In silico identification of miRNAs and their target genes and analysis of gene co-expression network in saffron (Crocus sativus L.) stigma

Document Type: Original article

Authors

1 Agroecology Department, College of Agriculture and Natural Resources of Darab, Shiraz University, Iran

2 Crop Production and Plant Breeding Department, College of Agriculture, Shiraz University, Iran

Abstract

As an aromatic and colorful plant of substantive taste, saffron (Crocus sativus L.) owes such properties of matter to growing class of the secondary metabolites derived from the carotenoids, apocarotenoids. Regarding the critical role of microRNAs in secondary metabolic synthesis and the limited number of identified miRNAs in C. sativus, on the other hand, one may see the point how the characterization of miRNAs along with the corresponding target genes in C. sativus might expand our perspectives on the roles of miRNAs in carotenoid/apocarotenoid biosynthetic pathway. A computational analysis was used to identify miRNAs and their targets using EST (Expressed Sequence Tag) library from mature saffron stigmas. Then, a gene co-expression network was constructed to identify genes which are potentially involved in carotenoid/apocarotenoid biosynthetic pathways.  EST analysis led to the identification of two putative miRNAs (miR414 and miR837-5p) along with the corresponding stem-looped precursors. To our knowledge, this is the first report on miR414 and miR837-5p in C. sativus. Co-expression network analysis indicated that miR414 and miR837-5p may play roles in C. sativus metabolic pathways and led to identification of candidate genes including six transcription factors and one protein kinase probably involved in carotenoid/apocarotenoid biosynthetic pathway. Presence of transcription factors, miRNAs and protein kinase in the network indicated multiple layers of regulation in saffron stigma. The candidate genes from this study may help unraveling regulatory networks underlying the carotenoid/apocarotenoid biosynthesis in saffron and designing metabolic engineering for enhanced secondary metabolites.

Keywords


1. Frusciante S, Diretto G, Bruno M, Ferrante P, Pietrella M, Prado-Cabrero A, Robio-Moraga A, Beyer P, Gomez-Gomez L, Al-Babili S, Giuliano G. Novel carotenoid cleavage dioxygenase catalyzes the first dedicated step in saffron crocin biosynthesis. Proc Natl Acad Sci USA 2014;111:12246-12251.

2. Abdullaev FI, Espinosa-Aguirre JJ. Biomedical properties of saffron and its potential use in cancer therapy and chemoprevention trials. Cancer Detect Prev 2004; 28:426-432.

3. Zhang Z, Wang CZ, Wen XD, Shoyama Y, Yuan CS. Role of saffron and its constituents on cancer chemoprevention. Pharm Biol 2013;51:920-924.

4. Gómez-Gómez L, Rubio-Moraga A, Ahrazem O. Understanding carotenoid metabolism in saffron stigmas: unraveling aroma and colour formation. Funct Plant Sci Biotechnol 2010; 4:56-63.

5. D'Agostino N, Pizzichini D, Chiusano ML, Giuliano G. An EST database from saffron stigmas. BMC Plant Biol 2007;7:53.

6. Baba SA, Mohiuddin T, Basu S, Swarankar MK, Malik AH, Wani ZA, Singh AK, Ashraf  N. Comprehensive transcriptome analysis of Crocus sativus for discovery and expression of genes involved in apocarotenoid biosynthesis. BMC Genomics 2015;16:698. 

7. Boke H, Ozhuner E, Turktas M, Parmaksiz I, Ozcan S, Unver T. Regulation of the alkaloid biosynthesis by miRNA in opium poppy. Plant Biotechnol J 2015;13:409-420.

8. Robert-Seilaniantz A, MacLean D, Jikumaru Y, Hill L, Yamaguchi S, Kamiya Y, Jones JDG. The microRNA miR393 redirects secondary metabolite biosynthesis away from camalexin and towards glucosinolates. Plant J 2011;67:218-231.

9. Ng DWK, Zhang CQ, Miller M, Palmer G, Whiteley M, Tholl D, Chen ZJ. cis- and trans-regulation of miR163 and target genes confers natural variation of secondary metabolites in two Arabidopsis species and their allopolyploids. Plant Cell 2011; 23:1729-1740.

10. Bartel DP. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 2004;116:281-297.

11. Jones-Rhoades MW, Bartel DP, Bartel B. MicroRNAs and their regulatory roles in plants. Annu Rev Plant Biol 2006;57:19-53.

12. Voinnet O. Origin, biogenesis, and activity of plant microRNAs. Cell 2009; 136:669-687.

13. Baumberger N, Baulcombe DC. Arabidopsis ARGONAUTE1 is an RNA slicer that selectively recruits microRNAs and short interfering RNAs. Proc Natl Acad Sci USA 2005;102:11928-11933.

14. Song JJ, Smith SK, Hannon GJ, Joshua-Tor L. Crystal structure of Argonaute and its implications for RISC slicer activity. Science 2004;305:1434-1437.

15. Guleria p, Goswami D, Yadav K. Computational identification of miRNAs and their targets from Crocus sativus L. Arch Biol Sci 2012;64:65-70.

16. Yusuf NH, Ong WD, Redwan RM, Latip MA, Kumar SV. Discovery of precursor and mature microRNAs and their putative gene targets using high-throughput sequencing in pineapple (Ananas comosus var. comosus). Gene 2015;571:71-80.

17. Han Y, Luan F, Zhu H, Shao Y, Chen A, Lu C, Luo Y, Zhu B. Computational identification of microRNAs and their targets in wheat (Triticum aestivum L.). Sci China C Life Sci 2009;52:1091-1100.

18. Zanca AS, Vicentini R, Ortiz-Morea FA, Del Bem LE, da Silva MJ, Vincentz M, Nogueira FT. Identification and expression analysis of microRNAs and targets in biofuel crop sugarcane. BMC Plant Biol 2010;10:260.

19. Akter A, Islam MM, Mondal SI, Mahmud Z, Jewel NA, Ferdous S, Amin MR, Rahman MM. Computational identification of miRNA and targets from expressed sequence tags of coffee (Coffea arabica). Saudi J Biol Sci 2013;21:3-12.

20. Vishwakarma NP, Jadeja VJ. Identification of miRNA encoded by Jatropha curcas from EST and GSS. Plant Signal Behav 2013;8:e23152.

21. Din M, Barozai MYK. Profiling microRNAs and their targets in an important fleshy fruit: tomato (Solanum lycopersicum). Gene 2014;535:198-203.

22. Griffiths-Jones S, Grocock RJ, van Dongen S, Bateman A, Enright AJ. miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res 2006; 34:D140-D144.

23. Masoudi-Nejad A, Tonomura K, Kawashima S, Moriya Y, Suzuki M, Itoh M, Kanehisa M, Endo T,Goto S. EGassembler: online bioinformatics service for large-scale processing, clustering and assembling ESTs and genomic DNA fragments. Nucleic Acids Res 2006;34:W459-462.

24. Carlson JE, Leebens-Mack JH, Wall PK, Zahn LM, Mueller LA, Landherr LL, Hu Y, Ilut DC, Arrington JM, Choirean S, Becker A, Field D, Tanksley SD, Ma H, dePamphilis CW. EST database for early flower development in California poppy (Eschscholzia californica Cham., Papaveraceae) tags over 6000 genes from a basal eudicot. Plant Mol Biol 2006;62:351-369.

25. Numnark S, Mhuantong W, Ingsriswang S, Wichadakul D. C-mii: a tool for plant miRNA and target identification. BMC Genomics 2012;13:S16. 

26. Bhardwaj J, Mohammad H, Yadav SK. Computational identification of microRNAs and their targets from the expressed sequence tags of horsegram (Macrotyloma uniforum (Lam.) Verdc.). J Struct Funct Genomics 2010;11:233-240.

27. Zhang BH, Pan XP, Wang QL, Cobb GP, Anderson TA. Identification and characterization of new plant microRNAs using EST analysis. Cell Res 2005;15: 336-360.

28. Huang DW, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 2009;4:44-57. 

29. Huang DW, Sherman BT, Lempicki RA. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res 2009;37:1-13. 

30. Kanehisa M, Sato Y, Kawashima M, Furumichi M, Tanabe M. KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res 2016;44: D457-D462.

31. Warde-Farley D, Donaldson SL, Comes O, Zuberi K, Badrawi R, Chao P, Franz M, Grouios C, Kazi F, Lopes CT, Maitland A, Mostafavi S, Montojo J, Shao Q, Wright G, Bader GD, Morris Q. The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function. Nucleic Acids Res 2010;38:W214-W220.

32. Pérez-Rodríguez P, Riaño-Pachón DM, Corrêa LGG, Rensing SA, Kersten B, Mueller-Roeber B. PlnTFDB: updated content and new features of the plant transcription factor database. Nucleic Acids Res 2010;38:D822-D827.

33. Buzko O, Shokat KM. Kinase sequence database: sequence alignments and family assignment. Bioinformatics 2002;18:1274-1275. 

34. Zhang B, Pan X, Wang Q, Cobba GP, Anderson TA. Computational identification of microRNAs and their targets. Comp Biol Chem 2006;30:395-407.

35. Xie F, Frazier TP, Zhang B. Identification and characterization of microRNAs and their targets in the bioenergy plant switchgrass (Panicum virgatum). Planta 2010; 232:417-434.

36. Guleria P, Yadav SK. Identification of miR414 and expression analysis of conserved miRNAs from Stevia rebaudiana. Genomics Proteomics Bioinformatics 2011;9:211-217.

37. Suo J, Liang X, Pu L, Zhang Y, Xue Y. Identification of GhMYB109 encoding a R2R3MYB transcription factor that expressed specifically in fiber initials and elongating fibers of cotton (Gossypium hirsutum L.). Biochim Biophys Acta 2003; 1630:25-34.

38. Zhang W, Wu Q, Pwee KH, Manjunatha Kini R. Interaction of wheat high-mobility-group proteins with four-way-junction DNA and characterization of the structure and expression of HMGA gene. Arch Biochem Biophys 2003;409:357-366.

39. Flaus A, Martin DM, Barton GJ, Owen-Hughes T. Identification of multiple distinct SNF2 subfamilies with conserved structural motifs. Nucleic Acids Res 2006;43:2887-2905.

40. Guo Q, Xiang A, Yang Q. Bioinformatic identification of microRNAs and their target genes from Solanum tuberosum expressed sequence tags. Chin Sci Bull 2007; 52:2380-2389.

41. Wan P, Wu J, Zhou Y, Xiao J, Feng J, Zhao W, Xiang S, Jiang G, Chen JK. Computational analysis of drought stress-associated miRNAs and miRNA co-regulation network in Physcomitrella patens. Genomics Proteomics Bioinformatics 2011;9:37-44.

42. Hua L, Ming-Qun G, Xiao-Yu S, Hui-Jie Z. Identification of microRNA responsed to iron deficiency in Arabidopsis. Chin J Biochem Mol Biol 2014;30:291-297. [In Chinese]

43. Eisen MB, Spellman PT, Brown PO, Botstein D. Cluster  analysis and display of genome-wide expression patterns. Proc Natl Acad Sci USA 1998;95:14863-14868.

44. Castillo R, Fernandez J, Gomez-Gomez L. Implications of carotenoid biosynthetic genes in apocarotenoid formation during the stigma development of Crocus sativus and its closer relatives. Plant Physiol 2005;139:674-689.

45. Winterhalter P, Skouroumounis GK. Glycoconjugated aroma compounds:   occurrence, role and biotechnological transformation. Adv Biochem Eng Biotechnol 1997;55:73-105

46. Winterhalter P, Rouseff RS, eds Carotenoid-derived aroma compounds: an introduction. In: Carotenoid-derived aroma compounds. American Chemical Society: Washington, DC; 2001.p. 1–17

47. Barvkar VT, Pardeshi VC, Kale SM, Kadoo NY, Gupta VS. Phylogenomic analysis of UDP glycosyltransferase 1 multigene family in Linum usitatissimum identified genes with varied expression patterns. BMC Genomics 2012;13:175.

48. Rubio-Moraga A, Rambla JL, Fernández-de-Carmen A, Trapero-Mozos A, Ahrazem O, Orzáez D, Granell A, Gómez-Gómez L. New target carotenoids for CCD4 enzymes are revealed with the characterization of a novel stress-induced carotenoid cleavage dioxygenase gene from Crocus sativus. Plant Mol Biol 2014; 86:555-569.

49. Onkokesung N, Gaquerel E, Kotkar H, Kaur H, Baldwin IT, Galis I. MYB8 controls inducible phenolamide levels by activating three novel hydroxycinnamoyl-coenzyme A: polyamine transferases in Nicotiana attenuata. Plant Physiol 2012; 158:389-407.

50. Koyama K, Numata M, Nakajima I, Goto Yamamoto N, Matsumura H, Tanaka N. Functional characterization of a new grapevine MYB transcription factor and regulation of proanthocyanidin biosynthesis in grapes. J Exp Bot 2014;65:4433-4449.

51. Yuan Y, Wu C, Liu Y, Yang J, Huang L. The Scutellaria baicalensis R2R3-MYB transcription factors modulates flavonoid biosynthesis by regulating GA metabolism in transgenic tobacco plants. PLoS One 2013;8:e77275.

52. Gargouri M, Park JJ, Holguin FO, Kim MJ, Wang H, Deshpande RR,Shachar-Hill Y, Hicks LM, David RG. Identification of regulatory network hubs that control lipid metabolism in Chlamydomonas reinhardtii. J Exp Bot 2015;66:4551-4566.

53. Bartels S, Gonzalez Besteiro MA, Lang D, Ulm R. Emerging functions for plant MAP kinase phosphatases. Trends Plant Sci 2010;15:322-329.