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Reference genes selection of Paeonia ostii ‘Fengdan’ under osmotic stresses and hormone treatments by RT-qPCR

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Abstract

Background

Tree peony possess significant ornamental, medicinal and oil values. Osmotic stresses including dehydratiuon and salinity limit the expansion of cultivation area of tree peony. Information on reference genes selection under osmotic stress and hormone stimulation of tree peony still limited. This study aimed to determine the stable reference genes suitable for tree peony under osmotic stresses and hormone treatments, and provide a theoretical basis for the molecular biology research.

Methods and results

Twelve candidate reference genes were evaluated in Paeonia ostii ‘Fengdan’ under osmotic stress and hormone treatments by RT-qPCR. Delta Ct method, geNorm, and NormFinder were used for the comprehensive expression stability ranking comparison. The results revealed that tubulin-α was the preferred internal reference genes for drought and ABA treatment, tubulin-β was identified as the most suitable reference gene under drought and OPDA induction, 18s-rRNA was regarded as the most stable gene for salinity and JA treatment, eIF-5 A was listed as the most stable gene for JA and MeJA treatments. The experiments also displayed that EF1-α were comparatively unstable under ABA and BR hormone treatments.

Conclusion

These preferred reference genes could be useful in qPCR studies involving osmotic or hormonal stresses in Paeonia ostii ‘Fengdan’. It is anticipated that the results will benefit tree peony functional genomics studies and molecular breeding research in the future.

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References

  1. Guo LL, Guo S, Xu J, He LX, Carlson JE, Hou XG (2020) Phylogenetic analysis based on chloroplast genome uncover evolutionary relationship of all the nine species and six cultivars of tree peony. Ind Crop Prod 153:112567. https://doi.org/10.1016/j.indcrop.2020.112567

    Article  CAS  Google Scholar 

  2. Guo LL, Guo DL, Zhao W, Hou XG (2018) Newly developed SSR markers reveal genetic diversity and geographical clustering in Paeonia suffruticosa based on flower colour. J Hortic Sci Biotech 93(4):416–424. https://doi.org/10.1080/14620316.2017.1373039

    Article  CAS  Google Scholar 

  3. Yang Y, Sun M, Li SS, Chen Q, Teixeira da Silva JA, Wang A, Yu XN, Wang LS (2020) Germplasm resources and genetic breeding of Paeonia: a systematic review. Hortic Res 7:107. https://doi.org/10.1038/s41438-020-0332-2

    Article  Google Scholar 

  4. Li SS, Wu Q, Yin DD, Feng CY, Liu ZG, Wang LS (2018) Phytochemical variation among the traditional Chinese medicine Mu Dan Pi from Paeonia suffruticosa (tree peony). Phytochemistry 146:16–24. https://doi.org/10.1016/j.phytochem.2017.11.008

    Article  CAS  Google Scholar 

  5. Zhang L, Guo DL, Guo LL, Guo Q, Wang HF, Hou XG (2019) Construction of a high-density genetic map and QTLs mapping with GBS from the interspecific F1 population of P. ostii ‘Fengdan Bai’ and P. suffruticosa ‘Xin Riyuejin’. Sci Hortic 246:190–200. https://doi.org/10.1016/j.scienta.2018.10.039

    Article  CAS  Google Scholar 

  6. Guo Q, Guo LL, Zhang L, Zhang LX, Ma HL, Guo DL, Hou XG (2017) Construction of a genetic linkage map in tree peony (Paeonia Sect. Moutan) using simple sequence repeat (SSR) markers. Sci Hortic 219:294–301. https://doi.org/10.1016/j.scienta.2017.03.017

    Article  Google Scholar 

  7. Shi J, Shi GA, Tian Z (2015) Effect of exogenous hydrogen peroxide or ascorbic acid on senescence in cut flowers of tree peony (Paeonia suffruticosa Andr.). J Hortic Sci Biotech 90(6):689–694. https://doi.org/10.1080/14620316.2015.11668732

    Article  CAS  Google Scholar 

  8. Zhang C, Wang YJ, Fu JX, Dong L, Gao SL, Du DN (2014) Transcriptomic analysis of cut tree peony with glucose supply using the RNA-Seq technique. Plant Cell Rep 33(1):111–129. https://doi.org/10.1007/s00299-013-1516-0

    Article  CAS  Google Scholar 

  9. Wang XJ, Liang HY, Guo DL, Guo LL, Duan XG, Jia QS, Hou XG (2019) Integrated analysis of transcriptomic and proteomic data from tree peony (P. ostii) seeds reveals key developmental stages and candidate genes related to oil biosynthesis and fatty acid metabolism. Hortic Res 6:111. https://doi.org/10.1038/s41438-019-0194-7

    Article  CAS  Google Scholar 

  10. Zhang Y, Liu P, Gao JY, Wang XS, Yan M, Xue NC, Qu CX, Deng RX (2018) Paeonia veitchii seeds as a promising high potential by-product: proximate composition, phytochemical components, bioactivity evaluation and potential applications. Ind Crop Prod 125:248–260. https://doi.org/10.1016/j.indcrop.2018.08.067

    Article  CAS  Google Scholar 

  11. Xu J, Xu ZC, Zhu YJ, Luo HM, Qian J, Ji AJ, Hu YL, Sun W, Wang B, Song JY, Sun C, Chen SL (2014) Identification and evaluation of reference genes for qRT-PCR normalization in Ganoderma lucidum. Curr Microbiol 68(1):120–126. https://doi.org/10.1007/s00284-013-0442-2

    Article  CAS  Google Scholar 

  12. VanGuilder HD, Vrana KE, Freeman WM (2008) Twenty-five years of quantitative PCR for gene expression analysis. Biotechniques 44(5):619–626. https://doi.org/10.2144/000112776

    Article  CAS  Google Scholar 

  13. Livak KJ, Schmittgen TD (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2. method Methods 25:402–408. https://doi.org/10.1006/meth.2001.1262

    Article  CAS  Google Scholar 

  14. Radonić A, Thulke S, Mackay IM, Landt O, Siegert W, Nitsche A (2004) Guideline to reference gene selection for quantitative real-time PCR. Biochem Biophys Res Commun 313:856–862. https://doi.org/10.1016/j.bbrc.2003.11.177

    Article  CAS  Google Scholar 

  15. Bustin SA, Benes V, Nolan T, Pfaffl MW (2005) Quantitative real-time RT-PCR–a perspective. J Mol Endocrinol 34(3):597–601. https://doi.org/10.1677/jme.1.01755

    Article  CAS  Google Scholar 

  16. Mahoney DJ, Carey KA, Fu MH, Snow RJ, Cameronsmith D, Parise G, Tarnopolsky MA (2004) Real-time RT-PCR analysis of housekeeping genes in human skeletal muscle following acute exercise. Physiol Genomics 18:226–231. https://doi.org/10.1152/physiolgenomics.00067.2004

    Article  CAS  Google Scholar 

  17. Anirban K, Anju P, Amita P (2013) Defining reference genes for qPCR normalization to study biotic and abiotic stress responses in Vigna mungo. Plant Cell Rep 32(10):1647–1658. https://doi.org/10.1007/s00299-013-1478-2

    Article  CAS  Google Scholar 

  18. Wang HL, Chen JH, Tian QQ, Wang S, Xia XL, Yin WL (2014) Identification and validation of reference genes for Populus euphratica gene expression analysis during abiotic stresses by quantitative real-time PCR. Physiol Plant 152(3):529–545. https://doi.org/10.1111/ppl.12206

    Article  CAS  Google Scholar 

  19. Wang HL, Li L, Tang S, Yuan C, Tian QQ, Su YY, Li HG, Zhao L, Yin WL, Zhao R, Xia XL (2015) Evaluation of appropriate reference genes for reverse transcription-quantitative PCR studies in different tissues of a desert poplar via comparison of different algorithms. Int J Mol Sci 16(9):20468–20491. https://doi.org/10.3390/ijms160920468

    Article  CAS  Google Scholar 

  20. Wang YJ, Dong L, Zhang C, Wang XQ (2012) Reference gene selection for real-time quantitative PCR normalization in tree peony (Paeonia suffruticosa Andr.). Agric Biotechnol 20(5):521–528. https://doi.org/10.3969/j.issn.16747968.2012.05.008

    Article  CAS  Google Scholar 

  21. Zhang YX, Gai SP, Liu CY, Mu P, Zheng GS (2011) Selection of control gene in real-time qPCR analysis during bud dormancy release in tree peony (Peaonia suffruticosa). Mol Plant Breed 9:1052–1056. https://doi.org/10.5376/mpb.cn.2011.09.0007

    Article  Google Scholar 

  22. Liu HF, Gao LX, Hu YH (2015) Reference genes discovery and selection for quantitative real time PCR in tree peony seed and petal tissue of different development stages. Agr Biotech 23:1639–1648. https://doi.org/10.3969/j.issn.1674-7968.2015.12.014

    Article  CAS  Google Scholar 

  23. Zhou L, Shi QQ, Wang Y, Li K, Zheng BQ, Miao K (2016) Evaluation of candidate reference genes for quantitative gene expression studies in tree peony. J Am Soc Hortic Sci 141:99–111. https://doi.org/10.21273/JASHS.141.2.99

    Article  CAS  Google Scholar 

  24. Li J, Han JG, Hu YH, Yang J (2016) Selection of reference genes for quantitative real-time PCR during flower development in tree peony (Paeonia suffruticosa Andr.). Front Plant Sci 7:516–516. https://doi.org/10.3389/fpls.2016.00516

    Article  Google Scholar 

  25. Pan MH, Lu TQ, Tian B (2020) Selection and validation of reference genes in the deeds of Paeonia delavayi in quantitative real-time PCR analysis. Biotechnol Bull 36(9):1–8. https://doi.org/10.13560/j.cnki.biotech.bull.1985.2019-1208

    Article  CAS  Google Scholar 

  26. Wan YL, Hong AY, Zhang YX, Liu Y (2019) Selection and validation of reference genes of Paeonia lactiflora in growth development and light stress. Physiol Mol Bio Pla 25(4):1097–1105. https://doi.org/10.1007/s12298-019-00684-2

    Article  CAS  Google Scholar 

  27. Gu CS, Chen SM, Liu ZL, Shan H, Luo HL, Guang ZY, Chen FD (2011) Reference gene selection for quantitative real-time PCR in chrysanthemum subjected to biotic and abiotic stress. Mol Biotechnol 49(2):192–197. https://doi.org/10.1007/s12033-011-9394-6

    Article  CAS  Google Scholar 

  28. Li MY, Song X, Wang F, Xiong AS (2016) Suitable reference genes for accurate gene expression analysis in parsley (Petroselinum crispum) for abiotic stresses and hormone stimuli. Front Plant Sci 7:1481. https://doi.org/10.3389/fpls.2016.01481

    Article  CAS  Google Scholar 

  29. Wang PH, Xiong AS, Gao ZH, Yu XY, Li M, Hou YJ, Sun C, Qu SC (2016) Selection of suitable reference genes for RT-qPCR normalization under abiotic stresses and hormone stimulation in Persimmon (Diospyros kaki Thunb). PlosOne 11(8), e0160885. https://doi.org/10.1371/journal.pone.0160885

  30. Niu XP, Chen MX, Huang XY, Chen HH, Tao AF, Xu JT, Qi JM (2017) Reference gene selection for qRT-PCR normalization analysis in kenaf (Hibiscus cannabinus L.) under abiotic stress and hormonal stimuli. Front Plant Sci 8:771. https://doi.org/10.3389/fpls.2017.00771

    Article  Google Scholar 

  31. Liu X, Guang HR, Song M, Fu YP, Han XM, Lei M, Ren JY, Guo B, He W, Wei YH (2018) Reference gene selection for qRT-PCR assays in Stellera chamaejasme subjected to abiotic stresses and hormone treatments based on transcriptome datasets. PeerJ 6:e4535. https://doi.org/10.7717/peerj.4535

    Article  CAS  Google Scholar 

  32. Yan HF, Zhang YY, Xiong YP, Chen QW, Liang HZ, Niu MY, Guo BY, Li MZ, Zhang XH, Li Y, Teixeira da Silva JA, Ma GH (2018) Selection and validation of novel RT-qPCR reference genes under hormonal stimuli and in different tissues of Santalum album. Sci Rep 8(1):17511. https://doi.org/10.1038/s41598-018-35883-6

    Article  CAS  Google Scholar 

  33. Feng K, Liu JX, Xing GM, Sun S, Li S, Duan AQ, Wang F, Li MY, Xu ZS, Xiong AS (2019) Selection of appropriate reference genes for RT-qPCR analysis under abiotic stress and hormone treatment in celery. PeerJ 7:e7925. https://doi.org/10.7717/peerj.7925

    Article  Google Scholar 

  34. Guo LL, Guo DL, Yin WL, Hou XG (2018) Tolerance strategies revealed in tree peony (Paeonia suffruticosa; Paeoniaceae) ecotypes differentially adapted to desiccation. Appl Plant Sci 6(10):e01191. https://doi.org/10.1002/aps3.1191

    Article  Google Scholar 

  35. Wang HL, Li L, Tang S, Yuan C, Tian QQ, Su YY, Li HG, Zhao L, Yin WL, Zhao R, Xia XL (2015) Evaluation of appropriate reference genes for reverse transcription-quantitative PCR studies in different tissues of a desert poplar via comparision of different algorithms. Int J Mol Sci 16(9):20468–20491. https://doi.org/10.3390/ijms160920468

    Article  CAS  Google Scholar 

  36. Silver N, Best S, Jiang J, Thein SL (2006) Selection of housekeeping genes for gene expression studies in human reticulocytes using real-time PCR. BMC Mol Biol 7:33

    Article  Google Scholar 

  37. Andersen CL, Jensen JL, Orntoft 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. Cancer Res 64:5245–5250

    Article  CAS  Google Scholar 

  38. Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Speleman F (2002) Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 3. https://doi.org/10.1186/gb-2002-3-7-research0034. research0034.1

  39. 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

    Article  CAS  Google Scholar 

  40. Vandesompele J, Preter KD, Pattyn F, Poppe B, Roy NV, Paepe AD, Speleman F (2002) Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 3(7):1–12. https://doi.org/10.1186/gb-2002-3-7-research0034

    Article  Google Scholar 

  41. Wan Q, Chen SL, Shan ZH, Yang ZL, Chen LM, Zhang CJ, Yuan SL, Hao QN, Zhang XJ, Qiu DZ, Chen HF, Zhou XN (2017) Stability evaluation of reference genes for gene expression analysis by RT-qPCR in soybean under different conditions. PlosOne 12(12):e0189405. https://doi.org/10.1371/journal.pone.0189405

    Article  CAS  Google Scholar 

  42. Wan HG, Zhao ZG, Qian CT, Sui YH, Malik AA, Chen JF (2010) Selection of appropriate reference genes for gene expression studies by quantitative real-time polymerase chain reaction in cucumber. Anal Biochem 399(2):257–261. https://doi.org/10.1016/j.ab.2009.12.008

    Article  CAS  Google Scholar 

  43. Chen L, Zhong HY, Kuang JF, Li JG, Lu WJ, Chen JY (2011) Validation of reference genes for RT-qPCR studies of gene expression in banana fruit under different experimental conditions. Planta 234(2):377–390. https://doi.org/10.1007/s00425-011-1410-3

    Article  CAS  Google Scholar 

  44. Yue JY, Zhu CX, Zhou Y, Niu XL, Miao M, Tang XF, Chen FD, Zhao WP, Liu YS (2018) Transcriptome analysis of differentially expressed unigenes involved in flavonoid biosynthesis during flower development of Chrysanthemum morifolium ‘Chuju’. Sci Rep 8(1):1–14. https://doi.org/10.1038/s41598-018-31831-6

    Article  CAS  Google Scholar 

  45. Maroufi A, Bockstaele EV, Loose MD (2010) Validation of reference genes for gene expression analysis in chicory (Cichorium intybus) using quantitative real-time PCR. BMC Mol Biol 11:15–27. https://doi.org/10.1186/1471-2199-11-15

    Article  CAS  Google Scholar 

  46. Bustin SA, Benes V, Garson JA, Hellemans J, Huggett JF, Kubista M, Mueller R, Nolan T, Pfaffl MW, Shipley GL, Vandesompele J, Wittwer CT (2009) The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin chem 55:611–622. https://doi.org/10.1373/clinchem.2008.112797

    Article  CAS  Google Scholar 

  47. Mallona I, Lischewski S, Weiss J, Hause B, Egeacortines M (2010) Validation of reference genes for quantitative real-time PCR during leaf and flower development in Petunia hybrida. BMC Plant Biol 10(1):4–4. https://doi.org/10.1186/1471-2229-10-4

    Article  CAS  Google Scholar 

  48. Sturzenbaum SR, Kille P (2001) Control genes in quantitative molecular biological techniques: the variability of invariance. Comp Biochem Phys B 130(3):281–289. https://doi.org/10.1016/s1096-4959(01)00440-7

    Article  CAS  Google Scholar 

  49. Su X, Lu LY, Li YS, Zhen CG, Hu GL, Jiang K, Yan YW, Xu YB, Wang G, Shi MW, Chen XL, Zhang BZ (2020) Reference gene selection for quantitative real-time PCR (qRT-PCR) expression analysis in Galium aparine L. PlosOne 15(2), e0226668. https://doi.org/10.1371/journal.pone.0226668

  50. Iskandar HM, Simpson RS, Casu RE, Bonnett GD, Maclean DJ, Manners JM (2004) Comparison of reference genes for quantitative real-time polymerase chain reaction analysis of gene expression in sugarcane. Plant Mol Biol Rep 22(4):325–337. https://doi.org/10.1007/bf02772676

    Article  CAS  Google Scholar 

  51. Thellin O, Zorzi W, Lakaye B, Borman BD, Coumans B, Hennen G, Grisar T, Igout A, Heinen E (1999) Housekeeping genes as internal standards: use and limits. J Biotechnol 75(2):291–295. https://doi.org/10.1016/S0168-1656(99)00163-7

    Article  CAS  Google Scholar 

  52. Liu QX, Qi X, Yan HD, Huang LK, Nie G, Zhang XQ (2018) Reference gene selection for quantitative real-time reverse-transcriptase PCR in annual ryegrass (Lolium multiflorum) subjected to various abiotic stresses. Molecules 23(1):172. https://doi.org/10.3390/molecules23010172

    Article  CAS  Google Scholar 

  53. Gulshan K, Singh AK (2015) Reference gene validation for qRT-PCR based gene expression studies in different developmental stages and under biotic stress in apple. Sci Horticamsterdam 197:597–606. https://doi.org/10.1016/j.scienta.2015.10.025

    Article  CAS  Google Scholar 

  54. Wang T, Hao RJ, Pan HT, Cheng TR (2014) Selection of suitable reference genes for quantitative real-time polymerase chain reaction in Prunus mume during flowering stages and under different abiotic stress conditions. J Am Soc Hortic Sci 139(2):113–122. https://doi.org/10.21273/JASHS.139.2.113

    Article  CAS  Google Scholar 

  55. Ren R, Dai PH, Li M, Liu ZM, Cao FX (2016) Selection and stability evaluation of reference genes for real-time quantitative PCR in dove tree (Davidia involucrata). Plant Physiol 52(10):1565–1575. https://doi.org/10.13592/j.cnki.ppj.2016.0325

    Article  Google Scholar 

  56. Qi JN, Yu SC, Zhang FL, Shen XQ, Zhao XY, Yu YJ, Zhang DS (2010) Reference gene selection for real-time quantitative polymerase chain reaction of mRNA transcript levels in Chinese cabbage (Brassica rapa L. ssp. pekinensis). Plant Mol Biol Rep 28(4):597–604. https://doi.org/10.1007/s11105-010-0185-1

    Article  CAS  Google Scholar 

  57. Monteiro F, Sebastiana M, Pais MS, Figueiredo A (2013) Reference gene selection and validation for the early responses to downy mildew infection in susceptible and resistant Vitis vinifera cultivars. PlosOne 8(9):e72998. https://doi.org/10.1371/journal.pone.0072998

    Article  CAS  Google Scholar 

  58. Schmidt GW, Delaney SK (2010) Stable internal reference genes for normalization of real-time RT-PCR in tobacco (Nicotiana tabacum) during development and abiotic stress. Mol Genet Genomics 283(3):233–241. https://doi.org/10.1007/s00438-010-0511-1

    Article  CAS  Google Scholar 

  59. Xu M, Zhang B, Su XH, Zhang SG, Huang MR (2011) Reference gene selection for quantitative real-time polymerase chain reaction in. Anal Biochem 408(2):337–339. https://doi.org/10.1016/j.ab.2010.08.044

    Article  CAS  Google Scholar 

  60. Bartłomiej K, Rapacz M (2013) Reference genes in real-time PCR. J Appl Genet 54(4):391–406. https://doi.org/10.1007/s13353-013-0173-x

    Article  CAS  Google Scholar 

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Funding

This work was supported by [National Natural Science Foundation of China](Grant number [U1804233]), [Outstanding Youth Fund Project of Natural Science Foundation of Henan Province](Grant number [202300410119]), [the Colleges and Universities Science and Technology Innovation Talent Support Plan of Henan Province](Grant number [22HASTIT036]), and [Central Plains Academics of Henan Province, China](Grant number [212101510003]).

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Lili Guo contributed to the conceptualization, investigation, writing, reviewing, and editing. Yuying Li contributed to the material preparation, methodology and data curation. Zhenzhen Wei contributed to the original draft preparation. Can Wang contributed to the manuscript editing. Xiaogai Hou contributed to the supervision and funding acquisition.

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Correspondence to Xiaogai Hou.

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Guo, L., Li, Y., Wei, Z. et al. Reference genes selection of Paeonia ostii ‘Fengdan’ under osmotic stresses and hormone treatments by RT-qPCR. Mol Biol Rep 50, 133–143 (2023). https://doi.org/10.1007/s11033-022-07938-5

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