تجزیه و تحلیل شبکه هم بیانی mRNA- lncRNA در لوبیا (Phaseolus vulgaris L.) تحت تنش شوری

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، گروه مهندسی تولید و ژنتیک گیاهی، دانشکده کشاورزی، دانشگاه لرستان، خرم آباد، ایران.

2 استاد، گروه مهندسی تولید و ژنتیک گیاهی، دانشکده کشاورزی، دانشگاه لرستان، خرم آباد، ایران.

3 استادیار، گروه مهندسی تولید و ژنتیک گیاهی، دانشکده کشاورزی، دانشگاه لرستان، خرم آباد، ایران

چکیده

هدف: تنش شوری به عنوان یکی از مهمترین تنش‌های محیطی، به‌طور گسترده بر رشد و بهره‌وری و در مجموع بر عملکرد اغلب محصولات زراعی از جمله لوبیا ‌(Phaseolus vulgaris) تأثیر منفی دارد. با این حال، گیاهان با استفاده از طیف وسیعی از مکانیسم‌های مولکولی، از جمله تنظیم بیان ژن‌ها در سطوح مختلف به تنش شوری پاسخ می‌دهند. هر چند مکانیسم عمل و خصوصیات مولکولی RNA‌های بلند غیرکدکننده‌‌lncRNAs) ) در بسیاری از گیاهان ناشناخته باقی مانده است؛ با این حال نقش این عناصر به عنوان یکی از مؤثرترین عوامل ژنتیکی در تنظیم بیان ژن‌‌‌ها در پاسخ به انواع مختلفی از تنش‌های غیرزیستی اثبات شده است. در پژوهش حاضر با شناسایی LncRNA‌‌‌ها در گیاه لوبیا و ترسیم شبکه هم بیانی mRNA-LncRNA به بررسی نقش احتمالی این عناصر تنظیمی در پاسخ به تنش شوری پرداخته شد.
مواد و روش‌ها: داده‌های حاصل از توالی‌یابی RNA گیاه لوبیا تحت تنش شوری برای شناسایی ‌lncRNAها و تحلیل‌های بیوانفورماتیکی مربوط به شبکه هم‌بیانی مورد استفاده قرار گرفتند. پس از پردازش داده‌‌‌ها و نقشه‌یابی خوانش‌های تمیز شده علیه ژنوم لوبیا از خوانش‌های نقشه‌یابی نشده برای شناسایی lncRNA استفاده شد. علاوه بر این تغییرات بیان نسبی برخی از توالی‌های شناسایی شده نیز از طریق واکنش qRT-PCR سنجش شد. برای اعمال تنش شوری از گیاهچه‌های سه‌برگی در دو گروه شاهد و تیمار تنش شوری ‌(150 میلی مولار) استفاده شد و نمونه‌برداری از برگ گیاهان 72 ساعت پس از اعمال تنش صورت گرفت.
نتایج: در مجموع 2640 توالی به‌عنوان lncRNA در برگ لوبیا تحت تنش شوری شناسایی شد که 195 مورد از آن‌ها در سه پایگاه lncRNA گیاهی ثبت شده بودند. از میان آن‌ها سه lncRNA دارای بیان افتراقی معنی‌دار بودند. تحلیل شبکه هم‌بیانی نشان داد که این ‌lncRNAها با 581 ژن هم‌بیان بوده و 9 ژن به‌طور مستقیم هدف آن‌ها بودند. بررسی عملکردی این ژن‌ها نقش آن‌ها را در مسیرهایی چون بیوسنتز فلاونوئیدها، ریبوزوم، لیپید و فتوسنتز تأیید کرد.
نتیجه‌گیری: به‌طورکلی پژوهش حاضر اولین گزارش از شناسایی lncRNA‌‌‌ها در لوبیا تحت تنش شوری محسوب‌ می‌شود. این پژوهش به درک عمیق‌تری از مکانیسم‌های تنظیمی مرتبط با تحمل شوری در گیاه لوبیا کمک می‌کند و دیدگاه‌های جدیدی برای تحقیقات آینده در این حوزه فراهم می‌آورد.

کلیدواژه‌ها

عنوان مقاله [English]

Co-expression network analysis of mRNA-lncRNA in common bean (Phaseolus vulgaris) under salt stress

نویسندگان [English]

  • Setareh Mirzavand 1
  • Ahmad Ismaili 2
  • Seyed Sajad Sohrabi 3
1 Ph.D. Student, Department of Plant Production and Genetic Engineering, Faculty of Agriculture, Lorestan University, Khorramabad, Iran.
2 Professor, Department of Plant Production and Genetic Engineering, Faculty of Agriculture, Lorestan University, Khorramabad, Iran.
3 Assistant Professor, Department of Plant Production and Genetic Engineering, Faculty of Agriculture, Lorestan University, Khorramabad, Iran
چکیده [English]

Objective
Salinity stress, as one of the most important environmental stresses, has a widespread negative impact on the growth, productivity, and overall yield of most crops, including common bean (Phaseolus vulgaris). However, plants respond to salinity through a wide range of molecular mechanisms, including the regulation of gene expression at multiple levels. Although the mode of action and molecular characteristics of long non-coding RNAs (lncRNAs) remain unknown in many plant species, their role as one of the most influential genetic factors in regulating gene expression in response to various abiotic stresses has been well established. In the present study, lncRNAs were identified in common bean, and an mRNA–lncRNA co-expression network was constructed to investigate the potential regulatory roles of these elements in the salinity stress response.
Materials and methods
RNA-seq data from common bean under salinity stress were used to identify lncRNAs and perform bioinformatic analyses of the co-expression network. After data processing and mapping of clean reads to the bean genome, unmapped reads were used for lncRNA identification. In addition, the relative expression changes of selected identified sequences were validated by qRT-PCR. Salinity stress (150 mM) was applied to bean seedlings at the first trifoliate stage in two groups (control and stress-treated), and leaf samples were collected 72 hours after stress application.
Results
A total of 2,640 sequences were identified as lncRNAs in bean leaves under salinity stress, of which 195 were recorded in three plant lncRNA databases. Among them, three lncRNAs showed significant differential expression. Co-expression network analysis revealed that these lncRNAs were co-expressed with 581 genes, with nine genes being direct targets. Functional analysis of these genes confirmed their roles in pathways such as flavonoid biosynthesis, ribosome, lipid metabolism, and photosynthesis.
Conclusions
Overall, this study is the first report on the identification of lncRNAs in common bean under salinity stress. The findings contribute to a deeper understanding of regulatory mechanisms associated with salinity tolerance in common bean and provide new insights for future research in this field.

کلیدواژه‌ها [English]

  • gene expression
  • non-coding sequences
  • regulatory sequence
  • stress-responsive genes

مراجع

 
Alavi, M., Mozafari, M., Ghaemi, S., Ashengroph, M., Hasanzadeh Davarani, F., & Mohammadabadi, M. (2022). Interaction of epigallocatechin gallate and quercetin with spike glycoprotein (S-glycoprotein) of SARS-CoV-2: In silico study. Biomedicines, 10(12), 3074. https://doi.org/10.3390/biomedicines10123074 
Amiri Roudbar, M., Mohammadabadi, M. R., Ayatollahi Mehrgardi, A., Abdollahi-Arpanahi, R., Momen, M., Morota, G., Brito Lopes, F., Gianola, D., & Rosa, G. J. (2020). Integration of single nucleotide variants and whole-genome DNA methylation profiles for classification of rheumatoid arthritis cases from controls. Heredity, 124(5), 658-674. https://doi.org/https://doi.org/10.1038/s41437-020-0301-4  
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. Agricultural Biotechnology Journal, 13(4), 183-200. https://doi.org/10.22103/jab.2022.18782.1371  
Athar, H. U. R., Zulfiqar, F., Moosa, A., Ashraf, M., Zafar, Z. U., Zhang, L., Ahmed, N., Kalaji, H. M., Nafees, M., Hossain, M. A., Islam, M. S., El Sabagh, A., & Siddique, K. H. M. (2022). Salt stress proteins in plants: An overview [Review]. Front Plant Sci, 13. https://doi.org/10.3389/fpls.2022.999058 
Bhardwaj, R., Sharma, I., Kanwar, M., Sharma, R., Handa, N., Kaur, H., Kapoor, D., & Poonam. (2013). LEA Proteins in Salt Stress Tolerance. In P. Ahmad, M. M. Azooz, & M. N. V. Prasad (Eds.), Salt Stress in Plants: Signalling, Omics and Adaptations. Springer New York, 79-112. https://doi.org/10.1007/978-1-4614-6108-1_5 
Bouzroud, S., Henkrar, F., Fahr, M., & Smouni, A. (2023). Salt stress responses and alleviation strategies in legumes: a review of the current knowledge. 3 Biotech, 13(8), 287. https://doi.org/https://doi.org/10.1007/s13205-023-03643-7 
Carbas, B., Machado, N., Oppolzer, D., Ferreira, L., Queiroz, M., Brites, C., Rosa, E. A., & Barros, A. I. (2020). Nutrients, antinutrients, phenolic composition, and antioxidant activity of common bean cultivars and their potential for food applications. Antioxidants, 9(2), 186. https://doi.org/10.3390/antiox9020186  
Chand Jha, U., Nayyar, H., Mantri, N., & Siddique, K. H. (2021). Non-coding RNAs in legumes: their emerging roles in regulating biotic/abiotic stress responses and plant growth and development. Cells, 10(7), 1674. https://doi.org/https://doi.org/10.3390/cells10071674 
Chandran, A. K. N., Kim, J. W., Yoo, Y. H., Park, H. L., Kim, Y. J., Cho, M. H., & Jung, K. H. (2019). Transcriptome analysis of rice-seedling roots under soil–salt stress using RNA-Seq method. Plant Biotechnology Reports, 13(6), 567-578. https://doi.org/10.1007/s11816-019-00550-3 
Chin, C. H., Chen, S. H., Wu, H. H., Ho, C. W., Ko, M. T., & Lin, C. Y. (2014). cytoHubba: identifying hub objects and sub-networks from complex interactome. BMC Systems Biology, 8, 1-7. https://doi.org/10.1186/1752-0509-8-S4-S11 
Conesa, A., Madrigal, P., Tarazona, S., Gomez-Cabrero, D., Cervera, A., McPherson, A., Szcześniak, M. W., Gaffney, D. J., Elo, L. L., & Zhang, X. (2016). A survey of best practices for RNA-seq data analysis. Genome Biology, 17(1), 13. https://doi.org/10.1186/s13059-016-0881-8 
Das, P., Agarwala, N., Gill, S. S., & Varshney, R. K. (2023). Emerging role of plant long non coding RNAs (lncRNAs) in salinity stress response. Plant Stress, 100-265. https://doi.org/10.1016/j.plst.2023.100265 
Deng, F., Zhang, X., Wang, W., Yuan, R., & Shen, F. (2018). Identification of Gossypium hirsutum long non-coding RNAs (lncRNAs) under salt stress. BMC Plant Biology, 18(1), 23. https://doi.org/10.1186/s12870-018-1238-0 
Di Marsico, M., Paytuvi Gallart, A., Sanseverino, W., & Aiese Cigliano, R. (2022). GreeNC 2.0: a comprehensive database of plant long non-coding RNAs. Nucleic Acids Research, 50(D1), D1442-D1447. https://doi.org/https://doi.org/10.1093/nar/gkab1170 
El-Beltagi, H. S., Al-Otaibi, H. H., Parmar, A., Ramadan, K. M., Lobato, A. K. D. S., & El-Mogy, M. M. (2023). Application of potassium humate and salicylic acid to mitigate salinity stress of common bean. Life, 13(2), 448. https://doi.org/10.3390/life13020448 
Garcia, C. L., Dattamudi, S., Chanda, S., & Jayachandran, K. (2019). Effect of salinity stress and microbial inoculations on glomalin production and plant growth parameters of snap bean (Phaseolus vulgaris). Agronomy, 9(9), 545. https://doi.org/https://doi.org/10.3390/agronomy9090545 
Gong, H., You, J., Zhang, X., Liu, Y., Zhao, F., Cui, X., & Zhang, Y. (2021). Genome-wide identification and functional analysis of long non-coding RNAs in sesame response to salt stress. Journal of Plant Biology, 64(6), 555-565. https://doi.org/10.1007/s12374-021-09324-3 
Hajalizadeh, Z., Dayani, O., Khezri, A., Tahmasbi, R., Mohammadabadi, M., Solodka, T., Kalashnyk, O., Afanasenko, V., & Babenko, O. (2021). Expression of calpastatin gene in Kermani sheep using real-time PCR. Journal of Livestock Science and Technologies, 9(2), 57-51. https://doi.org/10.22103/jlst.2021.18165.1381 
Heidarpour, F., Mohammadabadi, M., Zaidul, I., Maherani, B., Saari, N., Hamid, A., Abas, F., Manap, M., & Mozafari, M. (2011). Use of prebiotics in oral delivery of bioactive compounds: a nanotechnology perspective. Die Pharmazie-An International Journal of Pharmaceutical Sciences, 66(5), 319-324. https://doi.org/https://pubmed.ncbi.nlm.nih.gov/21699064 
Hernández, J. A. (2019). Salinity tolerance in plants: trends and perspectives. International Journal of Molecular Sciences, 20(10), 2408. https://doi.org/10.3390/ijms20102408 
Hou, J., Lu, D., Mason, A. S., Li, B., Xiao, M., An, S., & Fu, D. (2019). Non-coding RNAs and transposable elements in plant genomes: emergence, regulatory mechanisms and roles in plant development and stress responses. Planta, 250, 23-40. https://doi.org/10.1007/s00425-019-03110-y 
Huang, H., Ullah, F., Zhou, D. X., Yi, M., & Zhao, Y. (2019). Mechanisms of ROS regulation of plant development and stress responses. Frontiers in Plant Science, 10, 800. https://doi.org/10.3389/fpls.2019.00800  
Jan, R., Kim, N., Lee, S. H., Khan, M. A., Asaf, S., Lubna, Park, J. R., Asif, S., Lee, I. J., & Kim, K. M. (2021). Enhanced Flavonoid Accumulation Reduces Combined Salt and Heat Stress Through Regulation of Transcriptional and Hormonal Mechanisms. Frontiers in Plant Science, 12:796956. https://doi.org/10.3389/fpls.2021.796956 
Jannesar, M., Seyedi, S. M., & Botanga, C. (2024). Crosstalk between long non-coding RNAs and miRNAs regulates transferase activities in response to salt stress in Pistachio (Pistacia vera L.). Plant Stress, 12, 100474. https://doi.org/10.1016/j.plst.2023.100474 
Jia, J., Wang, F., Yuan, M., Wang, Z., Qin, Z., Zhang, X., Shao, Y., & Pei, H. (2025). Transcriptomic Analysis Reveals That the Photosynthesis and Carotenoid Metabolism Pathway Is Involved in the Salinity Stress Response in Brassica rapa L. ssp. Pekinensis. Plants, 14(4), 566. https://doi.org/https://doi.org/10.3390/plants14040566 
Jiang, C., Wang, Y., He, Y., Peng, Y., Xie, L., Li, Y., Sun, W., Zhou, J., Zheng, C., & Xie, X. (2024). Identification and Characterization of miRNAs and lncRNAs Associated with Salinity Stress in Rice Panicles. International Journal of Molecular Sciences, 25(15), 8247. https://doi.org/10.3390/ijms25158247
Jin, J., Lu, P., Xu, Y., Li, Z., Yu, S., Liu, J., Wang, H., Chua, N. H., & Cao, P. (2021). PLncDB V2. 0: a comprehensive encyclopedia of plant long noncoding RNAs. Nucleic Acids Research, 49(D1), D1489-D1495. https://doi.org/10.1093/nar/gkaa910 
Kang, Y. J., Yang, D. C., Kong, L., Hou, M., Meng, Y. Q., Wei, L., & Gao, G. (2017). CPC2: a fast and accurate coding potential calculator based on sequence intrinsic features. Nucleic Acids Research, 45(W1), W12-W16. https://doi.org/10.1093/nar/gkx428 
Khabiri, A., Toroghi, R., Mohammadabadi, M., & Tabatabaeizadeh, S. E. (2023). Introduction of a Newcastle disease virus challenge strain (sub-genotype VII. 1.1) isolated in Iran. Veterinary Research Forum, 14(4), 221. https://doi.org/10.30466/vrf.2022.548152.3373 
Kumar, N., Bharadwaj, C., Sahu, S., Shiv, A., Shrivastava, A. K., Reddy, S. P. P., Soren, K. R., Patil, B. S., Pal, M., & Soni, A. (2021). Genome-wide identification and functional prediction of salt-stress related long non-coding RNAs (lncRNAs) in chickpea (Cicer arietinum L.). Physiology and Molecular Biology of Plants, 27, 2605-2619. https://doi.org/10.1007/s12298-021-00996-9 
Li, J., Ma, W., Zeng, P., Wang, J., Geng, B., Yang, J., & Cui, Q. (2015). LncTar: a tool for predicting the RNA targets of long noncoding RNAs. Briefings in bioinformatics, 16(5), 806-812. https://doi.org/10.1093/bib/bbu048 
Liu, J., Wang, H., & Chua, N. H. (2015). Long noncoding RNA transcriptome of plants. Plant Biotechnology Journal, 13(3), 319-328. https://doi.org/10.1111/pbi.12229 
Liu, P., Zhang, Y., Zou, C., Yang, C., Pan, G., Ma, L., & Shen, Y. (2022). Integrated analysis of long non-coding RNAs and mRNAs reveals the regulatory network of maize seedling root responding to salt stress. BMC Genomics, 23, 1-16. https://doi.org/10.1186/s12864-022-08520-0  
Livak, K. J., & Schmittgen, T. D. (2001). Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT method. Methods, 25(4), 402-408. https://doi.org/10.1006/meth.2001.1262 
Lowe, T. M., & Chan, P. P. (2016). tRNAscan-SE On-line: integrating search and context for analysis of transfer RNA genes. Nucleic Acids Research, 44(W1), W54-W57. https://doi.org/10.1093/nar/gkw413 
Ma, L., Bajic, V. B., & Zhang, Z. (2013). On the classification of long non-coding RNAs. RNA Biology, 10(6), 924-933. https://doi.org/10.4161/rna.24604 
Mahajan, R., Nazir, M., Sayeed, N., Rai, V., Mushtaq, R., Masoodi, K. Z., Wani, S. A., Urwat, U., Rasool, S., Salgotra, R. K., & Zargar, S. M. (2017). Unraveling the abiotic stress tolerance in common bean through omics. In Plant OMICS and Crop Breeding (pp. 311-365). https://doi.org/10.1201/9781315365930 
Mehralizade, Z., Soorni, A., & Meratian Esfahani, S. (2024). Regulatory Network of Spinach Under Salt Stress: An Integrated Study of Long Non-coding RNAs and mRNAs. Journal of Plant Growth Regulation, 44, 1-17. https://doi.org/10.1007/s00344-024-11546-x 
Mohammadabadi, M., & Asadollahpour Nanaei, H. (2021). Leptin gene expression in Raini Cashmere goat using Real Time PCR. Agricultural Biotechnology Journal, 13(1), 197-214. https://doi.org/10.22103/jab.2021.17334.1305 
Mohammadabadi, M., Afsharmanesh, M., Khezri, A., Kheyrodin, H., Babenko Ivanivna, O., Borshch, O., Kalashnyk, O., Nechyporenko, О., Afanasenko, V., & Slynko, V. (2025). Effect of mealworm on GBP4L gene expression in the spleen tissue of Ross broiler chickens. Agricultural Biotechnology Journal, 17(2), 343-360. https://doi.org/https://doi.org/10.22103/jab.2025.25277.1714 
Mohammadabadi, M., Babenko, I. O., Borshch, O., Kalashnyk, O., Ievstafiieva, Y., & Buchkovska, V. (2024). Measuring the relative expression pattern of the UCP2 gene in different tissues of the Raini Cashmere goat. Agricultural Biotechnology Journal, 16(3), 317-332. https://doi.org/10.22103/jab.2024.24337.1627 
Mohammadabadi, M., Golkar, A., & Askari Hesni, M. (2023). The effect of fennel (Foeniculum vulgare) on insulin-like growth factor 1 gene expression in the rumen tissue of Kermani sheep. Agricultural Biotechnology Journal, 15, 239-256. https://doi.org/10.22103/jab.2023.22647.1530 
Mohammadabadi, M., Kheyrodin, H., Latifi, A., & Babenko Ivanivna, O. (2022). mRNA expression profile of DNAH1 gene in testis tissue of Raini Cashmere goat. Agricultural Biotechnology Journal, 14(3), 243-256. https://doi.org/10.22103/jab.2022.20199.1428 
Netondo, G. W., Onyango, J. C., & Beck, E. (2004). Sorghum and salinity: II. Gas exchange and chlorophyll fluorescence of sorghum under salt stress. Crop Science, 44(3), 806-811. https://doi.org/10.2135/cropsci2004.8060 
Niron, H., Barlas, N., Salih, B., & Türet, M. (2020). Comparative transcriptome, metabolome, and ionome analysis of two contrasting common bean genotypes in saline conditions. Frontiers in Plant Science, 11, 599501. https://doi.org/10.3389/fpls.2020.599501 
Okay, A., Kırlıoğlu, T., Durdu, Y. Ş., Akdeniz, S. Ş., Büyük, İ., & Aras, E. (2024). Omics approaches to understand the MADS-box gene family in common bean (Phaseolus vulgaris L.) against drought stress. Protoplasma, 261(4), 709-724. https://doi.org/10.1007/s00709-024-01928-z 
Pan, L., Hu, X., Liao, L., Xu, T., Sun, Q., Tang, M., Chen, Z., & Wang, Z. (2023). Lipid metabolism and antioxidant system contribute to salinity tolerance in halophytic grass seashore paspalum in a tissue-specific manner. BMC Plant Biology, 23(1), 337. https://doi.org/10.1186/s12870-023-04358-w 
Parida, A. K., & Das, A. B. (2005). Salt tolerance and salinity effects on plants: a review. Ecotoxicology and Environmental Safety, 60(3), 324-349. https://doi.org/10.1016/j.ecoenv.2004.06.010 
Paytuví Gallart, A., Hermoso Pulido, A., Anzar Martínez de Lagrán, I., Sanseverino, W., & Aiese Cigliano, R. (2016). GREENC: a Wiki-based database of plant lncRNAs. Nucleic Acids Research, 44(D1), D1161-D1166. https://doi.org/10.1093/nar/gkv1215 
Quek, X. C., Thomson, D. W., Maag, J. L., Bartonicek, N., Signal, B., Clark, M. B., Gloss, B. S., & Dinger, M. E. (2015). lncRNAdb v2. 0: expanding the reference database for functional long noncoding RNAs. Nucleic Acids Research, 43(D1), D168-D173. https://doi.org/10.1080/07388551.2022.2093695 
Raza, A., Tabassum, J., Fakhar, A. Z., Sharif, R., Chen, H., Zhang, C., Ju, L., Fotopoulos, V., Siddique, K. H., & Singh, R. K. (2023). Smart reprograming of plants against salinity stress using modern biotechnological tools. Critical Reviews in Biotechnology, 43(7), 1035-1062. https://doi.org/10.1080/07388551.2022.2093695 
Revelle, W., & Revelle, M. W. (2015). Package ‘psych’. The Comprehensive R Archive Network, 337(338). https://doi.org/10.5281/zenodo.34069 
Samarfard, S., Ghorbani, A., Karbanowicz, T. P., Lim, Z. X., Saedi, M., Fariborzi, N., McTaggart, A. R., & Izadpanah, K. (2022). Regulatory non-coding RNA: The core defense mechanism against plant pathogens. Journal of Biotechnology, 359, 82-94. https://doi.org/10.1016/j.jbiotec.2022.04.003 
Sanchita, Trivedi, P. K., & Asif, M. H. (2020). Updates on plant long non-coding RNAs (lncRNAs): the regulatory components. Plant Cell, Tissue and Organ Culture (PCTOC), 140(2), 259-269. https://doi.org/10.1007/s11240-019-01726-z 
Sandalio, L. M. (2022). Insights in plant abiotic stress. Frontiers Media SA, 13, 1085150. https://doi.org/10.3389/fpls.2022.1085150 
Shrivastava, P., & Kumar, R. (2015). Soil salinity: A serious environmental issue and plant growth promoting bacteria as one of the tools for its alleviation. Saudi Journal of Biological Sciences, 22(2), 123-131. https://doi.org/10.1016/j.sjbs.2014.12.001 
Singh, U., Khemka, N., Rajkumar, M. S., Garg, R., & Jain, M. (2017). PLncPRO for prediction of long non-coding RNAs (lncRNAs) in plants and its application for discovery of abiotic stress-responsive lncRNAs in rice and chickpea. Nucleic Acids Research, 45(22), e183-e183. https://doi.org/10.1093/nar/gkx780 
Sun, X., Zheng, H., Li, J., Liu, L., Zhang, X., & Sui, N. (2020). Comparative transcriptome analysis reveals new lncRNAs responding to salt stress in sweet sorghum. Frontiers in Bioengineering and Biotechnology, 8, 331. https://doi.org/10.3389/fbioe.2020.00331 
Szcześniak, M. W., Bryzghalov, O., Ciomborowska-Basheer, J., & Makałowska, I. (2019). CANTATAdb 2.0: expanding the collection of plant long noncoding RNAs. In Plant Long non-coding RNAs: methods and protocols. Springer, 415-429. https://doi.org/10.1007/978-1-4939-8976-8_25 
Van Zelm, E., Zhang, Y., & Testerink, C. (2020). Salt tolerance mechanisms of plants. Annual Review of Plant Biology, 71(1), 403-433. https://doi.org/10.1146/annurev-arplant-050718-100005 
Wang, D., Wu, H., Yu, L., Lu, Z., Pan, L., & Xin, Y. (2025). Identification and functional characterization of lncRNAs and mRNAs in response to salt stress in mulberry. Forestry Research, 5(1). https://doi.org/https://doi.org/10.48130/forres-0025-0006 
Wang, X., Yin, J., Wang, J., & Li, J. (2023). Integrative analysis of transcriptome and metabolome revealed the mechanisms by which flavonoids and phytohormones regulated the adaptation of alfalfa roots to NaCl stress. Frontiers in Plant Science, 14, 1117868. https://doi.org/10.1016/j.jplph.2024.153123 
Wekesa, C., Asudi, G. O., Okoth, P., Reichelt, M., Muoma, J. O., Furch, A. C., & Oelmüller, R. (2022). Rhizobia contribute to salinity tolerance in Common Beans (Phaseolus vulgaris L.). Cells, 11(22), 3628. https://doi.org/https://doi.org/10.3390/cells11223628 
Yang, H., Cui, Y., Feng, Y., Hu, Y., Liu, L., & Duan, L. (2023). Long non-coding RNAs of Plants in response to abiotic stresses and their regulating roles in promoting environmental adaption. Cells, 12(5), 729. https://doi.org/https://doi.org/10.3390/cells12050729 
Yu, R., Li, Z., Rong, M., Yang, G., Xu, X., Wang, G., Xu, Z., Du, X., & Zhang, Q. (2023). Comparative physiology and transcriptome analysis to identify the important coding and non-coding RNAs imparting tolerance to salinity stress in alfalfa (Medicago sativa L). Research Square. https://doi.org/10.21203/rs.3.rs-2500111/v1 
Zahra, N., Al Hinai, M. S., Hafeez, M. B., Rehman, A., Wahid, A., Siddique, K. H. M., & Farooq, M. (2022). Regulation of photosynthesis under salt stress and associated tolerance mechanisms. Plant Physiology and Biochemistry, 178, 55-69. https://doi.org/https://doi.org/10.1016/j.plaphy.2022.03.003 
Zhao, S., Zhang, Q., Liu, M., Zhou, H., Ma, C., & Wang, P. (2021). Regulation of plant responses to salt stress. International journal of Molecular Sciences, 22(9), 4609. https://doi.org/10.3390/ijms22094609 
Zong, X., Wang, S., Han, Y., Zhao, Q., Xu, P., Yan, Q., Wu, F., & Zhang, J. (2021). Genome-wide profiling of the potential regulatory network of lncRNA and mRNA in Melilotus albus under salt stress. Environmental and Experimental Botany, 189, 104548. https://doi.org/10.1016/j.envexpbot.2021.104548 
مجله بیوتکنولوژی کشاورزی
دوره 17، شماره 4
آبان 1404
صفحه 99-122

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