[
Alzahrani SM, Alaraidh IA, Khan MA, Migdadi HM, Alghamdi SS, Alsahli AA (2019) Identification and characterization of salt-responsive microRNAs in Vicia faba by high-throughput sequencing. Genes 10: 303. https://doi.org/10.3390/genes10040303
]Search in Google Scholar
[
Andersen CL, Jensen JL, Ørntoft TF (2004) Normalization of rea-time quantitative reverse transcription-PCR data:A model-based variance estimation approach to identify genes suited for normalization,applied to bladder and colon cancer data sets. Cancer Res 64: 5245-5250. https://doi.org/10.1158/0008-5472.can-04-0496
]Search in Google Scholar
[
Bai Q, Wang X, Chen X, Shi G, Liu Z, Guo C, Xiao K (2018) Wheat miRNA TaemiR408 acts as an essential mediator in plant tolerance to Pi Deprivation and salt stress via modulating stress-associated physiological processes. Front Plant Sci 9: 499. https://doi.org/10.3389/fpls.2018.00499
]Search in Google Scholar
[
Bai S, Wang X, Guo M, Cheng G, Khan A, Yao W, Gao Y, Li J (2022) Selection and Evaluation of Reference Genes for Quantitative Real-Time PCR in Tomato (Solanum lycopersicum L.) Inoculated with Oidium neolycopersici. Agronomy 12(12):3171. https://doi.org/10.3390/agronomy12123171
]Search in Google Scholar
[
Brunner AM, Yakovlev IA, Strauss SH (2004) Validatinginternal controls for quantitative plant gene expression studies. BMC Plant Biol 4: 14. https://doi.org/10.1186/1471-2229-4-14
]Search in Google Scholar
[
Carrió-Seguí À, Ruiz-Rivero O, Villamayor-Belinchón L, Puig S, Perea-García A, Peñarrubia L (2019). The Altered Expression of microRNA408 Influences the Arabidopsis Response to Iron Deficiency. Front Plant Sci 10:324. https://doi.org/10.3389/fpls.2019.00324
]Search in Google Scholar
[
Chen K, Fessehaie A, Arora R (2012) Selection of reference genes for normalizing gene expression during Seed priming and germination using qPCR in Zea mays and Spinacia Oleracea. Plant Mol Biol Rep: 478-487. https://doi.org/10.1007/s11105-011-0354-x
]Search in Google Scholar
[
Covarrubias AA, JOSé LR (2010) Post-transcriptional gene regulation of salinity and drought responses by plant microRNAs. Plant Cell and Environment 33: 481-489. https://doi.org/10.1111/j.1365-3040.2009.02048.x
]Search in Google Scholar
[
Czechowski T, Stitt M, Altmann T, Udvardi MK, Scheible W (2005) Genome-wide identification and testing of superior reference genes for transcript normalization in Arabidopsis. Plant Physiol 139: 5-17. https://doi.org/10.1104/pp.105.063743
]Search in Google Scholar
[
Dheda K, Huggett JF, Bustin SA, Johnson MA, Rook G, Zumla A (2004) Validation of housekeeping genes for normalizing RNA expression in real-time PCR. Biotechniques 37: 112–119. https://doi.org/10.2144/04371rr03
]Search in Google Scholar
[
Dini P, Loux SC, Scoggin KE, Esteller-Vico A, Squires EL, Troedsson MHT, Daels P, Ball BA (2017) Identification of Reference Genes for Analysis of microRNA Expression Patterns in Equine Chorioallantoic Membrane and Serum. Molecular Biotechnology 60: 62-73. https://doi.org/10.1007/s12033-017-0047-2
]Search in Google Scholar
[
Du B, Winkler JB, Ache P, White PJ, Dannenmann M, Alfarraj S, Albasher G, Schnitzler JP, Hedrich R, Rennenberg H (2023) Differences of nitrogen metabolism in date palm (Phoenix dactylifera) seedlings subjected to water deprivation and salt exposure. Tree Physiol 43:587-596 . https://doi.org/10.1093/treephys/tpac145
]Search in Google Scholar
[
Feng H, Huang X, Zhang Q, Wei G, Wang X, Kang Z (2012) Selection of suitable inner reference genes for relative quantification expression of microRNA in wheat. Plant Physiology and Biochemistry 51: 116-122. https://doi.org/10.1016/j.plaphy.2011.10.010
]Search in Google Scholar
[
Guo MW, Zhu L, Li HY, Wu ZN, Li ZY, Li J (2022) Evaluation of reference genes for normalization of mRNA and microRNA expression by RT-qPCR under different experimental conditions in Medicago ruthenica (L.) Ledeb.. Genet Re-sour Crop Evol 69, 587–600 (2022). https://doi.org/10.1007/s10722-021-01243-z
]Search in Google Scholar
[
Gao Z, Ma C, Zheng C, Yao Y, Du Y (2022) Advances in the regulation of plant salt-stress tolerance by miRNA. Mol Biol Rep 49:5041-5055. https://doi.org/10.1007/s11033-022-07179-6
]Search in Google Scholar
[
Feng H, Huang X, Zhang Q, Wei G, Wang X, Kang Z (2012) Selection of suitable inner reference genes for relative quantification expression of microRNA in wheat. Plant Physiol Biochem 51:116–22. https://doi.org/10.1016/j.plaphy.2011.10.010
]Search in Google Scholar
[
Fujii H, Chiou TJ, Lin SI, Aung K, Zhu JK (2005) A miRNA involved in phosphate-starvation response in Arabidopsis. Current Biology 15: 2038-2043. https://doi.org/10.1016/j.cub.2005.10.016
]Search in Google Scholar
[
Fu, R, Zhang M, Zhao Y, He X, Ding C, Wang S, Feng Y, Song X, Li P, Wang B (2017) Identification of salt tolerance-related microRNAs and their targets in maize (Zea mays L.) using high-throughput sequencing and degradome analysis. Front. Plant Sci 8: 864 . https://doi.org/10.3389/fpls.2017.00864
]Search in Google Scholar
[
Jia X, Wang WX, Ren L, Chen QJ, Mendu V, Willcut B, Dinkins R, Tang X, Tang G (2009) Differential and dynamic regulation of miR398 in response to ABA and salt stress in Populus tremula and Arabidopsis thaliana. Plant Molecular Biology 71: 51-59. https://doi.org/10.1007/s11103-009-9508-8
]Search in Google Scholar
[
Jain M, Nijhawan A, Tyagi AK, Khurana JP (2006) Validation of housekeeping genes as internal control for studying gene expression in rice by quantitative real-time PCR. Biochemical & Biophysical Research Communications 345: 646-651. https://doi.org/10.1016/j.bbrc.2006.04.140
]Search in Google Scholar
[
Jeong YM, Mun JH, Lee I, Woo JC, Hong CB, Kim SG (2006) Distinct roles of the first introns on the expression of Arabidopsis profilin gene family members. Plant Physiol 140: 196–209. https://doi.org/10.1104/pp.105.071316
]Search in Google Scholar
[
Jiao Y, Wang Y, Xue D, Wang J, Yan M, Liu G, Dong G, Zeng D, Lu Z, Zhu X, Qian Q, Li J (2010) Regulation of OsSPL14 by OsmiR156 defines ideal plant architecture in rice. Nat Genet 42: 541–544. https://doi.org/10.1038/ng.591
]Search in Google Scholar
[
Jia X, Wang WX, Ren L, Chen QJ, Mendu V, Willcut B, Dinkins R, Tang X, Tang G. (2009) Differential and dynamic regulation of miR398 in response to ABA and salt stress in Populu stremula and Arabidopsis thaliana. Plant Molecular Biology 71: 51-59. https://doi.org/10.1007/s11103-009-9508-8
]Search in Google Scholar
[
Kehr J (2013) Systemic regulation of mineral homeostasis by micro RNAs Front Plant Sci 4: 145. https://doi.org/10.3389/fpls.2013.00145
]Search in Google Scholar
[
Kong Q, Yuan J, Gao L, Zhao S, Jiang W, Huang Y, Bie Z (2014) Identification of suitable reference genes for gene expression normalization in qRT-PCR analysis in watermelon. PLoS One 9: 1-11. https://doi.org/10.1371/journal.pone.0090612
]Search in Google Scholar
[
Kou SJ, Wu XM, Liu YL, Xu Q, Guo WW (2012) Selection and validation of suitable reference genes for miRNA expression normalization by quantitative RTPCR in citrus somatic embryogenic and adult tissues. Plant Cell Reports 31: 2151-2163. https://doi.org/10.1007/s00299-012-1325-x
]Search in Google Scholar
[
Kulcheski FR, Marcelino-Guimaraes FC, Nepomuceno AL, Abdelnoor RV, Marqis R (2010) The use of microRNAs as reference genes for quantitative polymerase chain reaction in soybean. Analytical Biochemistry 406: 185-192. https://doi.org/10.1016/j.ab.2010.07.020
]Search in Google Scholar
[
Li D, Yu S, Zeng M, Liu X, Yang J, Li C (2020) Selection and Validation of Appropriate Reference Genes for Real-Time Quantitative PCR Analysis in Needles of Larix olgensis under Abiotic Stresses. Forests 11(2):193. https://doi.org/10.3390/f11020193
]Search in Google Scholar
[
Li G, Sun X, Zhu X, Wu B, Hong H, Xin Z, Xin X, Peng J, Jiang S (2023) Selection and Validation of Reference Genes in Virus-Infected Sweet Potato Plants Genes (Basel).14(7):1477. https://doi.org/10.3390/genes14071477
]Search in Google Scholar
[
Li MY, Wang F, Jiang Q, Wang GL, Tian C, Xiong AS (2016) Validation and Comparison of Reference Genes for qPCR Normalization of Celery (Apium graveo-lens) at Different Development Stages. Frontiers in Plant Science 7: 313. https://doi.org/10.3389/fpls.2016.00313
]Search in Google Scholar
[
Liu X, Liu S, Zhang J, Wu Y, Wu W, Zhang Y, Liu B, Tang R, He L, Li R, Jia X (2020) Optimization of reference genes for qRT-PCR analysis of microRNA expression under abiotic stress conditions in sweet potato. Plant Physiol. Bioch 154, 379–396. https://doi.org/10.1016/j.plaphy.2020.06.016
]Search in Google Scholar
[
Lin YL, Lai ZX (2013) Evaluation of suitable reference genes for normalization of microRNA expression by real-time reverse transcription PCR analysis during longan somatic embryogenesis. Plant Physiology and Biochemistry 66: 20-25. https://doi.org/10.1016/j.plaphy.2013.02.002
]Search in Google Scholar
[
Livak KJ, Schmittgen TD (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 25: 402-408. https://doi.org/10.1006/meth.2001.1262
]Search in Google Scholar
[
Luan Y, Wang W, Liu P (2014) Identification and functional analysis of novel and conserved microRNAs in tomato. Mol. Biol. Rep 41: 5385–5394. https://doi.org/10.1007/s11033-014-3410-4
]Search in Google Scholar
[
Luo M, Gao Z, Li H, Li Q, Zhang C, Xu W, Song S, Ma C, Wang S (2018) Selection of reference genes for miRNA qRT-PCR under abiotic stress in grapevine. Sci Rep 8:4444. https://doi.org/10.1038/s41598-018-22743-6
]Search in Google Scholar
[
Luo X, Shi Y, Sun H, Song J, Ni Z, Gao Z (2014) Selection of suitable inner reference genes for normalisation of microRNA expression response to abiotic stresses by RT-qPCR in leaves, flowers and young stems of peach. Scientia Horticulturae 165: 281-287. https://doi.org/10.1016/j.scienta.2013.10.030
]Search in Google Scholar
[
Ma J, Wang Y, Li J (2019) Global identification and analysis of microRNAs involved in salt stress responses in two alfalfa (Medicago sativa ‘Millennium’) lines. Can. J. Plant Sci 4: 445–455. https://doi.org/10.1139/cjps-2018-0327
]Search in Google Scholar
[
Miao M, Yang X, Han X, Wang K (2011) Sugar signalling is involved in the sex expression response of monoecious cucumber to low temperature. Journal of Experimental Botany 62: 797-804. https://doi.org/10.1093/jxb/erq315
]Search in Google Scholar
[
Michael MJ, Bowman JL (2008) Evolution of plant microRNAs and their targets. Trends in Plant Science 13: 343-349. https://doi.org/10.1016/j.tplants.2008.03.009
]Search in Google Scholar
[
Mishra S, Sahu G, Shaw BP (2022) Integrative small RNA and transcriptome analysis provides insight into key role of miR408 towards drought tolerance response in cowpea. Plant Cell Rep 41: 75–94. https://doi.org/10.1007/s00299-021-02783-5
]Search in Google Scholar
[
Nandakumar M, Viswanathan R, Malathi P, Ramesh Sundar A (2021) Selection of reference genes for normalization of microRNA expression in sugarcane stalks during its interaction with Colletotrichum falcatum. 3 Biotech 11:72. https://doi.org/10.1007/s13205-020-02632-4
]Search in Google Scholar
[
Nicot N, Hausman J, Hoffmann L, Evers D (2005) Housekeeping gene selection for real-time RT-PCR normalization in potato during biotic and abiotic stress. J Exp Bot 56: 2907-2914. https://doi.org/10.1093/jxb/eri285
]Search in Google Scholar
[
Parmar S, Gharat SA, Tagirasa R, Chandra T, Behera L, Dash SK, Shaw BP, Amato A (2020) Identification and expression analysis of miRNAs and elucidation of their role in salt tolerance in rice varieties susceptible and tolerant to salinity PloS one 15: e0230958. https://doi.org/10.1371/journal.pone.0230958
]Search in Google Scholar
[
Peltier HJ, Latham GJ (2008) Normalization of microRNA expression levels in quantitative RT-PCR assays: identification of suitable reference RNA targets in normal and cancerous human solid tissues. RNA 14: 844-852. https://doi.org/10.1261/rna.939908
]Search in Google Scholar
[
Pfaffl, MW, Tichopad A, Prgomet C, Neuvians TP (2004) Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper—Excel-based tool using pair-wise correlations. Biotechnol. Lett 26: 509–515. https://doi.org/10.1023/b:bile.0000019559.84305.47
]Search in Google Scholar
[
Qiu CW, Liu L, Feng X, Hao PF, He X, Cao F, Wu F (2020) Genome-Wide identification and characterization of drought stress responsive microRNAs in Tibetan wild barley. Int. J. Mol. Sci 21: 2795. https://doi.org/10.3390/ijms21082795
]Search in Google Scholar
[
Ramachandran V, Chen XM (2008) Degradation of micro-RNAs by a family of exoribonucleases in Arabidopsis. Science 321: 1490–1492. https://doi.org/10.1126/science.1163728
]Search in Google Scholar
[
Rui M, Sheng X, Yucheg Z, Bing X, Ren W (2016) Selection and validation of appropriate reference genes for quantitative real-time PCR analysis of gene expression in Lycoris aurea. Front Plant Sci 7: 1-15. https://doi.org/10.3389/fpls.2016.00536
]Search in Google Scholar
[
Sekalska B, Ciechanowicz A, Dolegowska B, Narusze-wicz M (2006) Optimized RT-PCR method for assaying expression of monocyte chemotactic protein type 1(MCP-1) in rabbit aorta. Biochem Genet 44: 133–143. https://doi.org/10.1007/s10528-006-9015-4
]Search in Google Scholar
[
Shriram V, Kumar V, Devarumath RM, Khare TS, Wani SH (2016) MicroRNAs as potential targets for abiotic stress tolerance in plants Front Plant Sci 7: 817. https://doi.org/10.3389/fpls.2016.00817
]Search in Google Scholar
[
Song H, Xiao Z, Shi C, Wang S, Wu A, Wei C (2016) Selection and Verification of Candidate Reference Genes for Mature MicroRNA Expression by Quantitative RT-PCR in the Tea Plant (Camellia sinensis). Genes 7: 1-14. https://doi.org/10.3390/genes7060025
]Search in Google Scholar
[
Sunkar R, Zhu JK (2004) Novel and stress-regulated microRNAs and other small RNAs from Arabidopsis. Plant Cell 16: 2001-2019. https://doi.org/10.1105/tpc.104.022830
]Search in Google Scholar
[
Tong Z, Gao Z, Wang F, Zhou J, Zhang Z (2009) Selection of reliable reference genes for gene expression studies in peach using real-time PCR. BMC Molecular Biology 10: 1-13. https://doi.org/10.1186/1471-2199-10-71
]Search in Google Scholar
[
Tu C, Du T, Shao C, Liu Z, Li L, Shen Y (2018) Evaluating the potential of housekeeping genes, rRNAs, snRNAs, microRNAs and circRNAs as reference genes for the estimation of PMI. Forensic Science, Medicine and Pathology 14: 194-201. https://doi.org/10.1007/s12024-018-9973-y
]Search in Google Scholar
[
Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Frank Speleman (2002) Accurate normalization of real-time quantitative RTPCR data by geometric averaging of multiple internal control genes. Genome Biol 3: research0034.1-research0034.11. https://doi.org/10.1186/gb-2002-3-7-research0034
]Search in Google Scholar
[
Vdal TL, Lillo C (2009) Reference gene selection for quantitative real-time pcr normalization in tomato subjected to nitrogen, cold, and light stress. Analytical Biochemistry 387: 238-242. https://doi.org/10.1016/j.ab.2009.01.024
]Search in Google Scholar
[
Verstraeten B, Smet LD, Kyndt T, Meyer TD (2019) Selection of miRNA reference genes for plant defence studies in rice (Oryza sativa). Planta 250, 2101–2110. https://doi.org/10.1007/s00425-019-03289-x
]Search in Google Scholar
[
Wang B, Sun YF, Song N, Wei JP, Wang XJ, Feng H, Yin ZY, Kang ZS (2014) MicroRNAs involving in cold, wounding and salt stresses in Triticum aestivum L. Plant Physiol. Biochem 80: 90–96. https://doi.org/10.1016/j.plaphy.2014.03.020
]Search in Google Scholar
[
Wang M, Wang Q, Zhang, B (2013) Response of miRNAs and their targets to salt and drought stresses in cotton (Gossypium hirsutum L.). Gene 530: 26–32. https://doi.org/10.1016/j.gene.2013.08.009
]Search in Google Scholar
[
Wang P, Yang Y, Shi H, Wang Y, Ren F (2019) Small RNA and degradome deep sequencing reveal respective roles of cold-related microRNAs across Chinese wild grapevine and cultivated grapevine. BMC Genomics 20: 740. https://doi.org/10.1186/s12864-019-6111-5
]Search in Google Scholar
[
Islam W, Idrees A, Waheed A, Zeng F (2022) Plant responses to drought stress: microRNAs in action, Environmental Research 215: 114282. https://doi.org/10.1016/j.envres.2022.114282
]Search in Google Scholar
[
Wu XM, Liu MY, Ge XX, Xu Q, Guo WW (2011) Stage and tissue-specific modulation of ten conserved miRNAs and their targets during somatic embryogenesis of Valencia sweet orange. Planta 233: 495-505. https://doi.org/10.1007/s00425-010-1312-9
]Search in Google Scholar
[
Yang T, Wang Y, Teotia S, Wang Z, Shi C, Sun H, Gu Y, Zhang Z, Tang G (2019) The interaction between miR160 and miR165/166 in the control of leaf development and drought tolerance in Arabidopsis. Sci Rep 9: 2832. https://doi.org/10.1038/s41598-019-39397-7
]Search in Google Scholar
[
Yasmin Begum (2022) Regulatory role of microRNAs (miRNAs) in the recent development of abiotic stress tolerance of plants, Gene, 821, 146283. https://doi.org/10.1016/j.gene.2022.146283
]Search in Google Scholar
[
Yu Y, Ni Z, Wang Y, Wan H, Hu Z, Jiang Q, Sun X, Zhang H (2019) Overexpression of soybean miR169c confers increased drought stress sensitivity in transgenic Arabidopsis thaliana. Plant Science 285: 68-78. https://doi.org/10.1016/j.plantsci.2019.05.003
]Search in Google Scholar
[
Zeng X, Xu Y, Jiang J, Zhang F, Ma L, Wu D, Wang Y, Sun W (2018) Identification of cold stress responsive microRNAs in two winter turnip rape (Brassica rapa L.) by high throughput sequencing. BMC Plant Biol 18: 52. https://doi.org/10.1186/s12870-018-1242-4
]Search in Google Scholar
[
Zhang B, Pan X, Cobb GP, Anderson TA (2006) Plant microrna: a small regulatory molecule with big impact. Developmental Biology 289: 3-16. https://doi.org/10.1016/j.ydbio.2005.10.036
]Search in Google Scholar
[
Zhang Y, Xue J, Zhu L, Hu H, Yang J, Cui J, Xu J (2021) Selection and Optimization of Reference Genes for MicroRNA Expression Normalization by qRT-PCR in Chinese Cedar (Cryptomeria fortunei) under Multiple Stresses. Int J Mol Sci 22:7246. https://doi.org/10.3390/ijms22147246
]Search in Google Scholar
[
Zhao B, Liang R, Ge L, Li W, Xiao H, Lin H, Ruan K, Jin Y (2007) Identification of drought-induced micrornas in rice. Biochemical and Biophysical Research Communications 354: 585-590. https://doi.org/10.1016/j.bbrc.2007.01.022
]Search in Google Scholar
[
Zhao F, Maren NA, Kosentka PZ, et al. (2021) An optimized protocol for stepwise optimization of real-time RT-PCR analysis. Hortic Res 8: 179. https://doi.org/10.1038/s41438-021-00616-w
]Search in Google Scholar
[
Zhou X, Wang G, Sutoh K, Zhu JK, Zhang W (2008) Identification of cold-inducible microRNAs in plants by transcriptome analysis. BBA - Gene Regulatory Mechanisms 1779: 780-788. https://doi.org/10.1016/j.bbagrm.2008.04.005
]Search in Google Scholar
[
Zhong HY, Chen JW, Li CQ, Chen L, Wu JY, Chen JY, Lu WJ, Li JG (2011) Selection of reliable reference genes for expression studies by reverse transcription quantitative real-time PCR in litchi under different experimental conditions. Plant cell Reports 30: 641-653. https://doi.org/10.1007/s00299-010-0992-8
]Search in Google Scholar
[
Zhang L, Yan S, Zhang S, Yan P, Wang J, Zhang H (2021) Glutathione, carbohydrate and other metabolites of Larix olgensis A. Henry reponse to polyethylene glycol-simulated drought stress. PLoS One 16:e0253780. https://doi.org/10.1371/journal.pone.0253780
]Search in Google Scholar
[
Zhang J, Zhang S, Han S, Wu T, Li X, Li W, Qi L (2012) Genome-wide identification of microRNAs in larch and stage-specific modulation of 11 conserved microRNAs and their targets during somatic embryogenesis. Planta 236: 647-657. https://doi.org/10.1007/s00425-012-1643-9
]Search in Google Scholar
[
Zhang Y, Gong H, Li D, Zhou R, Zhao F, Zhang X, You J (2020) Integrated small RNA and degradome sequencing provide insights into salt tolerance in sesame (Sesamum indicum L.). BMC Genomics 21: 494. https://doi.org/10.1186/s12864-020-06913-3
]Search in Google Scholar
