|
|
|
|
|
| Validation of Reference Genes for Quantitative Real-Time PCR in Laodelphax striatellus |
| HE Xiu-ting, LIU Cheng-cheng, LI Zhao-qun, ZHANG Zan, LI Guo-qing, LI Fei , DONG Shuang- |
| Key Laboratory of Integrated Management of Crop Diseases and Pests, Ministry of Education/College of Plant Protection, Nanjing Agricultural University, Nanjing 210095, P.R.China |
|
|
|
摘要 The normalization of quantitative real-time PCR (qPCR) is important to obtain accurate gene expression data, and the most common method for qPCR normalization is to use reference genes. However, reference genes can be regulated under different conditions. qPCR has recently been used for gene expression study in Laodelphax striatellus, but there is no study on validation of the reference genes. In this study, five new housekeeping genes (LstrTUB1, LstrTUB2, LstrTUB3, LstrARF and LstrRPL9) in L. striatellus were cloned and deposited in the GenBank with accession numbers of JF728809, JF728810, JF728811, JF728807 and JF728806, respectively. Furthermore, mRNA expressions of the five genes and β-actin were measured by qPCR with insect samples of different instar at nymph stage, and the expression stabilities were determined by the software geNorm and NormFinder. As a result, ARF and RPL9 were consistently more stable than β-actin, while three TUB genes were less stable than β-actin. To determine the optimal number of reference genes used in qPCR, a pairwise variations analysis by geNorm indicated that two references ARF and RPL9 were required to obtain the accurate quantification. These results were further confirmed by the validation qPCR experiment with chitinase gene as the target gene, in which the standard error of the mRNA quantification by using binary reference ARF-RPL9 was much lower than those by ARF, RPL9 or β-actin alone. Taken together, our study suggested that the combination of ARF-RPL9 could replace β-actin as the reference genes for qPCR in L. striatellus.
Abstract The normalization of quantitative real-time PCR (qPCR) is important to obtain accurate gene expression data, and the most common method for qPCR normalization is to use reference genes. However, reference genes can be regulated under different conditions. qPCR has recently been used for gene expression study in Laodelphax striatellus, but there is no study on validation of the reference genes. In this study, five new housekeeping genes (LstrTUB1, LstrTUB2, LstrTUB3, LstrARF and LstrRPL9) in L. striatellus were cloned and deposited in the GenBank with accession numbers of JF728809, JF728810, JF728811, JF728807 and JF728806, respectively. Furthermore, mRNA expressions of the five genes and β-actin were measured by qPCR with insect samples of different instar at nymph stage, and the expression stabilities were determined by the software geNorm and NormFinder. As a result, ARF and RPL9 were consistently more stable than β-actin, while three TUB genes were less stable than β-actin. To determine the optimal number of reference genes used in qPCR, a pairwise variations analysis by geNorm indicated that two references ARF and RPL9 were required to obtain the accurate quantification. These results were further confirmed by the validation qPCR experiment with chitinase gene as the target gene, in which the standard error of the mRNA quantification by using binary reference ARF-RPL9 was much lower than those by ARF, RPL9 or β-actin alone. Taken together, our study suggested that the combination of ARF-RPL9 could replace β-actin as the reference genes for qPCR in L. striatellus.
|
|
Received: 27 February 2013
Accepted:
|
| Fund: This research is supported by the National 973 Program of China (2010CB126200), the Genetically Modified Organism Breeding Project, Ministry of Agriculture, China (2009ZX08001-002B). |
|
Corresponding Authors:
DONG Shuang-lin, Tel: +86-25-84399062, E-mail: sldong@njau.edu.cn; LI Fei, Tel: +86-25-84399025, E-mail: lifei@njau.edu.cn
E-mail: sldong@njau.edu.cn;lifei@njau.edu.cn
|
Cite this article:
HE Xiu-ting, LIU Cheng-cheng, LI Zhao-qun, ZHANG Zan, LI Guo-qing, LI Fei , DONG Shuang.
2014.
Validation of Reference Genes for Quantitative Real-Time PCR in Laodelphax striatellus. Journal of Integrative Agriculture, 13(4): 811-818.
|
| Andersen C L, Jensen J L, Ørntoft T F. 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 Research, 64, 5245-5250 Brinkhof B, Spee B, Rothuizen J, Penning L C. 2006. Development and evaluation of canine reference genes for accurate quantification of gene expression. Analytical Biochemistry, 356, 36-43 Carlyle W C, Toher C A, Vandervelde J R, McDonald K M, Homans D C, Cohn J N. 1996. Changes in β-actin mRNA expression in remodeling canine myocardium. Journal of Molecular and Cellular Cardiology, 28, 53- 63. Expósito-Rodríguez M, Borges A A, Borges-Pérez A, Borges-Pérez A, Pérez J A. 2008. Selection of internal control genes for quantitative real-time RT-PCR studies during tomato development process. BMC Plant Biology, 8, 131. Fink T, Lund P, Pilgaard L, Rasmussen J G, Duroux M, Zachar V. 2008. Instability of standard PCR reference genes in adipose-derived stem cells during propagation, differentiation and hypoxic exposure. BMC Molecular Biology, 9, 98. Foss D L, Baarsch M J, Murtaugh M P. 1998. Regulation of hypoxanthine phosphoribosyltransferase, glyceraldehyde-3-phosphate dehydrogenase and β-actin mRNA expression in porcine immune cells and tissues Animal Biotechnology, 9, 67-68 Fu Q, Zhang Z T, Hu C, Lai F X, Sun Z X. 2001. A chemically defined diet enables continuous rearing of the brown planthopper, Nilaparvata lugens (St l) (Homoptera: Delphacidae). Applied Entomology and Zoology, 36, 111-116 Gutierrez L, Mauriat M, Guénin S, Pelloux J, Lefebvre J F, Louvet R, Rusterucci C, Moritz T, Guerineau F, Bellini C, et al. 2008. The lack of a systematic validation of reference genes: a serious pitfall undervalued in reverse transcription-polymerase chain reaction (RT-PCR) analysis in plants. Plant Biotechnology Journal, 6, 609- 618. Haller F, Kulle B, Schwager S, Gunawan B, von Heydebreck A, Sultmann H, Fuzesi L. 2004. Equivalence test in quantitative reverse transcription polymerase chain reaction: confirmation of reference genes suitable for normalization. Analytical Biochemistry, 335, 1-9 Heid C A, Stevens J, Livak K J, Williams P M. 1996. Real time quantitative PCR. Genome Research, 6, 986-994 Liu S, Ding Z, Zhang C, Yang B, Liu Z. 2010. Gene knockdown by intro-thoracic injection of double- stranded RNA in the brown planthopper, Nilaparvata lugens. Insect Biochemistry and Molecular Biology, 40, 666-671 Liu S, Yang B, Gu J, Yao X, Zhang Y, Song F, Liu Z. 2008. Molecular cloning and characterization of a juvenile hormone esterase gene from brown planthopper, Nilaparvata lugens. Journal of Insect Physiology, 54, 1495-1502 Peters G P, Weber C L, Guan D, Hubacek K. 2007. China’s growing CO2 emissions - a race between increasing consumption and efficiency gains. Environmental Science and Technology, 41, 5939-5944 Ransbotyn V, Reusch T B H. 2006. Housekeeping gene selection for quantitative real-time PCR assays in the seagrass Zostera marina subjected to heat stress. Limnol Oceanogr Methods, 4, 367-373 Reid K E, Olsson N, Schlosser J, Peng F, Lund S. 2006. An optimized grapevine RNA isolation procedure and statistical determination of reference genes for real-time RT-PCR during berry development. BMC Plant Biology, 6, 27. Selvey S, Thompson E W, Matthaei K, Lea R A, Irving M G, Griffiths L R. 2001. β-Actin - an unsuitable internal control for RT-PCR. Molecular and Cellular Probes, 15, 307-311 Thellin O, Zorzi W, Lakaye B, de Borman B, Coumans B, Hennen G, Grisar T, Igout A, Heinen E. 1999. Housekeeping genes as internal standards: Use and limits. Journal of Biotechnology, 75, 291-295 Vandesompele J, de Preter K, Pattyn F, Poppe B, Roy N V, Paepe A D, Speleman F. 2002. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biology, 3, reserach0034.1-research0034.11. Wang Y, Fan H W, Huang H J, Xue J, Wu W J, Bao Y Y, Xu H J, Zhu Z R, Cheng J A, Zhang C X. 2012. Chitin synthase 1 gene and its two alternative splicing variants from two sap-sucking insects, Nilaparvata lugens and Laodelphax striatellus (Hemiptera: Delphacidae). Insect Biochemistry and Molecular Biology, 42, 637-646 Yamada H, Chen D, Monstein H J. 1997. Effects of fasting on the expression of gastrin, cholecystokinin, and somatostatin genes and of various housekeeping genes in the pancreas and upper digestive tract of rats. Biochemical and Biophysical Research Communications, 231, 835-838 Yoo W G, Kim T I, Li S, Kwon O S, Cho P Y, Kim T S, Kim K, Hong S J. 2009. Reference genes for quantitative analysis on Clonorchis sinensis gene expression by real-time PCR. Parasitology Research, 104, 321-328 Zhang S, L Li, Wang X, Zhou G. 2007. Transmission of Rice stripe virus acquired from frozen infected leaves by the small brown planthopper (Laodelphax striatellus Fallen). Journal of Virological Methods, 146, 359-362 Zhang Y J, Zhu Z F, Lu R, Xu Q, Shi L X, Jian X, Liu J Y, Yao Z. 2007. Selection of control genes in transcription analysis of gene expression. Progress in Biochemistry and Biophysics, 34, 546-550 Zhong H, Simons J W. 1999. Direct comparison of GAPDH, β-actin, cyclophilin, and 28S rRNA as internal standards for quantifying RNA levels under hypoxia. Biochemical and Biophysical Research Communications, 259, 523- 526. |
| No Suggested Reading articles found! |
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
| |
Shared |
|
|
|
|
| |
Discussed |
|
|
|
|
