Chinese Science Bulletin, Volume 58 , Issue 16 : 1919-1930(2013) https://doi.org/10.1007/s11434-013-5726-1

High-quality reference genes for quantifying the transcriptional responses of Oryza sativa L. (ssp. indica and japonica) to abiotic stress conditions

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  • AcceptedDec 10, 2012
  • PublishedMay 15, 2013



[1] Godfray H C J, Beddington J R, Crute I R, et al. Food security: The challenge of feeding 9 billion people. Science, 2010, 327: 812-818. Google Scholar

[2] Mantri N L, Ford R, Coram T E, et al. Evidence of unique and shared responses to major biotic and abiotic stresses in chickpea. Environ Exp Bot, 2010, 69: 286-292. Google Scholar

[3] Vij S, Giri J, Dansana P K, et al. The receptor-like cytoplasmic kinase (OsRLCK) gene family in rice: Organization, phylogenetic relationship, and expression during development and stress. Mol Plant, 2008, 1: 732-750. Google Scholar

[4] Zhou J, Wang X, Jiao Y, et al. Global genome expression analysis of rice in response to drought and high-salinity stresses in shoot, flag leaf, and panicle. Plant Mol Biol, 2007, 63: 591-608. Google Scholar

[5] Guenin S, Mauriat M, Pelloux J, et al. Normalization of qRT-PCR data: The necessity of adopting a systematic, experimental conditions-specific, validation of references. J Exp Bot, 2009, 60: 487-493. Google Scholar

[6] Andersen C L, Jensen J L, Orntoft T F. 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, 2004, 64: 5245-5250. Google Scholar

[7] Hu R, Fan C, Li H, et al. Evaluation of putative reference genes for gene expression normalization in soybean by quantitative real-time RT-PCR. BMC Mol Biol, 2009, 10: 93. Google Scholar

[8] Chen L, Zhong H-Y, Kuang J-F, et al. Validation of reference genes for RT-qPCR studies of gene expression in banana fruit under different experimental conditions. Planta, 2011, 234: 377-390. Google Scholar

[9] Hu R, Fan C, Li H, et al. Evaluation of putative reference genes for gene expression normalization in soybean by quantitative real-time RT-PCR. BMC Mol Biol, 2009, 10: 93-104. Google Scholar

[10] Narsai R, Ivanova A, Ng S, et al. Defining reference genes in Oryza sativa using organ, development, biotic and abiotic transcriptome datasets. BMC Plant Biol, 2010, 10: 56. Google Scholar

[11] Wang L, Xie W, Chen Y, et al. A dynamic gene expression atlas covering the entire life cycle of rice. Plant J, 2010, 61: 752-766. Google Scholar

[12] Long X Y, Liu Y X, Rocheleau H, et al. Identification and validation of internal control genes for gene expression in wheat leaves infected by strip rust. Int J Plant Breeding Genet, 2011, 5: 255-267. Google Scholar

[13] Cordoba E M, Die J V, Gonzalez-Verdejo C I, et al. Selection of reference genes in Hedysarum coronarium under various stresses and stages of development. Anal Biochem, 2011, 409: 236-243. Google Scholar

[14] Li H, Qin Y, Xiao X, et al. Screening of valid reference genes for real-time RT-PCR data normalization in Hevea brasiliensis and expression validation of a sucrose transporter gene HbSUT3. Plant Sci, 2011, 181: 132-139. Google Scholar

[15] Garg R, Sahoo A, Tyagi A K, et al. Validation of internal control genes for quantitative gene expression studies in chickpea (Cicer arietinum L.). Biochem Biophys Res Commun, 2010, 396: 283-288. Google Scholar

[16] Chen R, Gyokusen M, Nakazawa Y, et al. Selection of housekeeping genes for transgene expression analysis in Eucommia ulmoides oliver using real-time RT-PCR. J Bot, 2010, 2010: 1-7. Google Scholar

[17] Artico S, Nardeli S M, Brilhante O, et al. Identification and evaluation of new reference genes in Gossypium hirsutum for accurate normalization of real-time quantitative RT-PCR data. BMC Plant Biol, 2010, 10: 49-60. Google Scholar

[18] Lin Y L, Lai Z X. Reference gene selection for qPCR analysis during somatic embryogenesis in longan tree. Plant Sci, 2010, 178: 359-365. Google Scholar

[19] Long X Y, Wang J R, Ouellet T, et al. Genome-wide identification and evaluation of novel internal control genes for q-PCR based transcript normalization in wheat. Plant Mol Biol, 2010, 74: 307-311. Google Scholar

[20] Paolacci A R, Tanzarella O A, Porceddu E, et al. Identification and validation of reference genes for quantitative RT-PCR normalization in wheat. BMC Mol Biol, 2009, 10: 11. Google Scholar

[21] Lovdal T, Lillo C. Reference gene selection for quantitative real-time PCR normalization in tomato subjected to nitrogen, cold, and light stress. Anal Biochem, 2009, 387: 238-242. Google Scholar

[22] Jain M. Genome-wide identification of novel internal control genes for normalization of gene expression during various stages of development in rice. Plant Sci, 2009, 176: 702-706. Google Scholar

[23] Remans T, Smeets K, Opdenakker K, et al. Normalisation of real-time RT-PCR gene expression measurements in Arabidopsis thaliana exposed to increased metal concentrations. Planta, 2008, 227: 1343-1349. Google Scholar

[24] Caldana C, Scheible W R, Mueller-Roeber B, et al. A quantitative RT-PCR platform for high-throughput expression profiling of 2500 rice transcription factors. Plant Methods, 2007, 3: 7-15. Google Scholar

[25] Jain M, Nijhawan A, Tyagi A K, et al. Validation of housekeeping genes as internal control for studying gene expression in rice by quantitative real-time PCR. Biochem Biophys Res Commun, 2006, 345: 646-651. Google Scholar

[26] Pfaffl M W, Tichopad A, Prgomet C, et al. Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: Bestkeeper-excel-based tool using pair-wise correlations. Biotechnol Lett, 2004, 26: 509-515. Google Scholar

[27] Vandesompele J, De Preter K, Pattyn F, et al. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol, 2002, 3: RESEARCH0034. Google Scholar

[28] Iskandar H, Simpson R, Casu R, et al. Comparison of reference genes for quantitative real-time polymerase chain reaction analysis of gene expression in sugarcane. Plant Mol Biol Rep, 2004, 22: 325-337. Google Scholar

[29] Nicot N, Hausman J F, Hoffmann L, et al. Housekeeping gene selection for real-time RT-PCR normalization in potato during biotic and abiotic stress. J Exp Bot, 2005, 56: 2907-2914. Google Scholar

[30] Yoshida S. Fundamentals of Rice Crop Science. Philippines: IRRI, Los Banos, 1981. 121-122. Google Scholar

[31] Banyai W, Kirdmanee C, Mii M, et al. Overexpression of farnesyl pyrophosphate synthase (FPS) gene affected artemisinin content and growth of Artemisia annua L. Plant Cell Tiss Org Cult, 2010, 103: 255-265. Google Scholar

[32] Livak K J, Schmittgen T D. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-delta delta c(t)) method. Methods, 2001, 25: 402-408. Google Scholar

[33] Hellemans J, Mortier G, De Paepe A, et al. qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data. Genome Biol, 2007, 8: R19. Google Scholar

[34] Claes B, Dekeyser R, Villarroel R, et al. Characterization of a rice gene showing organ-specific expression in response to salt stress and drought. Plant Cell, 1990, 2: 19-27. Google Scholar

[35] Pramanik M H, Imai R. Functional identification of a trehalose 6-phosphate phosphatase gene that is involved in transient induction of trehalose biosynthesis during chilling stress in rice. Plant Mol Biol, 2005, 58: 751-762. Google Scholar

[36] Iordachescu M, Imai R. Trehalose biosynthesis in response to abiotic stresses. J Integr Plant Biol, 2008, 50: 1223-1229. Google Scholar

[37] Ge L-F, Chao D-Y, Shi M, et al. Overexpression of the trehalose-6-phosphate phosphatase gene OsTPP1 confers stress tolerance in rice and results in the activation of stress responsive genes. Planta, 2008, 228: 191-201. Google Scholar

[38] de Souza Filho G A, Ferreira B S, Dias J M, et al. Accumulation of salt protein in rice plants as a response to environmental stresses. Plant Sci, 2003, 164: 623-628. Google Scholar

[39] Munemasa S, Oda K, Watanabe-Sugimoto M, et al. The coronatine-insensitive 1 mutation reveals the hormonal signaling interaction between abscisic acid and methyl jasmonate in Arabidopsis guard cells. Specific impairment of ion channel activation and second messenger production. Plant Physiol, 2007, 143: 1398-1407. Google Scholar

[40] Yan J, Zhang C, Gu M, et al. The Arabidopsis coronatine insensitive1 protein is a jasmonate receptor. Plant Cell, 2009, 21: 2220-2236. Google Scholar

[41] Yanagisawa S. Dof domain proteins: Plant-specific transcription factors associated with diverse phenomena unique to plants. Plant Cell Physiol, 2004, 45: 386-391. Google Scholar

[42] Fowler S, Thomashow M F. Arabidopsis transcriptome profiling indicates that multiple regulatory pathways are activated during cold acclimation in addition to the CBF cold response pathway. Plant Cell, 2002, 14: 1675-1690. Google Scholar

[43] Chi X, Hu R, Yang Q, et al. Validation of reference genes for gene expression studies in peanut by quantitative real-time RT-PCR. Mol Genet Genomics, 2012, 287: 167-176. Google Scholar

[44] Dekkers B J W, Willems L, Bassel G W, et al. Identification of reference genes for RT-qPCR expression analysis in Arabidopsis and tomato seeds. Plant Cell Physiol, 2012, 53: 28-37. Google Scholar

[45] Manoli A, Sturaro A, Trevisan S, et al. Evaluation of candidate reference genes for qPCR in maize. J Plant Physiol, 2012, 169: 807-815. Google Scholar

[46] Pellino M, Sharbel T, Mau M, et al. Selection of reference genes for quantitative real-time PCR expression studies of microdissected reproductive tissues in apomictic and sexual boechera. BMC Res Notes, 2012, 4: 303. Google Scholar

[47] Reid K E, Olsson N, Schlosser J, et al. An optimized grapevine RNA isolation procedure and statistical determination of reference genes for real-time RT-PCR during berry development. BMC Plant Biol, 2006, 6: 27. Google Scholar

[48] Zhong H Y, Chen J W, Li C Q, et al. Selection of reliable reference genes for expression studies by reverse transcription quantitative real-time PCR in litchi under different experimental conditions. Plant Cell Rep, 2011, 30: 641-653. Google Scholar

[49] Sarkarung S. A regional breeding program to develop drought-tolerant rainfed lowland germplasm: IRRI’s experience in south and Southeast Asia. In: Fischer K S, Lafitte R, Fukai S, et al., eds. Breeding Rice for Drought-Prone Environments. Philippines: International Rice Research Institute, 2003. 70-74. Google Scholar

[50] Zhu Q, Ge S. Phylogenetic relationships among A-genome species of the genus Oryza revealed by intron sequences of four nuclear genes. New Phytol, 2005, 167: 249-265. Google Scholar


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