[BioC] Different expression direction between limma microarray data analysis vs quantitative real time PCR result

Wang, Jixin jixinwang at tamu.edu
Wed Sep 23 01:40:56 CEST 2009


Hi Jenny,

Thanks so much for the kind help! I will check the probe and PCR product sequence to the genome and see what is going on. 

Best regards,

Wang

----- Original Message -----
From: "Jenny Drnevich" <drnevich at illinois.edu>
To: "Jixin Wang" <jixinwang at tamu.edu>, "Chao-Jen Wong" <cwon2 at fhcrc.org>
Cc: bioconductor at stat.math.ethz.ch
Sent: Tuesday, September 22, 2009 8:54:13 AM GMT -06:00 US/Canada Central
Subject: Re: [BioC] Different expression direction between limma microarray data analysis vs quantitative real time PCR result

Hi Wang,

One more alternative: it's possible that both the 
microarray data and the qRT-PCR are "correct", if 
the microarray probe and the PCR primers target 
different parts of the transcript. There could be 
a splice variant (or something) between your 
conditions, such that one part of the transcript 
is higher in one condition but another part of 
the transcript is higher in the other condition. 
I saw a similar situation once with a KO gene 
where they removed a couple exons, and PCR 
primers based on those exons showed little or no 
transcript, but the microarray probes were for a 
different exon that was actually over-expressed, 
because there was no functional protein and the 
cell was trying to increase transcription! I 
believe the MACQ project also tried to track down 
the cause of some genes having different results 
on different microarray platforms and/or qRT-PCR 
results, and in almost all of the cases the 
probes were for very different parts of the transcript.

Cheers,
Jenny

At 06:50 PM 9/21/2009, Wang, Jixin wrote:
>Hi, Chao-Jen, Thanks for kind reply. I use limma 
>for microarray data analysis. But for qRT-PCR, I 
>first selected the optimal number of internal 
>control genes by geNorm program, and then use 
>those housekeeping genes that received best 
>score for normalization of qRT-PCR. The 
>qBasePlus software (Biogazelle, Belgium) was 
>used to evaluate the relative gene expression 
>across tissues and the statistical significance 
>of the derived CNRQ values was determined by 
>SPSS 17.0 statistics software. So I don’t 
>think either microarray or real time analysis 
>has problem. Best regards, Wang ----- Original 
>Message ----- From: "Chao-Jen Wong" 
><cwon2 at fhcrc.org> To: jixinwang at tamu.edu Cc: 
>bioconductor at stat.math.ethz.ch Sent: Monday, 
>September 21, 2009 12:29:51 PM GMT -06:00 
>US/Canada Central Subject: Re: [BioC] Different 
>expression direction between limma microarray 
>data analysis vs quantitative real time PCR 
>result Hi, Jixin, Is your qRT-PCR expression 
>level represented by cycle number (Ct) for limma 
>analysis? If it is, then one thing I can think 
>of is that you need to interpret the results in 
>the opposite way. Since lower Ct means higher 
>expression level, the resulting negative t or B 
>values indicate up-regulation of the genes, not 
>down-regulation.  If I am wrong, please correct 
>me. Regards, Chao-Jen jixinwang at tamu.edu 
>wrote: > Dear all, > > I use limma package to do 
>microarray data analysis and most of real time 
>PCR validation results are consistent with 
>microarray data in terms of expression direction 
>and statistical significance. However in one set 
>of experiemnts, two DE genes are statistically 
>significant in both of microarray and qRT-PCR 
>result BUT had the different expression 
>direction. (e.g. They are  down regulated in 
>microarray result but real time PCR result 
>showed that they are up regulated)? I don’t 
>know why. Does this occur to anyone before? Many 
>thanks.  > > > Best regards, > > Wang > > 
>_______________________________________________ > 
>  Bioconductor mailing list > 
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>-- Chao-Jen Wong Program in Computational 
>Biology Division of Public Health Sciences Fred 
>Hutchinson Cancer Research Center 1100 Fairview 
>Avenue N., M2-B876 PO Box 19024 Seattle, WA 
>98109 206.667.4485 cwon2 at fhcrc.org 
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Jenny Drnevich, Ph.D.

Functional Genomics Bioinformatics Specialist
W.M. Keck Center for Comparative and Functional Genomics
Roy J. Carver Biotechnology Center
University of Illinois, Urbana-Champaign

330 ERML
1201 W. Gregory Dr.
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