با همکاری مشترک دانشگاه پیام نور و انجمن بیوتکنولوژی جمهوری اسلامی ایران

نوع مقاله : علمی پژوهشی

نویسندگان

1 گروه زیست فناوری، دانشکده کشاورزی، دانشگاه صنعتی اصفهان، اصفهان، ایران

2 گروه زیست فناوری ، دانشکده مهندسی کشاورزی، دانشگاه صنعتی اصفهان، اصفهان، ایران

چکیده

کنه تارتن دولکه‌ای (Tetranychus urticae Koch) از مهم‌ترین آفات تخریب‌کننده لوبیا (Phaseolus vulgaris L.) است. به‌طور کلی شبکه‌های ژنی پیچیده‌ای در ایجاد حساسیت یا مقاومت در مقابل کنه تارتن دولکه‌ای دخیل هستند، بنابراین در این تحقیق از روش سامانه‌های زیستی به‌کار برده شد. برای این منظور از داده‌های RNA-Seq مربوط به تنش کنه تارتن روی گیاه لوبیا استفاده شد. پس از فراهم‌کردن ماتریس بیان ژن‌ها، شبکه‌های مولکولی با استفاده از آنالیز شبکه هم‌بیان وزن‌دار (WGCNA) مورد تجزیه و تحلیل قرار گرفتند. پس از ایجاد ماژول‌ها، عملکرد ژن‌ها در هر ماژول مورد بررسی و تجزیه و تحلیل قرار گرفت. بر اساس نتایج، مجموع 699 ژن با بیان افتراقی در پاسخ به تنش کنه تارتن شناسایی شدند که در 7 ماژول هم‌بیان از طریق خوشه‌بندی سلسله‌مراتبی جای گرفتند. بررسی هستی‌شناسی ژن‌ها و آنالیز برهمکنش ژن‌های کلیدی با استفاده از بانک اطلاعاتی String نشان داد پاسخ ترانسکریپتوم لوبیا به آلودگی با کنه تارتن بیشتر شامل ژن‌های کدکننده پروتئین کینازها، کاتالیزورها، فاکتورهای رونویسی، ساخت متابولیت‌ها و مسیرهای انتقال پیام هورمونی بود. ماژول فیروز‌ه‌ای بیشترین ژن‌های درگیر در مقاومت را دارا بود که این ماژول و ماژول زرد، بیشترین همبستگی را با رقم مقاوم به ترتیب پس از پنج و یک روز آلودگی داشتند. همچنین، ماژول مشکی بیشترین همبستگی با رقم حساس پس از پنج روز آلودگی را داشت. این مطالعه دانش ما را از مکانیسم‌های مولکولی دخیل در مقاومت به کنه تارتن افزایش می‌دهد. همچنین ژن‌های بررسی شده در این تحقیق می‌توانند به‌عنوان اهداف اصلاحی برای ایجاد مقاومت معرفی شوند.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Co-expression network analysis of common bean transcriptome in order to identify modules and hub genes involved in resistance to Tetranychus urticae (Acari, Tetranychidae)

نویسندگان [English]

  • Fatemeh Mohammadi 1
  • Aboozar Soorni 1
  • Rahim Mehrabi 2

1 Department of Biotechnology, College of Agriculture, Isfahan University of Technology, Isfahan, Iran

2 Department of Biotechnology, College of Agriculture, Isfahan University of Technology, Isfahan, Iran

چکیده [English]

Two-spotted spider mite (Tetranychus urticae Koch) is one of the most important pests of beans (Phaseolus vulgaris L.). Since, complex gene networks are involved in creating sensitivity or resistance against the two-spotted spider mite; therefore, in this research we used biological system methods to identify key networks. For this purpose, we used the RNA-Seq data related to the two-spotted spider mite stress on common bean plant. After providing the gene expression matrix, molecular networks were analyzed using weighted co-expression network analysis (WGCNA). After the modules identification, the gene functions in each module were investigated and analyzed. According to the results, a total of 699 genes were identified with differential expression in response to two-spotted spider mite stress, which were placed in 7 co-expression modules through hierarchical clustering. Gene ontology and interaction analysis of key genes using the String database showed that the response of common bean transcriptome to two-spotted spider mite infestation includes genes encoding protein kinases, catalysts, transcription factors, and metabolite production and pathways of hormonal message transmission. It is notable that among the most important genes that showed co-expression, WRKY and lipoxygenase were highlighted. The turquoise module had the higher number of genes involved in resistance, and this module and the yellow module had the highest correlation with the resistant variety after five and one day of contamination, respectively. Also, the black module had the highest correlation with the sensitive variety after five days of contamination. In conclusion, this study increases our knowledge of the molecular mechanisms involved in resistance to the two-spotted spider mite. Also, the genes examined in this research can be introduced as breeding targets to create resistance.

کلیدواژه‌ها [English]

  • co-expression network
  • Common bean
  • gene interaction
  • transcriptome
  • two spotted spider mite
Abbasi, S., Safaie, N., Sadeghi, A., & Shamsbakhsh, M. (2019). Streptomyces strains induce resistance to Fusarium oxysporum f. sp. lycopersici race 3 in tomato through different molecular mechanisms. Frontiers in Microbiology, 10, 1505. Artus, N. N., & Edwards, G. E. (1985). NAD‐malic enzyme from plants. FEBS letters, 182(2), 225-233. Bergmann, S., Ihmels, J., Barkai, N., & Eisen, M. (2004). Similarities and differences in genome-wide expression data of six organisms. PLoS biology, 2(1), e9. Bolger, A. M., Lohse, M., & Usadel, B. (2014). Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics, 30(15), 2114-2120. Broughton, W. J., Hernandez, G., Blair, M., Beebe, S., Gepts, P., & Vanderleyden, J. (2003). Beans (Phaseolus spp.)–model food legumes. Plant and soil, 252(1), 55-128. Bueno, A. D. F., Bueno, R. C. O. D. F., Nabity, P. D., Higley, L. G., & Fernandes, O. A. (2009). Photosynthetic response of soybean to twospotted spider mite (Acari: Tetranychydae) injury. Brazilian Archives of Biology and Technology, 52, 825-834. Creelman, R. A., Bell, E., & Mullet, J. E. (1992). Involvement of a lipoxygenase-like enzyme in abscisic acid biosynthesis. Plant Physiology, 99(3), 1258-1260. Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., ... & Gingeras, T. R. (2013). STAR: ultrafast universal RNA-seq aligner. Bioinformatics, 29(1), 15-21. Franck, C. M., Westermann, J., & Boisson-Dernier, A. (2018). Plant malectin-like receptor kinases: from cell wall integrity to immunity and beyond. Annual Review of Plant Biology, 69, 301-328. Fraudentali, I., Ghuge, S. A., Carucci, A., Tavladoraki, P., Angelini, R., Rodrigues-Pousada, R. A., & Cona, A. (2020). Developmental, hormone-and stress-modulated expression profiles of four members of the Arabidopsis copper-amine oxidase gene family. Plant Physiology and Biochemistry, 147, 141-160. Grbić, M., Van Leeuwen, T., Clark, R. M., Rombauts, S., Rouzé, P., Grbić, V., ... & Van de Peer, Y. (2011). The genome of Tetranychus urticae reveals herbivorous pest adaptations. Nature, 479(7374), 487-492. Heese, A., Hann, D. R., Gimenez-Ibanez, S., Jones, A. M., He, K., Li, J., ... & Rathjen, J. P. (2007). The receptor-like kinase SERK3/BAK1 is a central regulator of innate immunity in plants. Proceedings of the National Academy of Sciences, 104(29), 12217-12222. Hopper, D. W., Ghan, R., Schlauch, K. A., & Cramer, G. R. (2016). Transcriptomic network analyses of leaf dehydration responses identify highly connected ABA and ethylene signaling hubs in three grapevine species differing in drought tolerance. BMC plant biology, 16(1), 1-20. Hurt, J. A., Obar, R. A., Zhai, B., Farny, N. G., Gygi, S. P., & Silver, P. A. (2009). A conserved CCCH-type zinc finger protein regulates mRNA nuclear adenylation and export. Journal of Cell Biology, 185(2), 265-277. Jain, S., Chittem, K., Brueggeman, R., Osorno, J. M., Richards, J., & Nelson Jr, B. D. (2016). Comparative transcriptome analysis of resistant and susceptible common bean genotypes in response to soybean cyst nematode infection. PLoS One, 11(7), e0159338. Jones, J. D., & Dangl, J. L. (2006). The plant immune system. nature, 444(7117), 323-329. Katungi, E., Sperling, L., Karanja, D., Farrow, A., & Beebe, S. (2010). Relative Importance of Common Bean Attributes and Variety Demand in the Drought Areas of Kenya. International Journal of Tropical Agriculture and Food Systems, 4(3), 194-205. Kavousi, A. (2000). Laboratory evaluation of three pesticides on the predatory mite, Phytoseiulus persimillis (Doctoral dissertation, M. Sc. Thesis, College of Agriculture, University of Tehran, Iran. 170 pp.(In Persian with English Summary)). Langfelder, P., & Horvath, S. (2008). WGCNA: an R package for weighted correlation network analysis. BMC bioinformatics, 9(1), 1-13. Mortezaeefar, M., Fotovat, R., Shekari, F., & Sasani, S. (2017). Weighted gene co-expression network analysis of regulatory modules by jasmonic acid in Arabidopsis. Crop Biotechnology, 7(17), 55-71. (in persian) Moschen, S., Higgins, J., Di Rienzo, J. A., Heinz, R. A., Paniego, N., & Fernandez, P. (2016). Network and biosignature analysis for the integration of transcriptomic and metabolomic data to characterize leaf senescence process in sunflower. BMC bioinformatics, 17(5), 389-398. Niemi, J. (2007). Accuracy of the Bayesian network algorithms for inferring gene regulatory networks. Independent research projects in applied mathematics Mat-2.108, Helsinky University of Technology. O’Rourke, J. A., Iniguez, L. P., Fu, F., Bucciarelli, B., Miller, S. S., Jackson, S. A., ... & Vance, C. P. (2014). An RNA-Seq based gene expression atlas of the common bean. BMC genomics, 15(1), 1-17. Onstad, D. W., & Knolhoff, L. (2014). Arthropod resistance to crops. In Insect Resistance Management (pp. 293-326). Academic Press. Schaefer, R. J., Michno, J. M., & Myers, C. L. (2017). Unraveling gene function in agricultural species using gene co-expression networks. Biochimica et Biophysica Acta (BBA)-Gene Regulatory Mechanisms, 1860(1), 53-63. Schmutz, J., McClean, P. E., Mamidi, S., Wu, G. A., Cannon, S. B., Grimwood, J., ... & Jackson, S. A. (2014). A reference genome for common bean and genome-wide analysis of dual domestications. Nature genetics, 46(7), 707-713. Serin, E. A., Nijveen, H., Hilhorst, H. W., & Ligterink, W. (2016). Learning from co-expression networks: possibilities and challenges. Frontiers in plant science, 7, 444. Shih, K. C., Chen, R. M., Hu, R. M., Liu, F. M., Chen, H. K., & Tsai, J. J. (2004, December). Prediction of gene regulatory networks using differential expression of cDNA microarray data. In IEEE Sixth International Symposium on Multimedia Software Engineering (pp. 378-385). IEEE. Yin, M., Wang, Y., Zhang, L., Li, J., Quan, W., Yang, L., ... & Chan, Z. (2017). The Arabidopsis Cys2/His2 zinc finger transcription factor ZAT18 is a positive regulator of plant tolerance to drought stress. Journal of Experimental Botany, 68(11), 2991-3005. Yoshida, H., Nagata, M., Saito, K., Wang, K. L., & Ecker, J. R. (2005). Arabidopsis ETO1 specifically interacts with and negatively regulates type 2 1-aminocyclopropane-1-carboxylate synthases. BMC Plant Biology, 5(1), 1-13. Zhang, B., & Horvath, S. (2005). A general framework for weighted gene co-expression network analysis. Statistical applications in genetics and molecular biology, 4(1).