Evaluation of Candidate Reference Genes for Normalization of Quantitative RT-PCR in Soybean Tissues Under Various Abiotic Stress Conditions

Overview

Journal PLoS One

Specialties General Medicine
Science

Date 2012 Oct 3

PMID 23029532

Citations 71

Authors

Dung Tien Le

Donavan L Aldrich

Babu Valliyodan

Yasuko Watanabe

Chien Van Ha

Rie Nishiyama

Satish K Guttikonda

Truyen N Quach

Juan J Gutierrez-Gonzalez

Lam-Son Phan Tran

Henry T Nguyen

Affiliations

Soon will be listed here.

Abstract

Quantitative RT-PCR can be a very sensitive and powerful technique for measuring differential gene expression. Changes in gene expression induced by abiotic stresses are complex and multifaceted, which make determining stably expressed genes for data normalization difficult. To identify the most suitable reference genes for abiotic stress studies in soybean, 13 candidate genes collected from literature were evaluated for stability of expression under dehydration, high salinity, cold and ABA (abscisic acid) treatments using delta CT and geNorm approaches. Validation of reference genes indicated that the best reference genes are tissue- and stress-dependent. With respect to dehydration treatment, the Fbox/ABC, Fbox/60s gene pairs were found to have the highest expression stability in the root and shoot tissues of soybean seedlings, respectively. Fbox and 60s genes are the most suitable reference genes across dehydrated root and shoot tissues. Under salt stress the ELF1b/IDE and Fbox/ELF1b are the most stably expressed gene pairs in roots and shoots, respectively, while 60s/Fbox is the best gene pair in both tissues. For studying cold stress in roots or shoots, IDE/60s and Fbox/Act27 are good reference gene pairs, respectively. With regard to gene expression analysis under ABA treatment in either roots, shoots or across these tissues, 60s/ELF1b, ELF1b/Fbox and 60s/ELF1b are the most suitable reference genes, respectively. The expression of ELF1b/60s, 60s/Fbox and 60s/Fbox genes was most stable in roots, shoots and both tissues, respectively, under various stresses studied. Among the genes tested, 60s was found to be the best reference gene in different tissues and under various stress conditions. The highly ranked reference genes identified from this study were proved to be capable of detecting subtle differences in expression rates that otherwise would be missed if a less stable reference gene was used.

Citing Articles

Meta-analysis of plant growth-promoting rhizobacteria interaction with host plants: implications for drought stress response gene expression.

Ferrante R, Campagni C, Vettori C, Checcucci A, Garosi C, Paffetti D Front Plant Sci. 2024; 14:1282553.

PMID: 38288406 PMC: 10823023. DOI: 10.3389/fpls.2023.1282553.

H2O2-dependent oxidation of the transcription factor GmNTL1 promotes salt tolerance in soybean.

Zhang W, Zhi W, Qiao H, Huang J, Li S, Lu Q Plant Cell. 2023; 36(1):112-135.

PMID: 37770034 PMC: 10734621. DOI: 10.1093/plcell/koad250.

Transcriptomic analysis of humic acid in relieving the inhibitory effect of high nitrogen on soybean nodulation.

Zhang W, Li J, Li H, Zhang D, Zhu B, Yuan H Front Plant Sci. 2023; 14:1196939.

PMID: 37564385 PMC: 10410467. DOI: 10.3389/fpls.2023.1196939.

Reference genes identification for qRT-PCR normalization of gene expression analysis in under infection and treatment.

Ji T, Ma S, Liang M, Wang X, Gao L, Tian Y Front Plant Sci. 2023; 13:1061921.

PMID: 36589116 PMC: 9799720. DOI: 10.3389/fpls.2022.1061921.

Isolation and Functional Characterization of Soybean BES1/BZR1 Homolog 3-Like 1 (GmBEH3L1) Associated with Dehydration Sensitivity and Brassinosteroid Signaling in Arabidopsis thaliana.

Park C, Nguyen V, Min J, Sang H, Lim G, Kim C Plants (Basel). 2022; 11(19).

PMID: 36235431 PMC: 9573144. DOI: 10.3390/plants11192565.

References

Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A . Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol. 2002; 3(7):RESEARCH0034. PMC: 126239. DOI: 10.1186/gb-2002-3-7-research0034. View

Tang T, Francois N, Glatigny A, Agier N, Mucchielli M, Aggerbeck L . Expression ratio evaluation in two-colour microarray experiments is significantly improved by correcting image misalignment. Bioinformatics. 2007; 23(20):2686-91. DOI: 10.1093/bioinformatics/btm399. View

Nolan T, Hands R, Bustin S . Quantification of mRNA using real-time RT-PCR. Nat Protoc. 2007; 1(3):1559-82. DOI: 10.1038/nprot.2006.236. View

Nishiyama R, Watanabe Y, Fujita Y, Le D, Kojima M, Werner T . Analysis of cytokinin mutants and regulation of cytokinin metabolic genes reveals important regulatory roles of cytokinins in drought, salt and abscisic acid responses, and abscisic acid biosynthesis. Plant Cell. 2011; 23(6):2169-83. PMC: 3160038. DOI: 10.1105/tpc.111.087395. View

Valliyodan B, Nguyen H . Understanding regulatory networks and engineering for enhanced drought tolerance in plants. Curr Opin Plant Biol. 2006; 9(2):189-95. DOI: 10.1016/j.pbi.2006.01.019. View

Tran L, Nishiyama R, Yamaguchi-Shinozaki K, Shinozaki K . Potential utilization of NAC transcription factors to enhance abiotic stress tolerance in plants by biotechnological approach. GM Crops. 2011; 1(1):32-9. DOI: 10.4161/gmcr.1.1.10569. View

Ginzinger D . Gene quantification using real-time quantitative PCR: an emerging technology hits the mainstream. Exp Hematol. 2002; 30(6):503-12. DOI: 10.1016/s0301-472x(02)00806-8. View

Stolf-Moreira R, Medri M, Neumaier N, Lemos N, Brogin R, Marcelino F . Cloning and quantitative expression analysis of drought-induced genes in soybean. Genet Mol Res. 2010; 9(2):858-67. DOI: 10.4238/vol9-2gmr701. View

Ruijter J, Ramakers C, Hoogaars W, Karlen Y, Bakker O, van den Hoff M . Amplification efficiency: linking baseline and bias in the analysis of quantitative PCR data. Nucleic Acids Res. 2009; 37(6):e45. PMC: 2665230. DOI: 10.1093/nar/gkp045. View

10.

Ramakers C, Ruijter J, Lekanne Deprez R, Moorman A . Assumption-free analysis of quantitative real-time polymerase chain reaction (PCR) data. Neurosci Lett. 2003; 339(1):62-6. DOI: 10.1016/s0304-3940(02)01423-4. View

11.

Matsui A, Ishida J, Morosawa T, Mochizuki Y, Kaminuma E, Endo T . Arabidopsis transcriptome analysis under drought, cold, high-salinity and ABA treatment conditions using a tiling array. Plant Cell Physiol. 2008; 49(8):1135-49. DOI: 10.1093/pcp/pcn101. View

12.

Tran L, Nakashima K, Shinozaki K, Yamaguchi-Shinozaki K . Plant gene networks in osmotic stress response: from genes to regulatory networks. Methods Enzymol. 2007; 428:109-28. DOI: 10.1016/S0076-6879(07)28006-1. View

13.

Kodaira K, Qin F, Tran L, Maruyama K, Kidokoro S, Fujita Y . Arabidopsis Cys2/His2 zinc-finger proteins AZF1 and AZF2 negatively regulate abscisic acid-repressive and auxin-inducible genes under abiotic stress conditions. Plant Physiol. 2011; 157(2):742-56. PMC: 3192566. DOI: 10.1104/pp.111.182683. View

14.

Seki M, Narusaka M, Ishida J, Nanjo T, Fujita M, Oono Y . Monitoring the expression profiles of 7000 Arabidopsis genes under drought, cold and high-salinity stresses using a full-length cDNA microarray. Plant J. 2002; 31(3):279-92. DOI: 10.1046/j.1365-313x.2002.01359.x. View

15.

Pereira S, Guimaraes F, Carvalho J, Stolf-Moreira R, Oliveira M, Rolla A . Transcription factors expressed in soybean roots under drought stress. Genet Mol Res. 2011; 10(4):3689-701. DOI: 10.4238/2011.October.21.5. View

16.

Choudhary S, Oral H, Bhardwaj R, Yu J, Tran L . Interaction of brassinosteroids and polyamines enhances copper stress tolerance in raphanus sativus. J Exp Bot. 2012; 63(15):5659-75. PMC: 3444278. DOI: 10.1093/jxb/ers219. View

17.

Toda K, Takahashi R, Iwashina T, Hajika M . Difference in chilling-induced flavonoid profiles, antioxidant activity and chilling tolerance between soybean near-isogenic lines for the pubescence color gene. J Plant Res. 2010; 124(1):173-82. DOI: 10.1007/s10265-010-0345-2. View

18.

Nouri M, Hiraga S, Yanagawa Y, Sunohara Y, Matsumoto H, Komatsu S . Characterization of calnexin in soybean roots and hypocotyls under osmotic stress. Phytochemistry. 2011; 74:20-9. DOI: 10.1016/j.phytochem.2011.11.005. View

19.

Fujita Y, Fujita M, Shinozaki K, Yamaguchi-Shinozaki K . ABA-mediated transcriptional regulation in response to osmotic stress in plants. J Plant Res. 2011; 124(4):509-25. DOI: 10.1007/s10265-011-0412-3. View

20.

Le D, Nishiyama R, Watanabe Y, Mochida K, Yamaguchi-Shinozaki K, Shinozaki K . Genome-wide survey and expression analysis of the plant-specific NAC transcription factor family in soybean during development and dehydration stress. DNA Res. 2011; 18(4):263-76. PMC: 3158466. DOI: 10.1093/dnares/dsr015. View