Literature DB >> 15088380

Comparison of mRNA gene expression by RT-PCR and DNA microarray.

Wiguins Etienne1, Martha H Meyer, Johnny Peppers, Ralph A Meyer.   

Abstract

Few studies have compared the quantification of mRNA by DNA microarray to the results obtained by reverse transcription PCR (RT-PCR). In this study, mRNA was collected from the healing femoral fracture callus of adult and juvenile rats at various times after fracture. Ten samples were measured by both methods for 26 genes. For RT-PCR, mRNA was reverse transcribed, amplified, electrophoresed, blotted, and probed with 32P-labeled internal oligonucleotides, which were quantified. For DNA microarray, the mRNA was processed to biotin-labeled cRNA, hybridized to 10 Affymetrix Rat U34A microarrays, and quantified. Correlation coefficients (r) for each gene for the agreement between RT-PCR and microarray ranged from -0.48 to +0.93. This variation made the interpretation gene-specific. Genes with moderate expression levels gave the highest r values. Increased numbers of absent calls by the microarray software and increased separation between the location of the PCR primers and the microarray probes both led to reduced agreement. Microarray analysis suggested a floor effect in expression levels measured by RT-PCR for two genes. In conclusion, moderate mRNA expression levels with overlap in the location of PCR primers and microarray probes can yield good agreement between these two methods.

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Year:  2004        PMID: 15088380     DOI: 10.2144/04364ST02

Source DB:  PubMed          Journal:  Biotechniques        ISSN: 0736-6205            Impact factor:   1.993


  64 in total

1.  Translational Regulation of the Mitochondrial Genome Following Redistribution of Mitochondrial MicroRNA in the Diabetic Heart.

Authors:  Rajaganapathi Jagannathan; Dharendra Thapa; Cody E Nichols; Danielle L Shepherd; Janelle C Stricker; Tara L Croston; Walter A Baseler; Sara E Lewis; Ivan Martinez; John M Hollander
Journal:  Circ Cardiovasc Genet       Date:  2015-09-16

Review 2.  Molecular genetic studies of gene identification for osteoporosis: a 2004 update.

Authors:  Yong-Jun Liu; Hui Shen; Peng Xiao; Dong-Hai Xiong; Li-Hua Li; Robert R Recker; Hong-Wen Deng
Journal:  J Bone Miner Res       Date:  2006-10       Impact factor: 6.741

3.  Interleukin-6-mediated signaling in adrenal medullary chromaffin cells.

Authors:  Danielle E Jenkins; Dharshini Sreenivasan; Fiona Carman; Babru Samal; Lee E Eiden; Stephen J Bunn
Journal:  J Neurochem       Date:  2016-12-05       Impact factor: 5.372

4.  Comprehensive analysis of human endogenous retrovirus transcriptional activity in human tissues with a retrovirus-specific microarray.

Authors:  Wolfgang Seifarth; Oliver Frank; Udo Zeilfelder; Birgit Spiess; Alex D Greenwood; Rüdiger Hehlmann; Christine Leib-Mösch
Journal:  J Virol       Date:  2005-01       Impact factor: 5.103

5.  Analysis of variance components reveals the contribution of sample processing to transcript variation.

Authors:  Douwe van der Veen; José Miguel Oliveira; Willy A M van den Berg; Leo H de Graaff
Journal:  Appl Environ Microbiol       Date:  2009-02-20       Impact factor: 4.792

6.  Combined effects of blood and temperature shift on Borrelia burgdorferi gene expression as determined by whole genome DNA array.

Authors:  Rafal Tokarz; Julie M Anderton; Laura I Katona; Jorge L Benach
Journal:  Infect Immun       Date:  2004-09       Impact factor: 3.441

7.  Network analysis of endogenous gene expression profiles after polyethyleneimine-mediated DNA delivery.

Authors:  Timothy M Martin; Sarah A Plautz; Angela K Pannier
Journal:  J Gene Med       Date:  2013 Mar-Apr       Impact factor: 4.565

Review 8.  The role of gene expression in ecological speciation.

Authors:  Scott A Pavey; Hélène Collin; Patrik Nosil; Sean M Rogers
Journal:  Ann N Y Acad Sci       Date:  2010-09       Impact factor: 5.691

9.  MicroRNA profiling of BRCA1/2 mutation-carrying and non-mutation-carrying high-grade serous carcinomas of ovary.

Authors:  Cheng-Han Lee; Subbaya Subramanian; Andrew H Beck; Inigo Espinosa; Janine Senz; Shirley X Zhu; David Huntsman; Matt van de Rijn; C Blake Gilks
Journal:  PLoS One       Date:  2009-10-02       Impact factor: 3.240

10.  An efficient algorithm for the stochastic simulation of the hybridization of DNA to microarrays.

Authors:  Erdem Arslan; Ian J Laurenzi
Journal:  BMC Bioinformatics       Date:  2009-12-10       Impact factor: 3.169

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