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:: دوره 7، شماره 1 - ( 1399 ) ::
جلد 7 شماره 1 صفحات 144-127 برگشت به فهرست نسخه ها
شناسایی، تعیین توالی و ارزیابی پایداری بیان هشت ژن مرجع گیاه زعفران (.Crocus sativus L)
سید سجاد سهرابی ، سید محسن سهرابی* ، سید کریم موسوی ، محسن محمدی
گروه مهندسی تولید و ژنتیک گیاهی، دانشکده کشاورزی و منابع طبیعی، دانشگاه لرستان، خرم‌آباد ، sohrabi.sa@fa.lu.ac.ir
چکیده:   (10258 مشاهده)
زعفران (.LCrocus sativus ) ارزشمندترین و گران‌ترین ادویه در سطح جهان است. کلاله‌های این گیاه منبع آپوکاروتنوئیدهای با ارزشی مانند کروسین، پیکروکروسین و سافرانال هستند. مطالعات ترنسکریپتومی و بیانی ژن‌ها یکی از مهم‌ترین مراحل در بررسی تولید متابولیت‌های ثانویه‌ در گیاهان هستند. یکی از پیش‌نیازهای مهم در این گونه مطالعات، شناسایی ژن‌های مرجع قابل‌اعتماد و پایدار به‌منظور نرمال‌سازی بیان سایر ژن‌ها است. در پژوهش حاضر، با استفاده از ترنسکریپتوم گیاه زعفران هشت ژن مرجع شناسایی و تعیین توالی شد، سپس میزان پایداری بیان آن‌ها با استفاده از روش‌‌های غیرپارامتریک مورد بررسی قرار گرفت. نتایج تکثیر و توالی‌یابی، جداسازی صحیح هشت ژن مرجع Actin، EF1، GAPDH، H3، MDH، TBP، UBC و UBQ را از گیاه زعفران نشان داد. بررسی میزان پایداری بیان ژن‌های مرجع نشان داد که ژن‌های MDH و UBQ به‌ترتیب بیشترین میزان پایداری را بین بافت‌های مختلف گیاه زعفران داشته و کمترین میزان پایداری مربوط به ژن‌ TBP بود. در این پژوهش توالی هشت ژن مرجع در زعفران جداسازی و پایداری بیان آن‌ها برای اولین‌بار در بافت‌های مختلف این گیاه سنجیده شد. ژن‌های مرجع شناسایی شده در این پژوهش می‌توانند به‌عنوان ژن‌های پایدار برای نرمال‌سازی بیان ژن‌ها در مطالعات ترنسکریپتومی گیاه زعفران به‌کار برده شوند.
واژه‌های کلیدی: آماره‌های غیرپارامتریک، پایداری بیان ژن، ترنسکریپتوم، زعفران، ژن‌های مرجع
متن کامل [PDF 663 kb]   (1648 دریافت)    
نوع مطالعه: پژوهشي | موضوع مقاله: ژنتیک مولکولی
فهرست منابع
1. Agrawal, G.K., Jwa, N.S., Lebrun, M.H., Job, D. and Rakwal, R. (2010). Plant secretome: unlocking secrets of the secreted proteins. Proteomics, 10: 799-827.
2. Ahrazem, O., Argandona, J., Fiore, A., Aguado, C., Lujan, R., Rubio-Moraga, A., Marro, M., Araujo-Andrade, C., Loza-Alvarez, P., Diretto, G. and Gomez-Gomez, L. (2018). Transcriptome analysis in tissue sectors with contrasting crocins accumulation provides novel insights into apocarotenoid biosynthesis and regulation during chromoplast biogenesis. Scientific Reports, 8: 2843.
3. Ahrazem, O., Argandona, J., Fiore, A., Rujas, A., Rubio-Moraga, A., Castillo, R. and Gomez-Gomez, L. (2019). Multi-species transcriptome analyses for the regulation of crocins biosynthesis in Crocus. BMC Genomics, 20: 320.
4. Ahrazem, O., Rubio-Moraga, A., Nebauer, S.G., Molina, R.V. and Gómez-Gómez, L. (2015). Saffron: its phytochemistry, developmental processes, and biotechnological prospects. Journal of agricultural and food chemistry, 63: 8751-8764.
5. Ashraf, N., Jain, D. and Vishwakarma, R.A. (2015). Identification, cloning and characterization of an ultrapetala transcription factor CsULT1 from Crocus: a novel regulator of apocarotenoid biosynthesis. BMC Plant Biology, 15: 25.
6. Azizi-Zohan, A.A., Kamgar-Haghighi, A.A. and Sepaskhah, A.R (2009). Saffron (Crocus sativus L.) production as influenced by rainfall, irrigation method and intervals. Archives of Agronomy and Soil Science, 55: 547-555.
7. Baba, S.A., Mohiuddin, T., Basu, S., Swarnkar, M.K., Malik, A.H., Wani, Z.A., Abbas, N., Singh, A.K. and Ashraf, N. (2015). Comprehensive transcriptome analysis of Crocus sativus for discovery and expression of genes involved in apocarotenoid biosynthesis. BMC Genomics, 16: 698.
8. Behdani, M. and Fallahi, H. (2015) Saffron: Technical Knowledge Based on Research Approaches. University of Birjand Publication, Birjand, IR (In Persian).
9. Bolger, A.M., Lohse, M. and Usadel, B. (2014). Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics, 30: 2114-2120.
10. Brandizzi, F. and Caiola, M.G. (1998). Flow cytometric analysis of nuclear DNA inCrocus sativus and allies (Iridaceae). Plant Systematics and Evolution, 211: 149-154.
11. Burley, S.K. (1996). The TATA box binding protein. Current Opinion in Structural Biology, 6: 69-75.
12. Bustin, S.A. (2000). Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays. Journal of Molecular Endocrinology, 25: 169-193.
13. Cheng, B., Furtado, A. and Henry, R.J. (2017). Long-read sequencing of the coffee bean transcriptome reveals the diversity of full-length transcripts. Gigascience, 6: gix086.
14. Conesa, A., Madrigal, P., Tarazona, S., Gomez-Cabrero, D., Cervera, A., McPherson, A., Szcześniak, M.W., Gaffney, D.J., Elo, L.L., Zhang, X. and Mortazavi, A. (2016). A survey of best practices for RNA-seq data analysis. Genome Biology, 17: 13.
15. D'Agostino, N., Pizzichini, D., Chiusano, M.L. and Giuliano, G. (2007). An EST database from saffron stigmas. BMC Plant Biology, 7: 53.
16. Ebrahimi, A., Rashidi Monfared, S., moradi sarabshelli, A. and heidari, P. (2018). Validation of some of Housekeeping Genes in Aeluropus littoralis under Salinity Stress. Journal of Crop Breeding, 10: 110-117 (In Persian).
17. Fernández, J.A. (2004). Biology, biotechnology and biomedicine of saffron. Recent Res Dev Plant Science, 2: 127-159.
18. Finn, R.D., Coggill, P., Eberhardt, R.Y., Eddy, S.R., Mistry, J., Mitchell, A.L., Potter, S.C., Punta, M., Qureshi, M. and Sangrador-Vegas, A. (2016). The Pfam protein families database: towards a more sustainable future. Nucleic Acids Research, 44: D279-D285.
19. Garg, R. and Jain, M. (2013). RNA-Seq for Transcriptome Analysis in Non-Model Plants. In: Rose, R.J., Ed., Legume Genomics, pp. 43-58, Springer Science & Business Media, Berlin, DE.
20. Gilbert, D.G. (2018). Genes of the Pig, Sus scrofa, reconstructed with Evidential Gene. PeerJ Preprints, 7: e6374.
21. Gomez-Gomez, L., Pacios, L.F., Diaz-Perales, A., Garrido-Arandia, M., Argandona, J., Rubio-Moraga, A. and Ahrazem, O. (2018). Expression and Interaction Analysis among Saffron ALDHs and Crocetin Dialdehyde. International Journal of Molecular Sciences, 19(5): 1409.
22. Grabherr, M.G., Haas, B.J., Yassour, M., Levin, J.Z., Thompson, D.A., Amit, I., Adiconis, X., Fan, L., Raychowdhury, R. and Zeng, Q. (2011). Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nature Biotechnology, 29: 644-652.
23. Greganova, E., Altmann, M. and Bütikofer, P. (2011). Unique modifications of translation elongation factors. The FEBS Journal, 278: 2613-2624.
24. Gutierrez, L., Mauriat, M., Pelloux, J., Bellini, C. and Van Wuytswinkel, O. (2008). Towards a systematic validation of references in real-time RT-PCR. The Plant Cell, 20: 1734-1735.
25. Hershko, A. and Ciechanover, A. (1998). The ubiquitin system. Annual Review of Biochemistry, 67: 425-479.
26. Hochstrasser, M. (1996). Ubiquitin-dependent protein degradation. Annual Review of Genetics, 30: 405-439.
27. Houben, A., Demidov, D., Caperta, A.D., Karimi, R., Agueci, F. and Vlasenko, L. (2007). Phosphorylation of histone H3 in plants-a dynamic affair. Biochimica et Biophysica Acta (BBA)-Gene Structure and Expression, 1769: 308-315.
28. Hurley, J.H. (1996). The sugar kinase/heat shock protein 70/actin superfamily: implications of conserved structure for mechanism. Annual Review of Biophysics and Biomolecular Structure, 25: 137-162.
29. Husaini, A.M., Wani, S.A., Sofi, P., Rather, A.G., Parray, G.A., Shikari, A.B. and Mir, J.I. (2009). Bioinformatics for saffron (Crocus sativus L.) improvement. Communications in Biometry & Crop Science, 4(1): 3-8. [DOI:10.1093/bioinformatics/btp217]
30. Jain, M., Nijhawan, A., Tyagi, A.K. and Khurana, J.P. (2006). Validation of housekeeping genes as internal control for studying gene expression in rice by quantitative real-time PCR. Biochemical and Biophysical Research Communications, 345: 646-651.
31. Jain, M., Srivastava, P.L., Verma, M., Ghangal, R. and Garg, R. (2016). De novo transcriptome assembly and comprehensive expression profiling in Crocus sativus to gain insights into apocarotenoid biosynthesis. Scientific Reports, 6: 22456.
32. Jaiswal, P.S., Kaur, N. and Randhawa, G.S. (2019). Identification of reference genes for qRT-PCR gene expression studies during seed development and under abiotic stresses in Cyamopsis tetragonoloba. Crop Science, 59: 252-265.
33. Jones, P., Binns, D., Chang, H.Y., Fraser, M., Li, W., McAnulla, C., McWilliam, H., Maslen, J., Mitchell, A. and Nuka, G. (2014). InterProScan 5: genome-scale protein function classification. Bioinformatics, 30: 1236-1240.
34. Kamalipour, M. and Akhondzadeh, S. (2011). Cardiovascular effects of saffron: An evidence-based review. The Journal of Tehran Heart Center, 6(2): 59-61.
35. Karge, W.H., Schaefer, E.J. and Ordovas, J.M. (1998). Quantification of Mrna By Polymerase Chain Reaction (PCR) Using An Internal Standard and A Nonradioactive Detection Method. In: Ordovas, J.M., Ed., Lipoprotein Protocols, pp. 43-61, Springer Science & Business Media, Berlin, DE.
36. Khakpour, A., Zolfaghari, M. and Sorkheh, K. (2019). Bioinformatics Study and Investigation of the Expression Pattern of Several Important Genes Involved in Glycyrrhizin Synthesis of Glycyrrhiza glabra L. in Autumn and Spring Seasons. Plant Genetic Researches, 6(1): 55-68 (In Persian).
37. Kiarash, J.G., Wilde, H.D., Amirmahani, F., Moemeni, M.M., Zaboli, M., Nazari, M., Moosavi, S.S. and Jamalvandi, M. (2018). Selection and validation of reference genes for normalization of qRT-PCR gene expression in wheat (Triticum durum L.) under drought and salt stresses. Journal of Genetics, 97: 1433-1444.
38. Komander, D. (2009). The emerging complexity of protein ubiquitination. Biochemical Society Transactions, 37: 937-953.
39. Komander, D. and Rape, M. (2012). The ubiquitin code. Annual Review of Biochemistry, 81: 203-229.
40. Koocheki, A., Ebrahimian, E. and Seyyedi, S.M. (2016). How irrigation rounds and mother corm size control saffron yield, quality, daughter corms behavior and phosphorus uptake. Scientia Horticulturae, 213: 132-143.
41. Li, J. and Tibshirani, R. (2013). Finding consistent patterns: a nonparametric approach for identifying differential expression in RNA-Seq data. Stat Methods Med Res, 22: 519-36.
42. Malik, A.H. and Ashraf, N. (2017). Transcriptome wide identification, phylogenetic analysis, and expression profiling of zinc-finger transcription factors from Crocus sativus L. Molecular Genetics and Genomics, 292: 619-633.
43. Marchler-Bauer, A., Derbyshire, M.K., Gonzales, N.R., Lu, S., Chitsaz, F., Geer, L.Y., Geer, R.C., He, J., Gwadz, M. and Hurwitz, D.I. (2014). CDD: NCBI's conserved domain database. Nucleic Acids Research, 43: D222-D226.
44. Martin, M. (2011). Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnetjournal, 17(1): 10-12.
45. Matvienko, M. (2015). CLC Genomics Workbench. Plant and Animal Genome. Sr. Field Application Scientist, CLC Bio, Aarhus, DE.
46. Majdi, M., Karimzade, G. and Malboobi, M.A. (2015). The study of relative gene expression of key genes of terpene biosynthesis in tissues and different developmental stages of feverfew (Tanacetum parthenium) genotypes using real-time PCR. Plant Genetic Researches, 1: 25-32 (In Persian).
47. Minarik, P., Tomaskova, N., Kollarova, M. and Antalik, M. (2002). Malate dehydrogenases-structure and function. General Physiology and Biophysics, 21: 257-266.
48. Nassar, R. and Huehn, M. (1987). Studies on estimation of phenotypic stability: Tests of significance for nonparametric measures of phenotypic stability. Biometrics, 43(1): 45-53.
49. Nicholls, C., Li, H. and Liu, J.P. (2012). GAPDH: a common enzyme with uncommon functions. Clinical and Experimental Pharmacology and Physiology, 39: 674-679.
50. Nickel, W. and Seedorf, M. (2008). Unconventional mechanisms of protein transport to the cell surface of eukaryotic cells. Annual Review of Cell and Developmental Biology, 24: 287-308.
51. Nielsen, H. (2017). Predicting Secretory Proteins with SignalP. In: Kihara, D., Ed., Protein Function Prediction, Methods and Protocols, pp. 59-73, Springer Science & Business Media, Berlin, DE.
52. Nikolov, D.B., Hu, S.H., Lin, J., Gasch, A., Hoffmann, A., Horikoshi, M., Chua, N.H., Roeder, R.G. and Burley, S.K. (1992). Crystal structure of TFIID TATA-box binding protein. Nature, 360: 40-46.
53. Ono, H., Ishii, K., Kozaki, T., Ogiwara, I., Kanekatsu, M. and Yamada, T. (2015). Removal of redundant contigs from de novo RNA-Seq assemblies via homology search improves accurate detection of differentially expressed genes. BMC Genomics, 16: 1031.
54. Paez-Garcia, A., Sparks, J.A., de Bang, L. and Blancaflor, E.B. (2018). Plant Actin Cytoskeleton: New Functions From Old Scaffold. In: Sah,V.P. and Baluška, F., Eds., Concepts in Cell Biology-History And Evolution, pp. 103-137, Springer Science & Business Media, Berlin, DE.
55. Pettigrew, D.W. (2009). Amino acid substitutions in the sugar kinase/hsp70/actin superfamily conserved ATPase core of E. coli glycerol kinase modulate allosteric ligand affinity but do not alter allosteric coupling. Archives of Biochemistry and Biophysics, 481: 151-156.
56. Pfaffl, M.W., Tichopad, A., Prgomet, C. and Neuvians, T.P. (2004). Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper-Excel-based tool using pair-wise correlations. Biotechnology Letters, 26: 509-515.
57. Qian, X., Sun, Y., Zhou, G., Yuan, Y., Li, J., Huang, H., Xu, L. and Li, L. (2019). Single-molecule real-time transcript sequencing identified flowering regulatory genes in Crocus sativus. BMC Genomics, 20: 857.
58. Rajabi, H., Ghorbani, M., Jafari, S.M., Mahoonak, A.S. and Rajabzadeh, G. (2015). Retention of saffron bioactive components by spray drying encapsulation using maltodextrin, gum Arabic and gelatin as wall materials. Food Hydrocolloids, 51: 327-337.
59. Sampathu, S., Shivashankar, S., Lewis, Y. and Wood, A. (1984). Saffron (Crocus sativus Linn.)-cultivation, processing, chemistry and standardization. Critical Reviews in Food Science & Nutrition, 20: 123-157.
60. Sasikumar, A.N., Perez, W.B. and Kinzy, T.G. (2012). The many roles of the eukaryotic elongation factor 1 complex. Wiley Interdisciplinary Reviews: RNA, 3: 543-555.
61. Scheffner, M., Nuber, U. and Huibregtse, J.M. (1995). Protein ubiquitination involving an E1-E2-E3 enzyme ubiquitin thioester cascade. Nature, 373: 81-83.
62. Shahraki, S., Kazemitabar, S.K. and Hashemi, S.H.R. (2014). Study of Reference Genes in Sesame Leaves under Salt Stress by Real-Time PCR Method. Crop Biotech, 8: 1-10 (In Persian).
63. Sheskin, D.J. (2003) Handbook of Parametric and Nonparametric Statistical Procedures. CRC Press, Boca Raton, Florida, USA.
64. Singh, V.K., Singh, A.K., Singh, S. and Singh, B.D. (2015). Next-Generation Sequencing (NGS) Tools and Impact in Plant Breeding. In: Al-Khayri, J.M., Jain, S.M. and Johnson, D.V., Eds., Advances in Plant Breeding Strategies: Breeding, Biotechnology and Molecular Tools, pp. 563-612, Springer Science & Business Media, Berlin, DE.
65. Skladnev, N.V. and Johnstone, D.M. (2017). Neuroprotective properties of dietary saffron: more than just a chemical scavenger? Neural Regeneration Research, 12: 210-211.
66. Smith-Unna, R., Boursnell, C., Patro, R., Hibberd, J.M. and Kelly, S. (2016). TransRate: reference-free quality assessment of de novo transcriptome assemblies. Genome Research, 26: 1134-1144.
67. Soltani Howyzeh, M., Sadat Noori, S.A., Shariati, V. and Amiripour, M. (2019). Large scale identification of SSR molecular markers in Ajowan (Trachyspermum ammi) using RNA sequencing. Plant Genetic Researches, 6: 31-46 (In Persian).
68. Song, L. and Florea, L. (2015). Rcorrector: efficient and accurate error correction for Illumina RNA-seq reads. Gigascience, 4: 48.
69. Staiger, C.J., Baluska, F., Volkmann, D. and Barlow, P. (2013) Actin: A Dynamic Framework for Multiple Plant Cell Functions. Springer Science & Business Media, Berlin, DE.
70. Swatek, K.N. and Komander, D. (2016). Ubiquitin modifications. Cell Research, 26: 399-422.
71. Tan, H., Chen, X., Liang, N., Chen, R., Chen, J., Hu, C., Li, Q., Li, Q., Pei, W., Xiao, W., Yuan, Y., Chen, W. and Zhang, L. (2019). Transcriptome analysis reveals novel enzymes for apo-carotenoid biosynthesis in saffron and allows construction of a pathway for crocetin synthesis in yeast. Journal of Experimental Botany, 70: 4819-4834.
72. Thennarasu, K. (1995). On Certain Non-parametric Procedures for Studying Genotype-Environment Inertactions and Yield Stability. New Dehli, IND.
73. Tzeng, G.H. and Huang, J.J. (2011) Multiple Attribute Decision Making: Methods and Applications. CRC Press, Boca Raton, Florida, USA.
74. Unamba, C.I.N., Nag, A. and Sharma, R.K. (2015). Next generation sequencing technologies: the doorway to the unexplored genomics of non-model plants. Frontiers in Plant Science, 6: 10.3389/fpls.2015.01074.
75. Vandesompele, J., De Preter, K., Pattyn, F., Poppe, B., Van Roy, N., De Paepe, A. and Speleman, F. (2002). Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biology, 3: research0034
76. Wang, Y., Dai, M., Cai, D. and Shi, Z. (2019). Screening for quantitative real-time PCR reference genes with high stable expression using the mRNA-sequencing data for pear. Tree Genetics & Genomes, 15: 54.
77. Xie, X., Xiao, Q., Xiong, Z., Yu, C., Zhou, J. and Fu, Z. (2019). Crocin-I ameliorates the disruption of lipid metabolism and dysbiosis of the gut microbiota induced by chronic corticosterone in mice. Food & Functio, 10: 6779-6791.
78. Yang, S. and Zhai, Q. (2017). Cytosolic GAPDH: a key mediator in redox signal transduction in plants. Biologia Plantarum, 61: 417-426.
79. Zaffagnini, M., Fermani, S., Costa, A., Lemaire, S.D. and Trost, P. (2013). Plant cytoplasmic GAPDH: redox post-translational modifications and moonlighting properties. Frontiers in Plant Science, 4: 450.
80. Zali, H., Sofalian, O., Hasanloo, T., Asgharii, A. and Hoseini, S.M. (2015). Appraising of drought tolerance relying on stability analysis indices in canola genotypes simultaneously, using selection index of ideal genotype (SIIG) technique: Introduction of new method. Paper presented at the Biological Forum, 7(2): 703-711.
81. Zeng, Y., Yan, F., Tang, L. and Chen, F. (2003). Increased crocin production and induction frequency of stigma-like-structure from floral organs of Crocus sativus L. by precursor feeding. Plant Cell, Tissue and Organ Culture, 72: 185-191.
82. Zhang, L. and Li, W.H. (2004). Mammalian housekeeping genes evolve more slowly than tissue-specific genes. Molecular Biology and Evolution, 21: 236-239.
83. Zhang, Y., Li, D. and Sun, B. (2015). Do housekeeping genes exist? PLoS One, 10(5): e0123691
84. Zheng, B. and Chen, X. (2011). Dynamics of histone H3 lysine 27 trimethylation in plant development. Current Opinion in Plant Biology, 14: 123-129.
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Sohrabi S S, Sohrabi S M, Mousavi S K, Mohammadi M. Identification, Sequencing and Stability Evaluation of Eight Reference Genes in Saffron (Crocus sativus L.). pgr 2020; 7 (1) :127-144
URL: http://pgr.lu.ac.ir/article-1-177-fa.html

سهرابی سید سجاد، سهرابی سید محسن، موسوی سید کریم، محمدی محسن. شناسایی، تعیین توالی و ارزیابی پایداری بیان هشت ژن مرجع گیاه زعفران (.Crocus sativus L). پژوهش های ژنتیک گیاهی. 1399; 7 (1) :127-144

URL: http://pgr.lu.ac.ir/article-1-177-fa.html



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