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Open Access Highly Accessed Research article

Validation of internal control for gene expression study in soybean by quantitative real-time PCR

Bo Jian12, Bin Liu2, Yurong Bi1, Wensheng Hou2, Cunxiang Wu2 and Tianfu Han2*

Author Affiliations

1 School of Life Sciences, Lanzhou University, Lanzhou, Gansu 730000, PR China

2 The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI), Institute of Crop Sciences, The Chinese Academy of Agricultural Sciences, Beijing 100081, PR China

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BMC Molecular Biology 2008, 9:59  doi:10.1186/1471-2199-9-59

Published: 23 June 2008

Abstract

Background

Normalizing to housekeeping gene (HKG) can make results from quantitative real-time PCR (qRT-PCR) more reliable. Recent studies have shown that no single HKG is universal for all experiments. Thus, a suitable HKG should be selected before its use. Only a few studies on HKGs have been done in plants, and none in soybean, an economically important crop. Therefore, the present study was conducted to identify suitable HKG(s) for normalization of gene expression in soybean.

Results

All ten HKGs displayed a wide range of Ct values in 21 sample pools, confirming that they were variably expressed. GeNorm was used to determine the expression stability of the HGKs in seven series sets. For all the sample pools analyzed, the stability rank was ELF1B, CYP2 > ACT11 > TUA > ELF1A > UBC2 > ACT2/7 > TUB > G6PD > UBQ10. For different tissues under the same developmental stage, the rank was ELF1B, CYP2 > ACT2/7 > UBC2 > TUA > ELF1A > ACT11 > TUB > G6PD > UBQ10. For the developmental stage series, the stability rank was ACT2/7, TUA > ELF1A > UBC2 > ELF1B > TUB > CYP2 > ACT11 > G6PD > UBQ10. For photoperiodic treatments, the rank was ACT11, ELF1B > CYP2 > TUA > ELF1A > UBC2 > ACT2/7 > TUB > G6PD > UBQ10. For different times of the day, the rank was ELF1A, TUA > ELF1B > G6PD > CYP2 > ACT11 > ACT2/7 > TUB > UBC2 > UBQ10. For different cultivars and leaves on different nodes of the main stem, the ten HKGs' stability did not differ significantly. ΔCt approach and 'Stability index' were also used to analyze the expression stability in all 21 sample pools. Results from ΔCt approach and geNorm indicated that ELF1B and CYP2 were the most stable HKGs, and UBQ10 and G6PD the most variable ones. Results from 'Stability index' analysis were different, with ACT11 and CYP2 being the most stable HKGs, and ELF1A and TUA the most variable ones.

Conclusion

Our data suggests that HKGs are expressed variably in soybean. Based on the results from geNorm and ΔCt analysis, ELF1B and CYP2 could be used as internal controls to normalize gene expression in soybean, while UBQ10 and G6PD should be avoided. To achieve accurate results, some conditions may require more than one HKG to be used for normalization.