| [1] |
Li Y, Guo L, Wang Z, Zhao D, Guo D, et al. 2023. Genome-wide association study of 23 flowering phenology traits and 4 floral agronomic traits in tree peony (Paeonia section Moutan DC.) reveals five genes known to regulate flowering time. |
| [2] |
Hao S, Wang Y, Yan Y, Liu Y, Wang J, et al. 2021. A review on plant responses to salt stress and their mechanisms of salt resistance. |
| [3] |
An H, Luan Y, Zhao D, Tao J. 2024. The VQ motif-containing PoVQ31 protein positively modulates drought stress tolerance in Paeonia ostii 'FengDan'. |
| [4] |
Ding Y, Tao Y, Zhu C. 2013. Emerging roles of microRNAs in the mediation of drought stress response in plants. |
| [5] |
Gao Z, Ma C, Zheng C, Yao Y, Du Y. 2022. Advances in the regulation of plant salt-stress tolerance by miRNA. |
| [6] |
Udvardi MK, Czechowski T, Scheible WR. 2008. Eleven golden rules of quantitative RT-PCR. |
| [7] |
Li W, Wang P, Li Y, Zhang K, Ding F, et al. 2015. Identification of microRNAs in response to different day lengths in soybean using high-throughput sequencing and qRT-PCR. |
| [8] |
Liu X, Liu S, Zhang J, Wu Y, Wu W, et al. 2020. Optimization of reference genes for qRT-PCR analysis of microRNA expression under abiotic stress conditions in sweetpotato. |
| [9] |
Zhu J, Zhang L, Li W, Han S, Yang W, et al. 2013. Reference gene selection for quantitative real-time PCR normalization in Caragana intermedia under different abiotic stress conditions. |
| [10] |
Yang Y, Zhang X, Chen Y, Guo J, Ling H, et al. 2016. Selection of reference genes for normalization of microRNA expression by RT-qPCR in sugarcane buds under cold stress. |
| [11] |
Luo M, Gao Z, Li H, Li Q, Zhang C, et al. 2018. Selection of reference genes for miRNA qRT-PCR under abiotic stress in grapevine. |
| [12] |
Li J, Han J, Hu Y, Yang J. 2016. Selection of reference genes for quantitative real-time PCR during flower development in tree peony (Paeonia suffruticosa Andr.). |
| [13] |
Liu H, Gao L, Hu Y. 2015. Reference genes discovery and selection for quantitative real-time PCR in tree peony seed and petal tissue of different development stages. Chinese Journal of Agricultural Biotechnology 23:1639−1648 |
| [14] |
Guo L, Li Y, Wei Z, Wang C, Hou X. 2023. Reference genes selection of Paeonia ostii 'Fengdan' under osmotic stresses and hormone treatments by RT-qPCR. |
| [15] |
Zhou S, Ma C, Zhou W, Gao S, Hou D, et al. 2024. Selection of stable reference genes for QRT-PCR in tree peony 'Doulv' and functional analysis of PsCUC3. |
| [16] |
Shen J, Wang X, Li Y, Guo L, Hou X. 2023. Screening of reference miRNA of different early-and late-flowering tree peony varieties. |
| [17] |
Zhang C, Song C, Chen L, Ma H, Zhang Y, et al. 2023. Selection and validation of miRNA reference genes by quantitative real-time PCR analysis in Paeonia suffruticosa. |
| [18] |
Tang F, Chu L, Shu W, He X, Wang L, et al. 2019. Selection and validation of reference genes for quantitative expression analysis of miRNAs and mRNAs in Poplar. |
| [19] |
Zhang Y, Xue J, Zhu L, Hu H, Yang J, et al. 2021. Selection and optimization of reference genes for microRNA expression normalization by qRT-PCR in Chinese cedar (Cryptomeria fortunei) under multiple stresses. |
| [20] |
Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, et al. 2002. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. |
| [21] |
Li B, Liu Y, Liang H, Wang X, Wang S, et al. 2026. PomiR172d-PoARR module regulates the drought response through the reactive oxygen pathway in tree peony. |
| [22] |
Zhou L, Shi Q, Wang Y, Li K, Zheng B, et al. 2016. Evaluation of candidate reference genes for quantitative gene expression studies in tree peony. |
| [23] |
Hellemans J, Mortier G, De Paepe A, Speleman F, Vandesompele J. 2007. qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data. |
| [24] |
Wu J, He B, Du Y, Li W, Wei Y. 2017. Analysis method of systematically evaluating stability of reference genes using geNorm, NormFinder and BestKeeper. |
| [25] |
Andersen CL, Jensen JL, Ørntoft TF. 2004. Normalization of real-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. |
| [26] |
Bartels D, Sunkar R. 2005. Drought and salt tolerance in plants. |
| [27] |
Ding D, Zhang L, Wang H, Liu Z, Zhang Z, et al. 2009. Differential expression of miRNAs in response to salt stress in maize roots. |
| [28] |
Megha S, Basu U, Kav NNV. 2018. Regulation of low temperature stress in plants by microRNAs. |
| [29] |
Radonić A, Thulke S, Mackay IM, Landt O, Siegert W, et al. 2004. Guideline to reference gene selection for quantitative real-time PCR. |
| [30] |
Xie F, Wang J, Zhang B. 2023. RefFinder: a web-based tool for comprehensively analyzing and identifying reference genes. |
| [31] |
Liu X, Yang T, Li J, Ma C. 2025. Selection and validation of RT-qPCR reference genes for multi-tissue gene expression normalization in two honeybee subspecies across post-emergence developmental stages. |
| [32] |
Borowski JM, Galli V, da Silva Messias R, Perin EC, Buss JH, et al. 2014. Selection of candidate reference genes for real-time PCR studies in lettuce under abiotic stresses. |
| [33] |
Floyd SK, Bowman JL. 2004. Ancient microRNA target sequences in plants. |
| [34] |
Axtell MJ, Bowman JL. 2008. Evolution of plant microRNAs and their targets. |
| [35] |
Jin G, Zhang X, Yu S, Du Y, Wang M, et al. 2024. Screening and validation of optimal miRNA reference genes in different developing stages and tissues of Lilium henryi Baker. |
| [36] |
Wu W, Deng Q, Shi P, Yang J, Hu Z, et al. 2016. Identification of appropriate reference genes for normalization of miRNA expression in grafted watermelon plants under different nutrient stresses. |
| [37] |
Turner M, Adhikari S, Subramanian S. 2013. Optimizing stem-loop qPCR assays through multiplexed cDNA synthesis of U6 and miRNAs. |
| [38] |
Sun Z, Wang Y, Mou F, Tian Y, Chen L, et al. 2016. Genome-wide small RNA analysis of soybean reveals auxin-responsive microRNAs that are differentially expressed in response to salt stress in root apex. |
| [39] |
Song H, Zhang X, Shi C, Wang S, Wu A, et al. 2016. Selection and verification of candidate reference genes for mature microRNA expression by quantitative RT-PCR in the tea plant (Camellia sinensis). |
| [40] |
Wang H, Wang H. 2015. The miR156/SPL module, a regulatory hub and versatile toolbox, gears up crops for enhanced agronomic traits. |
| [41] |
Wang C, Wang Q, Zhu X, Cui M, Jia H, et al. 2019. Characterization on the conservation and diversification of miRNA156 gene family from lower to higher plant species based on phylogenetic analysis at the whole genomic level. |
| [42] |
Zhang L, Yang X, Yin Y, Wang J, Wang Y. 2021. Identification and validation of miRNA reference genes in poplar under pathogen stress. |
| [43] |
Barik S, SarkarDas S, Singh A, Gautam V, Kumar P, et al. 2014. Phylogenetic analysis reveals conservation and diversification of micro RNA166 genes among diverse plant species. |