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Is RNA Amplification Necessary for Microarrays?
RNA amplification using the Van Gelder and
Eberwine technique (1) has been used extensively for target
synthesis and labeling in array analysis experiments. Amplification
of RNA is clearly necessary when working with limited samples
(needle biopsies, LCM samples, etc.), but is it necessary when
the availability of sample is not limiting? Is there additional
biologically relevant information that can be obtained from
array analysis using amplified RNA as a target? In this article
we provide a brief synopsis of the findings of Polacek et al.
(2) and Feldman et al. (3) on why amplified RNA (aRNA) might
be a better choice than unamplified RNA for microarrays.
The Polacek Experiments
Polacek's group tested the fidelity
of differential gene expression data using amplified RNA in
a well established in vitro model of cytokine [tumor necrosis
factor (TNF-α)]-stimulated human aortic endothelial cells
(HAEC). 100 ng of total RNA, isolated from HAECs using a glass
filter based kit, was amplified using Ambion's MessageAmp™ aRNA
Kit, producing 4-5 µg of aRNA (cRNA). 2 µg of
this aRNA was labeled with 33P by reverse transcription
using hexanucleotide random primers; 10 µg of Total RNA
(unamplified) was labeled with 33P by reverse transcription
using Oligo d(T)15 primers. These targets
were hybridized to arrays containing 13,284 human cDNA elements.
Analysis of differential gene expression in
the cells treated with TNF-α compared to untreated control cells
identified 1296 genes in the amplified samples and 155 genes
in the unamplified samples whose expression was affected by cytokine
treatment. By comparing genes identified with probe prepared
by both amplified and unamplified RNA, three categories were
created: "genes common in amplified and unamplified RNA", "genes
unique to amplified RNA", and "genes unique to unamplified RNA" (Figure
1). Real-time quantitative RT-PCR (qRT-PCR) analysis
using SYBR® Green detection of expression differences
of a subset of the genes from each category was carried out.
A summary of the observed results from qRT-PCR analysis and array
analysis is shown in Table 1. The following conclusions were
drawn from these validation studies:
(A) Because genes were
identified as having differential expression with both preparations
of labeled target, "common identified genes" are considered to
have the highest probability of being verifiably regulated by
TNF-α. In general, the ratio of gene expression with and without
TNF-α treatment from amplified RNA had a closer correlation with
the qRT-PCR data than ratios from unamplified RNA. 94% of the "common
identified genes" show similar kinase-regulation patterns between
amplified and unamplified samples.
(B) "Genes unique
to amplified RNA" were ranked by P-values, and 24 genes (2.1%
of the total 1,150) were selected from the entire range of
P-values for validation by qRT-PCR. Similar regulation patterns
between array and qRT-PCR analysis were observed in 16 of the
24 genes tested.
(C) Six from the
category of "genes unique to unamplified RNA" were validated
by qRT-PCR. Of these, three genes showed a similar expression
ratio by qRT-PCR analysis.
Thus amplification improved the sensitivity
of the array analysis, enabling the identification of biologically
regulated genes that might have been missed if unamplified
RNA had been used.
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Figure 1. Venn
Diagrams Showing the Differential Distribution of Genes
Expressed With and Without TNF-α Treatment. Of
the total 13,284 genes tested, 1,296 were identified
from amplified RNA vs. 146 genes that are commonly
represented in both samples. |
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Table 1. Microarray
Results. This
study involved the comparison of multiple replicate
arrays for each condition tested: (+TNF-α and TNF-α)
with use of four unamplified and five amplified RNA
samples. The gene expression ratios between microarray
and quantitative RT-PCR data is presented in this table.
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The Feldman Experiments
Feldman et al. evaluated the fidelity
of microarrays probed with amplified vs. total RNA by comparing
microarray data with real-time qRT-PCR. They compared gene
expression in two murine tumor cell lines (B16F10 and MC38)
using mouse microarrays containing 2601 elements. In their
experiments, all array hybridizations were repeated using reciprocal
fluorescence to minimize the effects of labeling bias (i.e.
each array was hybridized with with Cy™3 labeled
B16F10 RNA and Cy5 labeled MC38 RNA, and then a second identical
array was hybridized with Cy5 labeled B16F10 RNA and Cy3 labeled
MC38 RNA).
The following differences were observed
between total RNA and amplified RNA samples:
(A) Correlation coefficients between
reciprocal arrays were consistently higher with probes generated
by a single or two rounds of amplification than with probes
from unamplified RNA.
(B) Total RNA samples showed a
higher correlation between duplicate forward or reciprocal
arrays than between forward and reciprocal arrays. This was
probably partially due to labeling bias. Total RNA also showed
increased variability between duplicate arrays compared to
amplified RNA. The authors speculate that data generated with
total RNA (unamplified) may be more subject to the effects
of background on the low-copy number transcripts than amplified
RNA.
(C) The correlation between arrays
using total RNA and amplified RNA was found to be similar to
duplicate arrays probed with total RNA. This observation corroborates
the finding that amplification does not significantly bias
the gene expression data.
The authors further evaluated whether
the individual genes that were differentially expressed in
amplified samples would have been identified as such using
total RNA. For this experiment, the number of "outliers" defined
by authors as "A gene with expression ratios of greater than
or equal to 2.0 or less than or equal to 0.5 in two reciprocal
microarray analysis" identified using total RNA or amplified
RNA (one or two rounds of amplification) were compared. The
amplified samples identified approximately 80% of the genes
selected as outliers with total RNA, with an 80% concordance
between target made by one and two rounds of amplification.
Thus amplification yielded approximately 2 times more outliers
than total RNA, with 80% of these showing similar trends in
expression between amplified and total RNA samples. Validation
of the "outliers" between total RNA and amplified RNA was carried
out using real-time PCR analysis. The PCR data suggested that
the majority of outliers identified using amplified RNA are
valid. Thus Feldman et al. also conclude that all RNA samples
should undergo at least one round of amplification to maximize
the quality of array data for detection of differentially expressed
genes.
SYBR Green is a registered trademark of Molecular
Probes, Inc.
Cy is a trademark of Amersham Biosciences.
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