y.K., I.A. Baloch and M. Din. 2011a. Computational identification of micrornas and their targets in two species of evergreen spruce tree (Picea). Waset, 75: 413-418.
4. Barozai, M.Y.K., I.A. Baloch and M. Din. 2012. Identification of micrornas and their targets in helianthus. Molecular Biology Reports, 39: 2523-2532. [DOI:10.1007/s11033-011-1004-y]
5. Barozai, M.Y.K., M. Din and I.A. Baloch. 2011b. Identification of micrornas in ecological model plant mimulus. Journal of Biophysical Chemistry, 2: 322-331. [DOI:10.4236/jbpc.2011.23037]
6. Bartel, D.P. 2004. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116: 281-297. [DOI:10.1016/S0092-8674(04)00045-5]
7. Berezikov, E., G. Van Tetering, M. Verheul, L. Van Laake, J. Vos, R. Verloop, M. Van de Wetering, V. Guryev, S. Takada, A.J. Van Zonneveld, H. Mano, R. Plasterk and E. Cuppen. 2006. Many novel mammalian microrna candidates identiwed by extensive clon-ing and rake analysis. Genome Research, 16: 1289-1298. [DOI:10.1101/gr.5159906]
8. Burnside, J., M. Ouyang, A. Anderson, E. Bernberg, C. Lu, B.C. Meyers, P.J. Green, M. Markis, G. Isaacs and E. Huang. 2008. Deep sequencing of chicken micrornas. BMC Genomics, 9: 185. [DOI:10.1186/1471-2164-9-185]
9. Chen, C.Z., L. Li, H.F. Lodish and D.P. Bartel. 2004. MicroRNAs modulate hematopoietic lineage differentiation. Science, 303: 83-86. [DOI:10.1126/science.1091903]
10. Clop, A., F. Marcq, H. Takeda, D. Pirottin, X. Tordoir, B. Bibé, J. Bouix, F. Caiment, J.M. Elsen and F. Eychenne. 2006. A mutation creating a potential illegitimate microRNA target site in the myostatin Gene Affects Muscularity in Sheep. Nature Genetics, 38: 813-818. [DOI:10.1038/ng1810]
11. Coutinho, L.L., L.K. Matukumalli, T.S. Sonstegard, C.P. Van Tassell, L.C. Gasbarre, A.V. Capuco and T.P.L Smith. 2007. Discovery and profiling of bovine micrornas from immune-related and embryonic tissues. Physiological Genomics, 29: 35-43. [DOI:10.1152/physiolgenomics.00081.2006]
12. Crooks, G.E., G. Hon, J.M. Chandonia and S.E. Brenner. 2004. WebLogo: A sequence logo generator. Genome Research, 14: 1188-1190. [DOI:10.1101/gr.849004]
13. Eddy, S.R. 2004. How do rna folding algorithms work? nature biotechnology, 22: 1457-1458. [DOI:10.1038/nbt1104-1457]
14. Enright, A.J., B. John, U. Gaul, T. Tuschl, C. Sander and D.S Marks. 2004. MicroRNA targets in drosophila. Genome Biology, 5: R1. [DOI:10.1186/gb-2003-5-1-r1]
15. Filipowicz, W., S.N. Bhattacharyya and N. Sonenberg. 2008. Mechanisms of post-transcriptional regulation by micrornas: are the answers in sight? Nature Reviews Genetics, 9: 102-114. [DOI:10.1038/nrg2290]
16. Friedman, R.C., K.K.H. Farh, C.B. Burge and D.P. Bartel. 2009. Most mammalian mrnas are conserved targets of micrornas. Genome Research, 19: 92-105. [DOI:10.1101/gr.082701.108]
17. Gaidatzis, D., E. Van Nimwegen, J. Hausser and M. Zavolan. 2007. Inference of mirna targets using evolutionary conservation and pathway analysis. BMC Bioinformatics, 8: 69. [DOI:10.1186/1471-2105-8-69]
18. Glazov, E.A., P.A. Cottee, W.C. Barris, R.J. Moore, B.P. Dalrymple and M.L. Tizard. 2008. A microrna catalog of the developing chicken embryo identified by a deep sequencing approach. Genome Research, 18: 957-964. [DOI:10.1101/gr.074740.107]
19. Glazov, E.A., K. Kongsuwan, W. Assavalapsakul, P.F. Horwood, N. Mitter and T.J Mahony. 2009. Repertoire of bovine mirna and mirna-like small regulatory rnas expressed upon viral infection. PLoS One, 4: e6349. [DOI:10.1371/journal.pone.0006349]
20. Hall, T.A. 1999. BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. In: Nucleic Acids Symposium Series, 41: 95-98.
21. Hofacker, I.L. 2003. Vienna rna secondary structure server. Nucleic Acids Research, 31: 3429-3431. [DOI:10.1093/nar/gkg599]
22. Hossain, M.M., N. Ghanem, M. Hoelker, F. Rings, C. Phatsara, E. Tholen, K. Schellander and D. Tesfaye. 2009. Identification and characterization of mirnas expressed in the bovine ovary. BMC Genomics, 10: 443. [DOI:10.1186/1471-2164-10-443]
23. Huang, J., Z. Ju, Q. Li, Q. Hou, C. Wang, J. Li, R. Li, L. Wang, T. Sun and S. Hang. 2011. Solexa sequencing of novel and differentially expressed micrornas in testicular and ovarian tissues in holstein cattle. International Journal of Biological Sciences, 7: 1016-1020. [DOI:10.7150/ijbs.7.1016]
24. Huang, T.H., B. Fan, M.F. Rothschild, Z.L. Hu, K. Li and S.H. Zhao. 2007. MiRFinder: an improved approach and software implementation for genome-wide fast microrna precursor scans. BMC Bioinformatics, 8: 341-350. [DOI:10.1186/1471-2105-8-341]
25. Huang, Y., Q. Zou, S.M. Tang, L.G. Wang and X.J. Shen. 2010. Computational identification and characteristics of novel MicroRNAs from the Silkworm (Bombyx mori L.). Molecular Biology Reports, 37: 3171-3176. [DOI:10.1007/s11033-009-9897-4]
26. Kidner, C.A. and R.A. Martienssen. 2005. The developmental role of microrna in plants. Current Opinion in Plant Biology 8: 38-44. [DOI:10.1016/j.pbi.2004.11.008]
27. Kloosterman, W.P. and R.H.A. Plasterk. 2006. The diverse functions of micrornas in animal development and disease. Developmental Cell, 11: 441-450. [DOI:10.1016/j.devcel.2006.09.009]
28. Krek, A., D. Grün, M.N. Poy, R. Wolf, L. Rosenberg, E.J. Epstein, P. MacMenamin, I. da Piedade, K. C. Gunsalus and M. Stoffel. 2005. Combinatorial microrna target predictions. Nature Genetics, 37: 495-500. [DOI:10.1038/ng1536]
29. Krützfeldt, J., N. Rajewsky, R. Braich, K.G. Rajeev, T. Tuschl, M. Manoharan and M. Stoffel. 2005. Silencing of MicroRNAs in vivo with 'antagomirs'. Nature, 438: 685-689. [DOI:10.1038/nature04303]
30. Lagos-Quintana, M., R. Rauhut, W. Lendeckel and T. Tuschl. 2001. Identification of novel genes coding for small expressed RNAs. Science Signalling, 294: 853-858. [DOI:10.1126/science.1064921]
31. Lagos-Quintana, M., R. Rauhut, A. Yalcin, J. Meyer, W. Lendeckel and T. Tuschl. 2002. Identification of tissue-specific MicroRNAs from mouse. Current Biology, 12: 735-739. [DOI:10.1016/S0960-9822(02)00809-6]
32. Larkin, M., G. Blackshields, N. Brown, R. Chenna, P. McGettigan, H. McWilliam, F. Valentin, I. Wallace, A. Wilm and R. Lopez. 2007. Clustal W and Clustal X Version 2.0. Bioinformatics, 23: 2947-2948. [DOI:10.1093/bioinformatics/btm404]
33. Lau, N.C., L.P. Lim, E.G. Weinstein and D.P. Bartel. 2001. An abundant class of tiny rnas with probable regulatory roles in caenorhabditis elegans. Science Signalling, 294: 858-867. [DOI:10.1126/science.1065062]
34. Lee, R., R. Feinbaum, and V. Ambros. 2004a. A short history of a short RNA. Cell, 116: 89-100. [DOI:10.1016/S0092-8674(04)00035-2]
35. Lee, R. C., R.L. Feinbaum and V. Ambros. 1993. The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to Lin-14. Cell, 75: 843-854. [DOI:10.1016/0092-8674(93)90529-Y]
36. Lee, Y., C. Ahn, J. Han, H. Choi, J. Kim, J. Yim, J. Lee, P. Provost, O. Radmark and S. Kim. 2003. The nuclear RNase III drosha initiates MicroRNA Processing. Nature, 425: 415-419. [DOI:10.1038/nature01957]
37. Lee, Y., M. Kim, J. Han, K.H. Yeom, S. Lee, S.H. Baek and V. N Kim. 2004b. MicroRNA Genes Are Transcribed by RNA Polymerase II. EMBO J, 23: 4051-4060. [DOI:10.1038/sj.emboj.7600385]
38. Lewis, B. 2003. Prediction of Mammalian MicroRNA targets., et al. 115, 2003, Cell, 115: 787-798. [DOI:10.1016/S0092-8674(03)01018-3]
39. Ling, Y.H., J.P. Ding, X.D. Zhang, L.J. Wang, Y.H. Zhang, Y.S Li, Z.J. Zhang and X.R. Zhang. 2013. Characterization of MicroRNAs from goat (Capra Hircus) by solexa deep-sequencing technology. Genet Molecular Research, 12: 1951-1961. [DOI:10.4238/2013.June.13.4]
40. Long, J.E. and H.X. Chen. 2009. Identification and Characteristics of cattle MicroRNAs by homology searching and small RNA cloning. Biochemical Genetics, 47: 329-343. [DOI:10.1007/s10528-009-9234-6]
41. Mathews, D.H., J. Sabina, M. Zuker and D.H. Turner. 1999. Expanded sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure. Journal of Molecular Biology, 288: 911-940. [DOI:10.1006/jmbi.1999.2700]
42. Nilsen, T.W. 2007. Mechanisms of MicroRNA-Mediated Gene Regulation in Animal Cells. Trends Genet, 23: 243-249. [DOI:10.1016/j.tig.2007.02.011]
43. Pillai, R.S., S.N. Bhattacharyya and W. Filipowicz. 2007. Repression of protein synthesis by mirnas: how many mechanisms? Trends in Cell Biology, 17: 118-126. [DOI:10.1016/j.tcb.2006.12.007]
44. Plasterk, R.H.A. 2006. Micro RNAs in Animal Development. Cell, 124: 877-881. [DOI:10.1016/j.cell.2006.02.030]
45. Place R.F., L.C. Li, D. Pookot, E.J. Noonan and R. Dahiya. 2008. MicroRNA-373 induces expression of genes with complementary promoter sequences. Proceedings of the national academy of Sciences of the United States of America, 105: 1608-1613. [DOI:10.1073/pnas.0707594105]
46. Ramachandra, R.K., M. Salem, S. Gahr, C.E. Rexroad and J. Yao. 2008. Cloning and characterization of MicroRNAs from rainbow trout (oncorhynchus mykiss): their expression during early embryonic development. BMC Developmental Biology, 8: 41-50. [DOI:10.1186/1471-213X-8-41]
47. Rehmsmeier, M., P. Steffen, M. Hochsmann and R. Giegerich. 2004. Fast and effective prediction of MicroRNA/Target Duplexes. RNA, 10: 1507-1517. [DOI:10.1261/rna.5248604]
48. Sheng, X., X. Song, Y. Yu, L. Niu, S. Li, H. Li, C. Wei, T. Liu, L. Zhang and L. Du. 2011. Characterization of MicroRNAs from Sheep (Ovis Aries) using computational and experimental analyses. Molecular Biology Reports, 38: 3161-3171. [DOI:10.1007/s11033-010-9987-3]
49. Singh, J. and J. Nagaraju. 2008. In silico prediction and characterization of MicroRNAs from Red flour beetle (Tribolium Castaneum). Insect Molecular Biology, 17: 427-436. [DOI:10.1111/j.1365-2583.2008.00816.x]
50. Sinha, S., T. Vasulu and R.K. De. 2009. Performance and evaluation of MicroRNA gene identification tools. Journal of Proteomics & Bioinformatics, 2: 336-343. [DOI:10.4172/jpb.1000093]
51. Strozzi, F., R. Mazza, R. Malinverni and J. Williams. 2009. Annotation of 390 bovine MiRNA genes by sequence similarity with other species. Animal Genetics, 40: 125. [DOI:10.1111/j.1365-2052.2008.01780.x]
52. Tesfaye, D., D. Worku, F. Rings, C. Phatsara, E. Tholen, K. Schellander and M. Hoelker. 2009. Identification and expression profiling of micrornas during bovine oocyte maturation using heterologous approach. Molecular Reproduction and Development, 76: 665-677. [DOI:10.1002/mrd.21005]
53. Wei, Y., S. Chen, P. Yang, Z. Ma and L. Kang. 2009 Characterization and comparative profiling of the small rna transcriptomes in two phases of locust. Genome Biology, 10: R6. [DOI:10.1186/gb-2009-10-1-r6]
54. Wightman, B., I. Ha and G. Ruvkun. 1993. Posttranscriptional Regulation of the Heterochronic Gene Lin-14 by Lin-4 Mediates Temporal Pattern Formation in C. Elegans. Cell, 75: 855-862. [DOI:10.1016/0092-8674(93)90530-4]
55. Winter, J., S. Jung, S. Keller, R.I. Gregory and S. Diederichs. 2009. Many roads to maturity: microrna biogenesis pathways and their regulation. Nature cell Biology, 11: 228-234. [DOI:10.1038/ncb0309-228]
56. Yekta, S., I. Shih and D.P. Bartel. 2004. MicroRNA-Directed cleavage of HOXB8 mRNA. Science Signalling, 304: 594-610. [DOI:10.1126/science.1097434]
57. Yoon, S. and G.D. Micheli. 2006. Computational Identification of MicroRNAs and Their Targets. Birth Defects Research Part C: Embryo Today: Reviews, 78: 118-128. [DOI:10.1002/bdrc.20067]
58. Yousef, M., L. Showe and M. Showe. 2009. A study of MicroRNAs in silico and in vivo: bioinformatics approaches to MicroRNA discovery and target identification. FEBS Journal, 276: 2150-2156. [DOI:10.1111/j.1742-4658.2009.06933.x]
59. Zhang, B., X. Pan, Q. Wang, G.P. Cobb and T.A. Anderson. 2006. Computational identification of MicroRNAs and Their Targets. Computational Biology and Chemistry, 30: 395-407. [DOI:10.1016/j.compbiolchem.2006.08.006]
60. Zhang, Y., J. Wang, S. Huang, X. Zhu, J. Liu. N. Yang, D. Song, R. Wu and G. Skogerbo. 2009. Systematic identification and characterization of chicken (Gallus Gallus) ncRNAs. Nucleic Acids Research, 37: 6562-6574. [DOI:10.1093/nar/gkp704]
61. Zuker, M. 2003. Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Research, 31: 3406-3415. [DOI:10.1093/nar/gkg595]

Add your comments about this article : Your username or Email:
CAPTCHA

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2025 CC BY-NC 4.0 | Research On Animal Production

Designed & Developed by : Yektaweb