Quantitative gene expression analysis by qPCR requires reference genes for normalization. Lagerstroemia indica (crape myrtle) is a popular ornamental plant in the world, but suitable endogenous reference genes are lacking. To find suitable reference genes, we evaluated the stabilities of nine candidate genes in six experimental data sets: six different tissues, three leaf colors, nine flower colors, and under three abiotic stresses (salt, drought, cold) using four statistical algorithms. A target gene LiMYB56 (homolog of Arabidopsis MYB56) was used to verify the authenticity and accuracy of the candidate reference genes. The results showed that the combination of two stably expressed reference genes, rather than a single reference gene, improved the accuracy of the qPCR. LiEF1α-2 + LiEF1α-3 was best for the tissue, salt treatment, and drought treatment sets; LiEF1α-2 + LiEF1α-1 was optimal for leaf color; LiEF1α-2 + LiACT7 was optimal for cold treatment; and LiUBC + LiEF1α-1 was best for the flower color set. Notably, LiEF1α-2 had high expression stability in all six experimental sets, implying it may be a good reference gene for expression studies in L. indica. Our results will facilitate future gene expression studies in L. indica.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
Availability of data and materials
All data generated or analyzed during this study are included in this paper.
Tang X, Zhang N, Si HJ, Calderón-Urrea A (2017) Selection and validation of reference genes for RT-qPCR analysis in potato under abiotic stress. Plant Methods 13:85. https://doi.org/10.1186/s13007-017-0238-7
Gu CS, Liu LQ, Xu C, Zhao YH, Zhu XD, Huang SZ (2014) Reference gene selection for quantitative real-time RT-PCR normalization in Iris lactea var. chinensis roots under cadmium, lead, and salt stress conditions. Sci World J 2014:1–7. https://doi.org/10.1155/2014/532713
Ni LJ, Wang ZQ, Liu LQ, Guo JB, Li HG, Gu CS (2019) Selection and verification of candidate reference genes for gene expression by quantitative RT-PCR in Hibiscus hamabo Sieb.et Zucc. Trees-Struct Funct 33:1591–1601. https://doi.org/10.1007/s00468-019-01882-x
Bustin SA, Benes V, Garson JA, Hellemans J, Huggett J, Kubista M, Reinhold 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
Kozera B, Rapacz M (2013) Reference genes in real-time PCR. J Appl Genetics 54:391–406. https://doi.org/10.1007/s13353-013-0173-x
Huggett J, Dheda K, Bustin S, Zumla A (2005) Real-time RT-PCR normalisation; strategies and considerations. Genes Immunity 6:279–284. https://doi.org/10.1038/sj.gene.6364190
Guénin S, Mauriat M, Pelloux J, Wuytswinkel OV, Bellini C, Gutierrez L (2009) Normalization of qRT-PCR data: the necessity of adopting a systematic, experimental conditions-specific, validation of references. J Exp Bot 60:487–493. https://doi.org/10.1093/jxb/ern305
Artico S, Nardeli SM, Brilhante O, Grossi-de-Sa MF, Alves-Ferreira M (2010) Identification and evaluation of new reference genes in Gossypium hirsutum for accurate normalization of real-time quantitative RT-PCR data. BMC Plant Biol 10:49. https://doi.org/10.1186/1471-2229-10-49
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
Fan CJ, Ma JM, Guo QR, Li XT, Wang H, Lu MZ (2013) Selection of reference genes for quantitative real-time PCR in bamboo (Phyllostachys edulis). PLoS ONE 8:e56573. https://doi.org/10.1371/journal.pone.0056573
Hu RB, Fan CM, Li HY, Zhang QZ, Fu YF (2009) Evaluation of putative reference genes for gene expression normalization in soybean by quantitative real-time RT-PCR. BMC Mol Biol 10:93. https://doi.org/10.1186/1471-2199-10-93
Wan HJ, 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 399:257–261. https://doi.org/10.1016/j.ab.2009.12.008
Jin XH, Fu JX, Dai SL, Sun Y, Hong Y (2013) Reference gene selection for qPCR analysis in cineraria developing flowers. Sci Hortic 153:64–70. https://doi.org/10.1016/j.scienta.2013.01.023
Qi S, Yang LW, Wen XH, Hong Y, Song XB, Zhang MM, Dai SL (2016) Reference gene selection for RT-qPCR analysis of flower development in Chrysanthemum morifolium and Chrysanthemum lavandulifolium. Front Plant Sci 7:287. https://doi.org/10.3389/fpls.2016.00287
Gopaulchan D, Lennon AM, Umaharan P (2013) Identification of reference genes for expression studies using quantitative RT-PCR in spathe tissue of Anthurium andraeanum (Hort.). Sci Hortic 153:1–7. https://doi.org/10.1016/j.scienta.2013.01.024
Wang T, Hao RJ, Pan HT, Cheng TR, Zhang QX (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 139:113–122. https://doi.org/10.21273/JASHS.139.2.113
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
Pounders C, Rinehart T, Edwards N, Knight P (2007) An analysis of combining ability for height, leaf out, bloom date, and flower color for crapemyrtle. Hortscience 42:1496–1499. https://doi.org/10.21273/HORTSCI.42.6.1496
Liang H, Zhang M, Zhao YD, Gao C, Wang HL (2019) Variation characteristics of stem water content in Lagerstroemia indica and its response to microenvironment. Peer J Preprints 7:e27772v1. https://doi.org/10.7287/peerj.preprints.27772v1
Li Y, Zhang ZY, Wang P, Wang SA, Ma LL, Li LF, Yang RT, Ma YZ, Wang Q (2015) Comprehensive transcriptome analysis discovers novel candidate genes related to leaf color in a Lagerstroemia indica yellow leaf mutant. Genes Genomics 37:851–863. https://doi.org/10.1007/s13258-015-0317-y
Zheng TC, Chen ZL, Ju YQ, Zhang H, Cai M, Pan HT, Zhang QX (2018) Reference gene selection for qRT-PCR analysis of flower development in Lagerstroemia indica and L. speciosa. PLoS ONE 13:e0195004. https://doi.org/10.1371/journal.pone.0195004
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(research0034):1. https://doi.org/10.1186/gb-2002-3-7-research0034
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. Cancer Res 64:5245–5250. https://doi.org/10.1158/0008-5472.CAN-04-0496
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
Xie F, Xiao P, Chen DL, Xu L, Zhang BH (2012) miRDeepFinder: a miRNA analysis tool for deep sequencing of plant small RNAs. Plant Mol Biol 80(1):75–84. https://doi.org/10.1007/s11103-012-9885-2
Jeong CY, Kim JH, Lee WJ, Jin JY, Lee H (2018) AtMYB56 regulates anthocyanin levels via the modulation of AtGPT2 expression in response to sucrose in Arabidopsis. Mol Cells. https://doi.org/10.14348/molcells.2018.2195
Ruijter JM, Ramakers C, Hoogaars WMH, Karlen Y, Bakker O, van den Hoff MJB, Moorman AFM (2009) Amplification efficiency: linking baseline and bias in the analysis of quantitative PCR data. Nucleic Acids Res 37(6):e45. https://doi.org/10.1093/nar/gkp045
Zhang YT, Peng XR, Liu Y, Li YL, Luo Y, Wang XR, Tang HR (2018) Evaluation of suitable reference genes for qRT-PCR normalization in strawberry (Fragaria × ananassa) under different experimental conditions. BMC Mol Biol 19:8. https://doi.org/10.1186/s12867-018-0109-4
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. https://doi.org/10.1186/1471-2199-11-15
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. Biochem Biophys Res Commun 345(2):646–651. https://doi.org/10.1016/j.bbrc.2006.04.140
Huang XN, Gao YC, Jiang B, Zhou ZC, Zhan AB (2016) Reference gene selection for quantitative gene expression studies during biological invasions: a test on multiple genes and tissues in a model ascidian Ciona savignyi. Gene 576(1):79–87. https://doi.org/10.1016/j.gene.2015.09.066
Han H, Liu L, Chen M, Liu Y, Wang H, Chen LB (2020) The optimal compound reference genes for qRT-PCR analysis in the developing rat long bones under physiological conditions and prenatal dexamethasone exposure model. Reprod Toxicol. https://doi.org/10.1016/j.reprotox.2020.10.008
Masilamani TJ, Loiselle JJ, Sutherland LC (2014) Assessment of reference genes for real-time quantitative PCR gene expression normalization during C2C12 and H9c2 skeletal muscle differentiation. Mol Biotechnol 56(4):329–339. https://doi.org/10.1007/s12033-013-9712-2
Podevin N, Krauss A, Henry I, Swennen R, Remy S (2012) Selection and validation of reference genes for quantitative RT-PCR expression studies of the non-model crop Musa. Mol Breed 30(3):1237–1252. https://doi.org/10.1007/s11032-012-9711-1
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 Biol Plants 25:1097–1105. https://doi.org/10.1007/s12298-019-00684-2
Reddy DS, Bhatnagar-Mathur P, Cindhuri KS, Sharma KK (2013) Evaluation and validation of reference genes for normalization of quantitative real-time PCR based gene expression studies in peanut. PLoS ONE 8(10):e78555. https://doi.org/10.1371/journal.pone.0078555
We thanked Margaret Biswas, PhD, from Liwen Bianji, Edanz Editing China (www.liwenbianji.cn/ac), for editing the English text of a draft of this manuscript.
This work was supported by National Natural Science Foundation of China (Grant No.31770745), Key R&D Program of Jiangsu Province (Grant No. BE2017375) and Forestry Science And Technology Innovation And Promotion Program of Jiangsu Province (LYKJ40).
Conflict of interest
The authors declare that they have no conflict of interest.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Below is the link to the electronic supplementary material.
About this article
Cite this article
Chen, M., Wang, Q., Li, Y. et al. Candidate reference genes for quantitative gene expression analysis in Lagerstroemia indica. Mol Biol Rep (2021). https://doi.org/10.1007/s11033-021-06209-z
- Lagerstroemia indica
- Reference genes
- Ornamental traits
- Abiotic stresses