Systematic comparison of the fidelity of aRNA, mRNA and T-RNA on gene expression profiling using cDNA microarray.

作者: Yao Li , Tao Li , Sanzhen Liu , Minyan Qiu , Zhiyong Han

DOI: 10.1016/J.JBIOTEC.2003.09.008

关键词:

摘要: In cDNA microarray technology, there are three main reverse transcription based RNA labeling methods, using total (T-RNA), mRNA, and amplified antisense (aRNA), respectively. However, despite the common use of types RNAs, limited data available regarding their differences concordances. this report, we compared methods through two sets self-comparison experiments same sample in all cases. Within each method, duplicate hybridizations highly reproducible with low biases, which randomly produced. When combining different RNAs within a single array, correlation coefficients between channels rather low, while discrepancies persistent. Furthermore, fidelity aRNA mRNA microarrays expression profile study shows no significant difference standard T-RNA methods. These results suggest that some abundance selectively changed during amplification/mRNA purification processes, but it will not affect gene ratio samples if type used. Therefore can be used profiling analysis as long test reference generated by identical method study.

参考文章(25)
Ena Wang, Lance D. Miller, Galen A. Ohnmacht, Edison T. Liu, Francesco M. Marincola, High-fidelity mRNA amplification for gene profiling. Nature Biotechnology. ,vol. 18, pp. 457- 459 ,(2000) , 10.1038/74546
László G. Puskás, Ágnes Zvara, László Hackler, Paul Van Hummelen, RNA amplification results in reproducible microarray data with slight ratio bias BioTechniques. ,vol. 32, pp. 1330- 1340 ,(2002) , 10.2144/02326MT04
LG Puskas, A Zvara, L Hackler Jr, T Micsik, P van Hummelen, Production of bulk amounts of universal RNA for DNA microarrays. BioTechniques. ,vol. 33, pp. 898- 904 ,(2002) , 10.2144/02334MT03
Abdel G. Elkahloun, Rebbecca LeVangie, Dennis C. Sgroi, Greg Robinson, Sarena Teng, James R. Hudson, In Vivo Gene Expression Profile Analysis of Human Breast Cancer Progression Cancer Research. ,vol. 59, pp. 5656- 5661 ,(1999)
Osamu Kitahara, Chikashi Kihara, Kazunori Ochiai, Tatsuhiko Tsunoda, Aikou Okamoto, Toshihiro Tanaka, Yusuke Nakamura, Toshihisa Takagi, Kenji Ono, Identification by cDNA Microarray of Genes Involved in Ovarian Carcinogenesis Cancer Research. ,vol. 60, pp. 5007- 5011 ,(2000)
Douglas T Ross, Uwe Scherf, Michael B Eisen, Charles M Perou, Christian Rees, Paul Spellman, Vishwanath Iyer, Stefanie S Jeffrey, Matt Van de Rijn, Mark Waltham, Alexander Pergamenschikov, JC Lee, Deval Lashkari, Dari Shalon, Timothy G Myers, John N Weinstein, David Botstein, Patrick O Brown, None, Systematic variation in gene expression patterns in human cancer cell lines. Nature Genetics. ,vol. 24, pp. 227- 235 ,(2000) , 10.1038/73432
J. Eberwine, H. Yeh, K. Miyashiro, Y. Cao, S. Nair, R. Finnell, M. Zettel, P. Coleman, Analysis of gene expression in single live neurons. Proceedings of the National Academy of Sciences of the United States of America. ,vol. 89, pp. 3010- 3014 ,(1992) , 10.1073/PNAS.89.7.3010
Norman N. Iscove, Mary Barbara, Marie Gu, Meredith Gibson, Carolyn Modi, Neil Winegarden, Representation is faithfully preserved in global cDNA amplified exponentially from sub-picogram quantities of mRNA Nature Biotechnology. ,vol. 20, pp. 940- 943 ,(2002) , 10.1038/NBT729
Qing-Hai Ye, Lun-Xiu Qin, Marshonna Forgues, Ping He, Jin Woo Kim, Amy C. Peng, Richard Simon, Yan Li, Ana I. Robles, Yidong Chen, Zeng-Chen Ma, Zhi-Quan Wu, Sheng-Long Ye, Yin-Kun Liu, Zhao-You Tang, Xin Wei Wang, Predicting hepatitis B virus-positive metastatic hepatocellular carcinomas using gene expression profiling and supervised machine learning. Nature Medicine. ,vol. 9, pp. 416- 423 ,(2003) , 10.1038/NM843