شناسایی ژن های کلیدی موثر در تحمل به تنش خشکی در برنج از طریق فراتحلیل داده ‏های ریزآرایه

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه بیوتکنولوژی، دانشکده کشاورزی، دانشگاه شهید مدنی آذربایجان، تبریز، ایران

2 دانشیار، گروه بیوتکنولوژی، دانشکده کشاورزی، دانشگاه شهید مدنی آذربایجان، تبریز، ایران

3 دانشیار، گروه علوم دامی، دانشکده کشاورزی، دانشگاه تبریز، تبریز، ایران

4 استادیار، گروه بیوتکنولوژی، دانشکده کشاورزی، دانشگاه شهید مدنی آذربایجان، تبریز، ایران

چکیده

اهداف: تنش‏های محیطی مانند خشکی، افزایش دما، شوری و افزایش CO2 تهدیدی جدی برای کشاورزی پایدار است. تنش خشکی از مهمترین تنش‏های غیر زیستی در برنج است که باعث کاهش عملکرد محصول می‏شود. تحقیقات متعددی به صورت جداگانه برای شناسایی سازوکار مولکولی پاسخ گیاه به تنش خشکی انجام شده است. بنابراین فراتحلیل می‏تواند با ادغام نتایج مطالعات متعدد مرتبط، منجر به درک بهتر سازوکار‏های تحمل به تنش خشکی شود.
مواد و روش‏ها: در این راستا، چهار سری داده ریزآرایه با کیفیت مناسب برنج تحت تنش خشکی و شرایط طبیعی انتخاب شد و سپس توسط بسته ‏limma نرم‏افزار R آنالیز شد. جهت فراتحلیل از بسته ‏meta RNAseq و روش Fisher برای یکی کردن p-valueهای حاصل از تجزیه انفرادی داده‏های مورد بررسی استفاده شد. ژن‏های متفاوت بیان شونده فراتحلیل دارای افزایش و کاهش بیان تحت تنش خشکی شناسایی شد. سپس هستی‏شناسی ژن (ژن آنتولوژی)، شناسایی ژن‏های مرکزی یا هاب و آنالیز شبکه هم بیانی انجام شد. نتایج حاصل با آزمایش real-time quantitative PCR در رقم برنج هاشمی حساس و رقم بومی متحمل به تنش کمبود آب در شرایط درون شیشه‏ای با تیمار PEG ارزیابی گردید.
یافته‏ها: از نتایج مطالعه حاضر 578 ژن با افزایش بیان و 660 ژن با کاهش بیان بدست آمد. تجزیه و تحلیل هستی‏شناسی ژن(GO) سازوکارهای پاسخ به خشکی را نشان داد و ترسیم شبکه برهمکنش پروتئین-پروتئین مشخص کرد که ژن‌های مرکزی متفاوت بیان شونده دارای کاهش بیان تحت تنش خشکی حاصل از این مطالعه عمدتاً مربوط به فرایند فتوسنتز و ژن‌های مرکزی متفاوت بیان شونده دارای افزایش بیان تحت تنش خشکی عمدتاً مربوط به تحمل تنش شامل ژن‌های HSP، LEAs، PP2Cs هستند. در نهایت، داده‏های به دست آمده از این فراتحلیل با real-time quantitative PCR بر روی ژن‏های پراکسیداز 47، OsDSSR1، homeobox-leucine zipper protein و یک ژن ناشناخته تایید شد. این یافته‏ها به طور قابل توجهی درک ما را از مسیر تنش خشکی بهبود می‏دهد. شناسایی ژن‏های مرکزی در این مطالعه می‏تواند برای به دست آوردن یک نمای کلی از ژن‏های مرکزی که نقش مهمی در پاسخ به تنش خشکی در برنج دارند، موثر باشد.
نتیجه‏گیری: شناسایی ژن‏های پایین دست ژن مرکزی می‏تواند در تهیه برنج متحمل به تنش خشکی از طریق روش‏های اصلاحی کلاسیک با هرمی‏سازی این ژن‏ها یا از طریق دستکاری ژنوم کمک نماید و تحمل به تنش خشکی را افزایش دهد و در نتیجه منجر به کشاورزی پایدار شود.

کلیدواژه‌ها


عنوان مقاله [English]

Identification of key genes effective in tolerance to drought stress in rice through meta-analysis of microarray data

نویسندگان [English]

  • Sedigheh Soltanpour 1
  • Alireza Tarinejad 2
  • Karim Hasanpur 3
  • Mohammad Majidi 4
1 Department of Biotechnology, Faculty of Agriculture, Azarbaijan Shahid Madani University, Tabriz, Iran
2 Associate Professor, Department of Biotechnology, Faculty of Agriculture, Azarbaijan Shahid Madani University, Tabriz, Iran
3 Associate Professor, Department of Animal Science, Faculty of Agriculture, University of Tabriz, Tabriz, Iran
4 Assistant Professor, Department of Biotechnology, Faculty of Agriculture, Azarbaijan Shahid Madani University, Tabriz, Iran
چکیده [English]

Objective
Environmental stresses such as drought, high temperature, salinity and high CO2 are a serious threat to sustainable agriculture. Drought stress is one of the most important abiotic stresses in rice, which causes a decrease in crop yield. Several researches have been carried out separately to clarify the molecular mechanism of plant response to drought stress. Therefore, meta-analysis can lead to a better understanding of drought stress tolerance mechanisms by integrating the results of several related studies.
Materials and Methods
In this regard, four series of good quality microarray data of rice under drought stress and normal condition were selected and then analyzed by R software limma packages. For meta-analysis were used of meta-RNAseq package and Fisher's method to combine p-values obtained from individual data analysis. Up and down regulated meta-analysis genes under drought stress were identified. Then, Gene ontology, hub genes and Co-expression network analysis were performed. The results were evaluated using real-time quantitative PCR test in Hashemi rice as sensitive variety and native rice as tolerant variety to water deficit stress in vitro with PEG treatment.
Results
The results of present study, 578 up-regulated genes and 660 down-regulated genes were obtained. Gene ontology (GO) analysis showed drought response mechanisms and drawing the protein-protein interaction network revealed that the down regulated hub genes under drought stress is mainly related to photosynthesis process and up regulated hub genes under drought stress mainly related to stress tolerance including HSP, LEAs, PP2Cs genes. Finally, the data obtained from the present meta-analysis were confirmed by real-time quantitative PCR on peroxidase 47, OsDSSR1, homeobox-leucine zipper protein and an unknown gene. These findings significantly improve our understanding of drought stress pathway. Identification of hub genes in this study can be effective to obtain an overview of hub genes that play an important role in response to drought stress in rice
Conclusion
Identifying downstream of hub genes can help in the production of drought-tolerant rice through classical breeding methods by pyramiding genes or genome manipulation and increase tolerance to drought stress.The result will lead to sustainable agriculture.

کلیدواژه‌ها [English]

  • meta-analysis
  • microarray
  • drought stress
  • hub genes
  • sustainable agriculture
عرب پور رق آبادی زهرا، محمدآبادی محمدرضا، خضری امین (1400) الگوی بیانی ژن p32 در بافت‌های ران، دست، راسته و چربی پشت بره کرمانی. مجله بیوتکنولوژی کشاورزی، 13(4)، 183-200.
محمدآبادی محمدرضا (1399) بیان ژن ESR1 در بز کرکی راینی با استفاده از real time PCR‎. مجله بیوتکنولوژی کشاورزی 12(1)، 192-177.
محمدآبادی محمدرضا (1399) پروفایل بیانیmRNA مختص بافت ژن ESR2 در بز. مجله بیوتکنولوژی کشاورزی 12(4)، 184-169.
محمدآبادی محمدرضا، سفلایی محمد (1399). پروفایل بیانی mRNA مختص بافت ژن BMP15 در بز. مجله بیوتکنولوژی کشاورزی 12(3)، 208-191.
محمدآبادی محمدرضا، کرد محبوبه، نظری محمود (1397) مطالعه بیان ژن لپتین در بافت‌های مختلف گوسفند کرمانی با استفاده از real time PCR. مجله بیوتکنولوژی کشاورزی 10(3)، 122-111.
References
Ahuja I, de Vos RC, Bones AM, Hall RD (2010) Plant molecular stress responses face climate change. Trends Plant Sci 15, 664-674.
Ali F, Bano A, Fazal A (2017) Recent methods of drought stress tolerance in plants. Plant Growth Regul 82, 363-375.
Arabpour Z, Mohammadabadi M, Khezri A (2021) The expression pattern of p32 gene in femur, humeral muscle, back muscle and back fat tissues of Kermani lambs. Agric Biotechnol J 13 (4), 183-200 (In Persian).
Alvarez S, Roy Choudhury S, Pandey S (2014) Comparative quantitative proteomics analysis of the ABA response of roots of drought-sensitive and drought-tolerant wheat varieties identifies proteomic signatures of drought adaptability. J Proteome Res 13, 1688-1701.
Bhattacharjee A, Sharma R, Jain M (2017) Over-expression of OsHOX24 confers enhanced susceptibility to abiotic stresses in transgenic rice via modulating stress-responsive gene expression. Front Plant Sci 8, 628.
Bhardwaj J, Chauhan R, Swarnkar MK et al. (2013) Comprehensive transcriptomic study on horse gram (Macrotyloma uniflorum): De novo assembly, functional characterization and comparative analysis in relation to drought stress. BMC Genom 14, 1-18.
Bielsa B, Leida C, Rubio-Cabetas MJ (2016) Physiological characterization of drought stress response and expression of two transcription factors and two LEA genes in three Prunus genotypes. Sci Hortic 213, 260-269.
Chin C-H, Chen S-H, Wu H-H et al. (2014) cytoHubba: identifying hub objects and sub-networks from complex interactome. BMC Syst Biol 8, 1-7.
Devi KU, Sridevi V, Mohan CM et al. (2005) Effect of high temperature and water stress on in vitro germination and growth in isolates of the entomopathogenic fungus Beauveria bassiana (Bals.) Vuillemin. J Invertebr Pathol 88, 181-189.
Ding X, Li X, Xiong L (2013) Insight into differential responses of upland and paddy rice to drought stress by comparative expression profiling analysis. Int J Mol Sci 14, 5214-5238.
Farooq M, Hussain M, Wahid A, Siddique K (2012) Drought stress in plants: an overview. Springer. E Yu pp. 1-33.
Gao W, Zhang Y, Feng Z et al. (2018) Effects of melatonin on antioxidant capacity in naked oat seedlings under drought stress. Mol 23, 1580.
González-Gordo S, Bautista R, Claros MG et al. (2019) Nitric oxide-dependent regulation of sweet pepper fruit ripening. J Exp Bot 70, 4557-4570.
Grennan AK (2006) Abiotic stress in rice. An “omic” approach. Plant Physiol 140, 1139-1141.
Haider MS, Kurjogi MM, Khalil-Ur-Rehman M et al. (2017) Grapevine immune signaling network in response to drought stress as revealed by transcriptomic analysis. Plant Physiol Biochem 121, 187-195.
Hsieh W-P, Hsieh H-L, Wu S-H (2012) Arabidopsis bZIP16 transcription factor integrates light and hormone signaling pathways to regulate early seedling development. Plant Cell 24, 3997-4011.
Huang D, Ma M, Wang Q et al. (2020) Arbuscular mycorrhizal fungi enhanced drought resistance in apple by regulating genes in the MAPK pathway. Plant Physiol Biochem 149, 245-255.
Jangam AP, Pathak RR, Raghuram N (2016) Microarray analysis of rice d1 (RGA1) mutant reveals the potential role of G-protein alpha subunit in regulating multiple abiotic stresses such as drought, salinity, heat, and cold. Front Plant Sci 7, 11.
Ji Y, Tu P, Wang K et al. (2014) Defining reference genes for quantitative real-time PCR analysis of anther development in rice. ABBS 46, 305-312.
Kaever A, Landesfeind M, Feussner K et al. (2014) Meta-analysis of pathway enrichment: combining independent and dependent omics data sets. PloS one 9, e89297.
Karaba A, Dixit S, Greco R et al. (2007) Improvement of water use efficiency in rice by expression of HARDY, an Arabidopsis drought and salt tolerance gene. Proc Natl Acad Sci 104, 15270-15275.
Kim D-W, Shibato J, Agrawal GK et al. (2007) Gene transcription in the leaves of rice undergoing salt-induced morphological changes (Oryza sativa L.). Mol Cells 24, 45-49
Le DT, Nishiyama R, Watanabe Y et al. (2012) Differential gene expression in soybean leaf tissues at late developmental stages under drought stress revealed by genome-wide transcriptome analysis. PloS one 7, e49522.
Li Y-Y, Meng D, Li M, Cheng L (2016) Genome-wide identification and expression analysis of the bZIP gene family in apple (Malus domestica). Tree Genet Genomes 12, 1-17.
Liang Y, Tabien RE, Tarpley L et al. (2021) Transcriptome profiling of two rice genotypes under mild field drought stress during grain-filling stage. AoB Plants 13: plab043.
Liu C, Mao B, Ou S et al. (2014) OsbZIP71, a bZIP transcription factor, confers salinity and drought tolerance in rice. Plant Mol Biol 84, 19-36.
Livak KJ, Schmittgen TD (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2− ΔΔCT method. Methods 25, 402-408.
Ma X, Xia H, Liu Y et al. (2016) Transcriptomic and metabolomic studies disclose key metabolism pathways contributing to well-maintained photosynthesis under the drought and the consequent drought-tolerance in rice. Front Plant Sci 7, 1886.
Magwanga RO, Lu P, Kirungu JN, Lu H et al. (2018) Characterization of the late embryogenesis abundant (LEA) proteins family and their role in drought stress tolerance in upland cotton. BMC Genet 19, 1-31.
Masoudzadeh SH, Mohammadabadi MR, Khezri A, et al. (2020) Dlk1 gene expression in different Tissues of lamb. Iran J Appl Anim Sci 10 (4), 669-677.
Mohammadabadi M (2021) Tissue-specific mRNA expression profile of ESR2 gene in goat. Agric Biotechnol J 12 (4), 167-181 (In Persian).
Mohammadabadi M, Masoudzadeh SH, Khezri A, et al. (2021) Fennel (Foeniculum vulgare) seed powder increases Delta-Like Non-Canonical Notch Ligand 1 gene expression in testis, liver, and humeral muscle tissues of growing lambs. Heliyon 7 (12), e08542.
Mohammadabadi M, Soflaei M (2020) Tissue-specific mRNA expression profile of BMP15 gene in goat. Agric Biotechnol J 12, 191-208 (In Persian).
Mohammadabadi MR (2020) Expression of ESR1 gene in Raini Cashmere goat using Real Time PCR. Agric Biotechnol J 12 (1), 177-192 (In Persian).
Mohammadabadi MR, Kord M, Nazari M (2018) Studying expression of leptin gene in different tissues of Kermani Sheep using Real Time PCR. Agric Biotechnol J 10, 111-122 (In Persian).
Safaei SMH, Dadpasand M, Mohammadabadi M, et al. (2022) An Origanum majorana Leaf Diet Influences Myogenin Gene Expression, Performance, and Carcass Characteristics in Lambs. Animals 13 (1), e14.
Rabbani MA, Maruyama K, Abe H, Khan MA et al. (2003) Monitoring expression profiles of rice genes under cold, drought, and high-salinity stresses and abscisic acid application using cDNA microarray and RNA gel-blot analyses. Plant Physiol 133, 1755-1767.
Ransbotyn V, Yeger‐Lotem E, Basha O et al. (2015). A combination of gene expression ranking and co‐expression network analysis increases discovery rate in large‐scale mutant screens for novel Arabidopsis thaliana abiotic stress genes. Plant Biotechnol J 13, 501-513.
Razi K, Muneer S (2021) Drought stress-induced physiological mechanisms, signaling pathways and molecular response of chloroplasts in common vegetable crops. Crit Rev Biotechnol 1-40.
Safaei SMH, Dadpasand M, Mohammadabadi M, et al. (2022) An Origanum majorana Leaf Diet Influences Myogenin Gene Expression, Performance, and Carcass Characteristics in Lambs. Animals 13 (1), e14.
Shaar-Moshe L, Hübner S, Peleg Z (2015) Identification of conserved drought-adaptive genes using a cross-species meta-analysis approach. BMC Plant Biol 15, 111.
Shahsavari M, Mohammadabadi M, Khezri A, et al. (2022) Effect of Fennel (Foeniculum Vulgare) Seed Powder Consumption on Insulin-like Growth Factor 1 Gene Expression in the Liver Tissue of Growing Lambs. Gene Expr 21 (2), 21-26.
Sharma R, Singh G, Bhattacharya S, Singh A (2018) Comparative transcriptome meta-analysis of Arabidopsis thaliana under drought and cold stress. PloS one 13, e0203266.
Sharma M, Singh A, Shankar A et al. (2014) Comprehensive expression analysis of rice Armadillo gene family during abiotic stress and development. DNA Res 21, 267-283.
Shinozaki K, Yamaguchi-Shinozaki K (2007) Gene networks involved in drought stress response and tolerance. J Exp Bot 58, 221-227.
Tseng GC, Ghosh D, Feingold E (2012) Comprehensive literature review and statistical considerations for microarray meta-analysis. Nucleic Acids Res 40, 3785-3799.
Wang W, Vinocur B, Shoseyov O, Altman A (2004) Role of plant heat-shock proteins and molecular chaperones in the abiotic stress response. Trends Plant Sci 9, 244-252.
Wang X-S, Zhu H-B, Jin G-L et al. (2007) Genome-scale identification and analysis of LEA genes in rice (Oryza sativa L.). Plant Sci 172, 414-420.
Waseem M, Ali A, Tahir M et al. (2011) Mechanism of drought tolerance in plant and its management through different methods. CJAgricSci 5, 10-25.
Xu K, Chen S, Li T et al. (2021) Overexpression of OsHMGB707, a high mobility group protein, enhances rice drought tolerance by promoting stress-related gene expression. Front Plant Sci 12, 711271.
Yang G, Wang Y, Zhang K, Gao C (2014) Expression analysis of nine small heat shock protein genes from Tamarix hispida in response to different abiotic stresses and abscisic acid treatment. Mol Biol Rep 41, 1279-1289.
Yoshimura K, Masuda A, Kuwano M et al. (2008) Programmed proteome response for drought avoidance/tolerance in the root of a C3 xerophyte (wild watermelon) under water deficits. Plant Cell Physiol 49, 226-241.
Zong W, Tang N, Yang J et al. (2016) Feedback regulation of ABA signaling and biosynthesis by a bZIP transcription factor targets drought-resistance-related genes. Plant Physiol 171, 2810-2825.