Background
Traditionally, techniques for the study of gene
expression were significantly limited in both breadth and
efficiency since these studies typically allowed
investigators to study only one or a few genes at a time.
However, the recently developed DNA microarray technique is
a powerful method that provides researchers with the
opportunity to analyze the expression patterns of tens of
thousands of genes in a short time [ 1 ] . Presently,
several vendors offer these microarray systems, also known
as chips, with a variety of technologies available.
Currently, DNA microarrays are manufactured using either
cDNA or oligonucleotides as gene probes. cDNA microarrays
are created by spotting amplified cDNA fragments in a high
density pattern onto a solid substrate such as a glass
slide [ 1 2 ] . Oligonucleotide arrays are either spotted
or constructed by chemically synthesizing approximately
25-mer oligonucleotide probes directly onto a glass or
silicon surface using photolithographic technology [ 3 ]
.
Due to the powerful nature of microarrays, the number of
relevant publications in this burgeoning field is
increasing exponentially. During the years 1995-1997, the
number of reports featuring microarray data was less than
ten. However, in 2001 alone approximately 800 publications
featured data generated by microarray studies (according to
a PubMed search).
Microarray technology certainly has the potential to
greatly enhance our knowledge about gene expression, but
there are drawbacks that need to be considered. As Knight [
4 ] cautioned, it is possible that errors could be
incorporated during the manufacture of the chips.
Consequently, the fidelity of the DNA fragments immobilized
to the microarray surface may be compromised. However,
there are few studies where the majority of the gene
sequences spotted on the microarrays were verified [ 5 ] .
Kuo
et al (2002) compared the data from
two high-throughput DNA microarray technologies, cDNA
microarray (Stanford type) and oligonucleotide microarray
(from Affymetrix) and found very little correlation between
these two platforms [ 6 ] . Unfortunately, many
investigators are reporting microarray data without
confirming their results by other traditional gene
expression techniques such as PCR, Northern blot analysis
and RNase protection assay. Raw microarray data obtained
from questionable nucleotide sequences are then often
manipulated using cluster and statistical analysis software
and subsequently reported in scientific journals. In
addition the quality of the probe sequences and the
location of the probes selected for incorporation into the
array are also very important. For example, if probes are
selected only from the 3' end of a given gene, then there
is a strong possibility that different splice variants of
that gene will not be identified if the alternative
splicing occurs at the 5' region of the gene.
The development of a single chip containing the complete
gene set for a given tissue or for a complex organism
(30,000 to 60,000 genes) is likely in the near future, so
it is paramount that chip manufacturers avoid these
problems [ 7 ] . In this report, we demonstrate that
microarray technology continues to be a dynamic and
developing process and highlight potential pitfalls that
must be addressed when interpreting data.
Results
Inconsistent sequence fidelity of spotted cDNA
microarrays
cDNA microarray analysis was performed using the
UniGEM-V chip (IncyteGenomics, Palo Alto, CA) with mRNA
isolated from peripheral blood mononuclear cells (PBMC)
of a large granular lymphocyte leukemia patient and a
healthy control. In this microarray, 7075 immobilized
cDNA fragments (4107 from known genes and 2968 ESTs) were
immobilized onto a glass slide. After careful examination
of the microarray probes, it was determined that the
majority of the spotted cDNA fragments were from the 3'
end of the genes. Approximately 80 up-regulated and 12
down-regulated genes were identified in leukemic LGL. We
then purchased seventeen clones from IncyteGenomics
containing cDNA fragments that represent fourteen of the
up-regulated and three of the down-regulated genes.
Plasmid DNA was isolated from the clones and the
sequences were verified. Unfortunately, we found several
problems with the insert DNA sequences in these clones.
Four of the seventeen c DNA fragments spotted on the
microarray contained incorrect sequences (23.5%) (Table
1).
Variable reliability of differential expression
data
The cDNA fragments corresponding to differentially
expressed genes spotted on the microarrays were excised
from the plasmid DNA and used as probes in Northern
blots. Out of the seventeen only eight provided positive
results as indicated by microarray (47%). Although all
the sequences for the down-regulated genes were correct,
Northern blot analysis with these probes did not show any
differential expression of the genes. This is in contrast
to the microarray data that suggested they were down
regulated (Table 1).
Low specificity of cDNA microarray probes
By microarray analysis, it is very difficult to
distinguish between two genes that share a high degree of
sequence similarity. Low specificity of probes is also a
frequently encountered problem in oligonucleotide arrays.
This problem is especially prevalent in instances where
DNA sequences are nearly identical between two genes and
the oligonucleotide probes are generated from the 3' end
of the genes. For example, the 1.2 kb fragment (GB
Accession No. M 57888) spotted on the cDNA microarray as
granzyme B was not able to distinguish between
granzyme B and
H (Fig. 1a). The balanced
differential expression of 6.3 was calculated. A probe
set was generated by Affymetrix using the similar
sequence information (GB Accession No.M28879) and
according to oligonucleotide array,
granzyme B was shown to be
up-regulated (fold change 21.5: Fig. 1b). Northern blot
analysis (using the same fragment as probe) did not
discriminate between the genes for
granzyme B versus
granzyme H (Fig. 1c). However, by
using gene-specific probes in an RNase protection assay,
we were able to demonstrate the over-expression of
granzyme B and
granzyme H separately in leukemic
LGL cells (Fig. 1dand 1e).
Discrepancy in fold change calculation for a given
gene
It is very difficult to compare the exact fold change
between two microarray techniques, and no standard value
system is currently in place to compare the changes found
in one microarray to the next. This fact was clearly
demonstrated by Kuo et al (2002) in their recent
publication [ 6 ] . In this paper we compared the fold
change (Affymetrix) and balanced differential expression
(cDNA) with Northern blot expression. For example, our
IncyteGenomics cDNA microarray data demonstrated only a
3.8 differential expression in the expression of
perforin (Fig. 2a), a pore-forming
protein produced by cytolytic lymphocytes [ 8 ] in
leukemic LGL cells, whereas the oligonucleotide
microarray indicated a 103 fold increase (Fig. 2b). Using
a probe identical to the one spotted on the cDNA
microarray, we performed a Northern blot analysis. The
blot demonstrated the up-regulation of the
perforin transcript in leukemia LGL
cells (Fig. 2c), but the fold increase was neither 103 as
indicated by oligonucleotide array nor 3.8 as determined
by the cDNA microarray data. Instead, the actual value
was determined to fall between these two extreme values.
These observations strongly suggest that results for
significantly altered genes should be confirmed with
other traditional techniques such as Northern blots or
RNase protection assays prior to reporting the fold
increase.
Lack of probe specificity for gene isoforms
One of the genes spotted on the cDNA microarray that
we are interested in is (
Phosphatase in Activated Cells )
PAC-1 [ 9 ] . The differential
expression of
PAC-1 by both cDNA microarray
(differential expression 4.2) and oligonucleotide arrays
(fold change 1.6) is shown in Figures 3aand 3b. Using a
cDNA fragment identical to the
PAC-1 probe on the cDNA microarray,
we performed a Northern blot analysis and confirmed the
over-expression of two transcripts in leukemic LGL cells
(Fig. 3c). RT-PCR was performed using total RNA from
leukemic LGL and specific probes designed to amplify
full-length PAC-1. We did not see amplification of any
product. In addition, we found no PAC-1 expression using
two different monoclonal anti-PAC-1 antibodies in Western
blot analysis (data not shown). The monoclonal antibodies
obtained from Santa Cruz were based on the amino acid
sequence information obtained from the N-terminus and
C-terminus of the PAC-1. The results of all the
experiments did not confirm the over-expression of
PAC-1 . Therefore, to obtain more
information about the structure of the
PAC-1 related genes in leukemic
LGL, we screened an LGL leukemia cDNA library using a 1.2
kb
PAC-1 cDNA fragment and identified
similar genes which are different forms of
PAC-1 (GenBank Accession #AF331843,
the other sequence is not deposited). Similarly an
anti-apoptotic gene
A20 is also over-expressed in
leukemic LGL, but protein expression was absent when
Western blots were performed with monoclonal antibodies
raised against the amino acid sequence derived from A20
(data not shown).
Likewise, another gene of interest,
NKG2 C , showed a balanced
differential expression of 5.5 (Fig. 4a). By using a
probe derived from an
NKG2 C clone, we identified a
number of transcripts by Northern blot analysis (Fig.
4b). In order to ascertain more structural information,
we again screened the LGL leukemia library and identified
the presence of several members of the
NKG2 gene family including
NKG2 A, NKG2 D, NKG2 E and
NKG2 F (GB Accession Nos. AF461812,
AF461811, AF461157) [ 10 ] . Therefore, if genes similar
to
NKG2 family members are spotted on
a microarray, it may be difficult to confirm which form
of the gene is differentially expressed in a given
sample.
Mismatch probe sets mask the perfect match signals
in oligonucleotide array (Affymetrix)
In order to accomplish the highest sensitivity and
specificity in the presence of a complex background,
Affymetrix introduced a system that entails the use of a
series of specific and non-specific gene probe sets that
are intended to result in a more accurate discrimination
between true signal and random hybridization. Each probe
set consists of a pair of 25-mer probes, one that
represents a perfect match (PM)to the mRNA of interest,
and a second probe differing by only one nucleotide, the
mismatch (MM). The mismatch in the middle position
theoretically provides maximal disruption of
hybridization. Unfortunately, the use of the mismatch
probe information can interfere with fold change
calculations of gene expression. For example,
perforin transcripts showed strong
hybridization to both PM and MM probe sets. As a
consequence, the strong MM signal masked the PM signal
resulting in a low expression readout, even though the
gene was present in normal PBMC (Fig. 2b). Therefore, the
subsequently calculated fold increase from the test
sample was extraordinarily high and deemed unreliable.
Similarly, the fold change calculation was underestimated
for
PAC-1 due to the strong signal
displayed for MM probe set (Fig. 3b). Genes such
as human auto-antigen (GenBank
Accession #L26339) and
carboxyl ester lipase-like
protein (GenBank Accession #L14813), are additional
examples where these genes are present in LGL sample, but
because of the strong signals associated with some of the
MM probes, they are considered absent in the samples
(Fig. 5aand 5b).
Discussion
In order to identify the differentially expressed genes
in large granular lymphocytic (LGL) leukemia, we performed
microarray analysis using the UniGEM-V microarray from
IncyteGenomics and the HU6800 oligonucleotide array from
Affymetrix. In the course of our analysis, we discovered
several problems that we feel could occur in other studies
that might lead to false conclusions.
Approximately 80 up-regulated genes and 12
down-regulated genes were identified by cDNA microarray
analysis in leukemic LGL cells. Since microarray technology
was a new tool at that time, we decided to verify the
sequences of all the genes that were differentially
expressed. To that end, we purchased approximately 20
clones representing the differentially expressed genes and
verified the sequences. We found that only approximately
70% of the genes spotted on the microarray matched the
correct sequence of the clones. Other groups reported
similar observations. For example, IMAGE mouse cDNA clones
(approximately 1200) were purchased from Research Genetics
(Huntsville, Alabama) and sequences were verified by
Halgren
et al [ 11 ] . This group found that
only 62% were definitely identified as a pure sample of the
correct clones. In another study, PCR amplification
products (previously sequence-verified cDNA clones) were
re-sequenced and only 79% of the clones matched the
original database [ 12 ] . In a different study, it was
estimated that only 80% of the genes in a set of microarray
experiments were correctly identified [ 5 ] . Therefore, we
advise that when preparing cDNA microarrays (commercial or
homemade), it is necessary to sequence verify each clone at
the final stage before printing the microarray. If mistakes
are made at this stage, it is not possible to correct them
later by using the most sophisticated analytical tools.
We used cDNA microarray analysis to compare the gene
expression profile of leukemic LGL cells obtained from a
patient versus the expression profile of PBMC obtained from
a normal healthy individual as a control. We decided to
verify the microarray results using samples from more
patients by employing the use of other methods such as PCR,
Northern blot and RNase protection assay. To our surprise,
none of the three down-regulated genes studied exhibited
differential expression in Northern blots when the cDNA
fragments of these genes were used as probes. In the
up-regulated genes, only 47 % proved to support the results
from the microarray data. The rest either displayed no
signal, were not detectable in any sample or failed to
reveal any differential expression whatsoever. Although
some genes such as
PAC-1 and
A20 showed differential expression in
LGL leukemia patients, no product amplification was
obtained using RT-PCR with gene-specific primers.
By microarray analysis, it is very difficult to
distinguish between two similar genes. The best example in
our case is when
granzyme B and
granzyme H are compared. These two
genes share approximately 80% similarity at the DNA level
but have different enzymatic activities [ 13 14 ] . Using
either one of the genes as a probe, both cDNA microarray
and northern blot analysis indicated over-expression of
both genes indiscriminately (Fig. 1). However, using
gene-specific probes in an RNase protection assay, we were
able to distinctly identify the over-expression of both
granzyme B and
H in leukemic LGL cells (Fig. 1dand
1e). In normal PBMC only trace amounts of both genes were
identified, but after activation by PHA and IL2 only
granzyme B was up-regulated. It is
very difficult to get this information by microarray
analysis alone. Therefore, caution in presenting microarray
data without verification and confirmation is advised.
When the results from two different microarray
technologies (cDNA and oligonucleotide arrays) were
compared, the differential expression in some of the genes
appeared to agree in both cases but a large variation in
expression profiles between the two microarrays was clearly
evident. Previously, such systematic differences in the two
technologies were reported [ 6 ] . For example,
perforin showed a 103-fold change in
the Affymetrix array, whereas the cDNA microarray showed
only a balanced differential expression of 3.8-fold.
Northern blot results indicate that the genes were
over-expressed, but the actual value is in between the
values from the two microarrays. This problem may be due to
an inaccurate fold change calculation due to the inclusion
of mismatch values in the formula. We observed that many
over-expressed genes were not properly identified at times.
This may be the result of the introduction of mismatch
values in the Affymetrix system. For example, genes for
human autoantigen and
human carboxyl ester lipase-like
protein would be considered up-regulated in the
microarray (according to PM match hybridization) if the MM
hybridization values were ignored in the fold change
calculation.
DNA microarray anlysis can be a powerful technique to
identify differentially expressed genes but differentiating
between splice variants can be problematic. For example,
although the differential expression of the several genes
such as
PAC-1 and
A20 were confirmed by northern blot
analysis, we were unable to see any expression of protein
corresponding to these genes by Western blot analysis. We
were also unable to amplify those genes using gene-specific
primers by RT-PCR. After screening the LGL library, we
obtained several full-length genes that were different from
both the 5' and 3' ends of
PAC1 . Similarly, we screened an LGL
leukemia library and obtained several 1.5 kb cDNA fragments
using the
A20 cDNA as a probe. The deduced
amino acid sequences of these genes revealed different
proteins.
We found an up-regulation of
NKG2C with a balanced differential
expression of 5.8 in cDNA microarray (Fig. 4a). When
Northern Blot analysis was performed using
NKG2 C cDNA as a probe, we identified
multiple transcripts. Screening the LGL leukemia library
resulted in the identification of several other members of
the
NKG2 family such as
NKG2 A, D, E , and
F [ 10 ] . Therefore, it can be very
difficult to distinguish different forms of genes if they
are similar in certain sequence regions.
Conclusions
At the time of writing this report there were
approximately 1150 articles published describing microarray
results (PubMed). There is no doubt that these results will
provide an overall idea of gene expression and contribute
to understanding the molecular mechanisms involved in
various processes. However, as demonstrated by our
findings, the development of a standardized microarray
system is needed to obtain more meaningful data from these
experiments. The introduction of more uniform systems
combined with the consideration of the above described
pitfalls and alternatives will allow better utilization of
this powerful technique in an expanding collection of
scientific endeavors. It will be very helpful for the
scientific community if the verified data is deposited in a
public data base.
Methods
Isolation of PBMC and RNA
PBMC were isolated from whole blood using
Ficoll-Hypaque density gradient centrifugation. These
cells were suspended in Trizol reagent (GIBCO-BRL,
Rockville, MD) and total RNA was isolated immediately
according to the manufacturer's instructions. Poly A+ RNA
was isolated from total RNA by using Oligo-Tex mini mRNA
kit (Qiagen, Valencia, CA) according to the
manufacturer's recommendations.
Activation of PBMC
Normal PBMC were cultured
in vitro and activated by PHA,
(Sigma Chemical Co. St. Louis, MO) (1 μg/ml, 2 days) and
Interleukin-2 (IL-2) (100 U/ml, 10 days), then total RNA
was isolated.
cDNA microarray analysis
Microarray probing and analysis was performed by
IncyteGenomics. Briefly, one μg of Poly (A) + RNA
isolated from PBMC of an LGL leukemia patient and healthy
individual was reverse transcribed to generate Cy3 and
Cy5 fluorescent labeled cDNA probes. cDNA probes were
competitively hybridized to a human UniGEM-V cDNA
microarray containing approximately 7075 immobilized cDNA
fragments (4107 for known genes and 2968 for ESTs).
Microarrays were scanned in both Cy3 and Cy5 channels
with an Axon GenePix scanner (Foster City, CA) with a 10
μm resolution. P1 and P2 signals are the intensity
reading obtained by the scanner for Cy3 and Cy5 channels.
The balanced differential expression was calculated using
the ratio between the P1 signal (intensity reading for
probe 1) and the balanced P2 signal (intensity reading
for probe 2 adjusted using the balanced coefficient)
Incyte GEMtools software (Incyte Pharmaceuticals,
Inc., Palo Alto, CA) was used for image analysis. A
gridding and region detection algorithm determined the
elements. The area surrounding each element image was
used to calculate a local background and was subtracted
from the total element signal. Background subtracted
element signals were used to calculate Cy3:Cy5 ratio. The
average of the resulting total Cy3 and Cy5 signal gave a
ratio that was used to balance or normalize the
signals.
Oligonucleotide microarray analysis
The HU 6800 microarray was obtained from Affymetrix
(Santa Clara, CA). Briefly, total RNA isolated from
normal PBMC and leukemic LGL were DNase-treated and
purified with a Qiagen kit (Valencia, CA). Approximately
10 μg of purified RNA was used to prepare double-stranded
cDNA (Supercript GIBCO/BRL, Rockville, MD) using a T7
(dT)24 primer containing a T7 RNA polymerase promoter
binding site. Biotinylated complementary RNA was prepared
from 10 μg of cDNA and then fragmented to approximately
50 to 100 nucleotides.
In vitro transcribed transcripts
were hybridized to the HU 6800 microarray for 16 h at
45°C with constant rotation at 60 rpm. Chips were washed
and stained by using the Affymetrix fluidics station.
Fluorescence intensity was measured for each chip and
normalized to the fluorescence intensity for the entire
chip.
Verification of the clones
GEM cDNA clones (supplied as a bacterial stab) were
purchased from IncyteGenomics and streaked on LB agar
plates containing the appropriate antibiotic. Individual
colonies were picked and grown in LB medium. Plasmid DNA
was isolated and sequenced in order to verify the
sequence identity.
Northern blot analysis
Northern Blotting was performed as described. Briefly
10 μg of total RNA from each sample was denatured at 65°C
in RNA loading buffer, electrophoresed in a 1% agarose
gel containing 2.2 M formaldehyde, then blotted onto a
Nytran membrane (Schleicher & Schuell, Inc, Keene,
N.H). The RNA was fixed to the membrane by UV
cross-linking. cDNA was labeled with [ 32P] and purified
using Nick columns (Amersham Pharmacia Biotech AB,
Piscataway, NJ). Hybridization and washing of the blots
were performed as described by Engler-Blum et al [ 15 ]
.
RNase protection assay (RPA)
RPAs were performed using the RNA isolated from
leukemic LGL, normal PBMC and normal PBMC activated by
IL-2 and PHA. Five μg of total RNA was hybridized to the
in vitro transcribed hAPO-4 probe
set (PharMingen, SanDiego, CA), and the RPA assay was
performed according to the manufacturer's protocol. After
the assay, the samples were resolved on a 5%
polyacrylamide gel. The gel was dried and exposed to
X-ray film. After developing the film, the bands were
quantitated by using the ImageQuant program and
normalized with the housekeeping gene, L32.
Western immunoblot analysis
Cells were lysed in a buffer containing 50 mM Tris-HCl
(pH 7.6), 5 mM EDTA, 150 mM NaCl, 0.5 % NP-40, and 0.5%
Triton X-100 containing 1 μg/ml leupeptin, aprotinin and
antipain; 1 mM sodiumorthovanadate; and 0.5 mM PMSF (all
reagents were obtained from Sigma Chemical Co.).
Twenty-five μg of total protein from each sample was
subjected to 10% SDS-PAGE. Then the proteins were
transferred to a membrane and Western blotting was
performed using the monoclonal antibody for PAC-1 and
A20, followed by the ECL technique as recommended by the
manufacturer (Amersham Biosciences, Piscataway, NJ).
Authors' contributions
RK conceived of the study along with TPL, isolated,
purified RNA from the samples for microarray and performed
all the experiments to validate the microarray data and
analysed the data and drafted the manuscript. SJY verified
the microarray data and participated in validation of the
microarray. SM performed microarray analysis and analyzed
the data and TPL conceived of the study, and participated
in its design and coordination.
