How to use the RefGenes tool in 4 simple steps
RefGenes is an online tool from the GENEVESTIGATOR
platform, located within the Gene Search toolset. Start it by
clicking on the START button on this website. RefGenes will be
launched with an example gene from mouse, so you will need to choose
your organism and conditions of interest.
Choose a biological context similar to your
RT-qPCR experiment The goal of RefGenes is to identify genes that
are stable in a chosen biological context. In this step, you
create a selection of microarrays from samples that were collected
in conditions similar to those in your RT-qPCRexperiment, e.g. a
similar tissue type.
Generally, we recommend to choose at least 50 microarrays from at
least three independent experiments/studies.
- Click on "New" in the Sample Selection section
- Choose organism and platform of interest (usually
default platform is fine)
- Click on "Select particular conditions"
- In the dialog that appears, select "Anatomy" and choose
a tissue type (or multiple tissue types) similar to the one(s)
in your RT-qPCR experiment
Enter your target gene of interest This step is
not essential, but it helps you to see whether your target gene is
strongly or weakly expressed in the conditions of interest
selected in STEP1. This then allows you to search for candidate
reference genes in a similar range of expression. Initially, you
enter gene identifiers (e.g. UniGene or Entrez IDs) for
transcripts you intend to measure in your RT-qPCR experiment. The
software will let you know if these genes exist in at least one
platform in GENEVESTIGATOR.
Search for the most stable genes in this biological
context Simply click on the "Run" button in the RefGenes tool.
RefGenes will show the top 20 most stable genes across the
selection of microarrays from STEP 2. Your target gene(s) of
interest entered in STEP1 are displayed in the upper section,
while candidate reference genes are shown in the lower section.
We recommend to choose three reference genes,
one in a slightly lower range of expression, one in a similar
range, and one in a slightly higher range of expression than
target genes (compare correponding boxplots). If needed, broaden
the search range by changing the numbers in the fields for
Validate candidate reference genes against a
compendium of experimental conditions Finally, candidate
reference genes proposed by RefGenes should be checked against
various other conditions.
- Create a new selection of genes containing the newly
found candidate reference genes (top right)
- Check how they respond to various conditions
(Perturbations tool in the Condition Search toolset).
This step will help you to obtain not only the most
stable candidates for a particular context, but also those that
are non-responsive to individual conditions that may occur within
your RT-qPCR experiment.
Video Tutorial For a more detailed step-by-step
introduction, please view our video about RefGenes.
Methods Data from GENEVESTIGATOR is normalized using RMA on
an experiment level, and an additional inter-experiment correction is
done by scaling the mean of the 90% quantile value of a given
experiment to a target value. Details about this normalization are
provided in the GENEVESTIGATOR
References This approach has been validated several times in
the literature and has been analyzed in detail in our own
Hruz T, Wyss M, Docquier M, Pfaffl MW, Masanetz S, Borghi
L, Verbrugge P, Kalaydjieva L, Bleuler S, Laule O, Descombes P,
Gruissem W and P Zimmermann (2011) RefGenes: identification of
reliable and condition specific reference genes for RT-qPCR data
normalization. BMC Genomics 2011, 12:156. [Abstract]
studies that identified and validated reference genes from
microarray data (earlier studies, without the use of RefGenes):
Czechowski T, Stiit M, Atlmann T, Udvardi M, Scheible W:
Genome-Wide Identification and Testing of Superior Reference Genes
for Transcript Normalization in Arabidopsis. Plant Physiol 2005,
Saviozzi S, Cordero F, Lo Iacono M,
Novello S, Scagliotti G, Calogero R: Selection of suitable reference
genes for accurate normalization of gene expression profile studies
in non-small cell lung cancer. BMC Cancer 2006, 6:200.
Hamalainen H, Tubman J, Vikman S, Kyrola T, Ylikoski E, Warrington J,
Lahesmaa R: Identification and validation of endogenous reference
genes for expression profiling of T helper cell differentiation by
quantitative real-time RT-PCR. Anal Biochem 2001, 299(1):63-70.
Gabrielsson BG, Olofsson LE, Sjogren A, Jernas M, Elander
A, Lonn M, Rudemo M, Carlsson LM: Evaluation of reference genes for
studies of gene expression in human adipose tissue. Obes Res 2005,
Stamova BS, Apperson M, Walker WL,
Tian Y, Xu H, Adamczy P, Zhan X, Liu DZ, Ander BP, Liao IH, Gregg JP,
Turner RJ, Jickling G, Lit L, Sharp FR: Identification and validation
of suitable endogenous reference genes for gene expression studies in
human peripheral blood. BMC Med Genomics 2009, 2:49.
Kwon MJ, Oh E, Lee S, Roh MR, Kim SE, Lee Y, Choi YL, In YH, Park T,
Koh SS, Shin YK: Identification of novel reference genes using
multiplatform expression data and their validation for quantitative
gene expression analysis. PLoS ONE 2009, 4:e6162.
Gur-Dedeoglu B, Konu O, Bozkurt B, Ergul G, Seckin S, Yulug IG:
Identification of endogenous reference genes for qRT-PCR analysis in
normal matched breast tumor tissues. Oncol Res 2009, 17:353-365.
Popovici V, Goldstein DR, Antonov J, Jaggi R, Delorenzi M,
Wirapati P: Selecting control genes for RT- QPCR using public
microarray data. BMC Bio formatics 2009, 10:42.
Pilbrow AP, Ellmers LJ, Black MA, Moravec CS, Sweet WE, Troughton RW,
Richards AM, Frampton CM, Cameron VA: Genomic selection of reference
genes for real-time PCR in human myocardium. BMC Med Genomics 2008,
Frericks M, Esser C: A toolbox of novel
murine house-keeping genes identified by meta-analysis of large scale
gene expression profiles. Biochim Biophys Acta 2008, 1779:830-837.
Lee S, Jo M, Lee J, Koh S, Kim S: Identification of novel
universal housekeeping genes by statistical analysis of microarray
data. Biochem Mol Biol 2007, 40(2):226-231.