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A comparison of gel-based, nylon filter and microarray
techniques to detect differential RNA expression in plants
Don Baldwin*, Virginia Crane† and Douglas Rice‡
An initial application of plant genomics has been to monitor
gene expression on a scale much larger than previously
possible. Although multiplexed assays of RNA abundance have
developed more quickly than those for protein and metabolite
levels, some combination of these approaches will soon be
providing our best views yet into plant molecular biology. Three
techniques that have made contributions to the RNA transcript
portion of this combination are reviewed. Currently, each can
produce a profile of expression levels for a large but
incomplete set of plant genes, at reproducibly high levels of
accuracy and over a range of labor and financial expenses.
Addresses
Disease Resistance Group, Trait and Technology Development
Pioneer Hi-Bred International Inc., 7300 NW 62nd Ave., Johnston,
IA 50131-1004, USA
*e-mail: [email protected]
† e-mail: [email protected]
‡ e-mail: [email protected]
Current Opinion in Plant Biology 1999, 2:96–103
http://biomednet.com/elecref/1369526600200096
© Elsevier Science Ltd ISSN 1369-5266
Abbreviations
AFLP
amplified fragment length polymorphism
AP-PCR arbitrarily primed PCR
cDNA
complementary deoxyribonucleic acid
cRNA
complementary ribonucleic acid
EST
expressed sequence tag
HD
high-density
MTAP
Microarray Technology Access Program
PCR
polymerase chain reaction
Introduction
The ability to generate profiles of the abundance of RNA
transcripts has numerous applications in plant biology
including identification of tissue-specific or organ-specific
transcripts, developmental stage-specific transcripts, transcripts induced by environmental stresses, and transcripts
induced or repressed upon pathogen infection. Generally,
biologists are interested in those genes expressed differentially in two or more populations of RNA transcripts. In the
past, differentially expressed genes were usually identified
by subtractive hybridizations, differential plaque hybridizations, or protein gel differences, followed by
micro-sequencing or using antibodies to clone cDNAs. As
large sequence databases become available for plants, the
number of genes we would like to monitor becomes too
large for traditional analyses such as Northern blots. Ideally,
an expression assay covering all genes in the plant cell will
reveal how patterns change during differentiation, growth,
response to stress, etc. In the past few years, several techniques have become available to monitor the expression of
large numbers of genes. Most of these techniques are based
on gel fractionation of cDNAs or hybridization to DNAs
immobilized on a solid support. Another approach, not discussed further in this review, is sequencing-intensive and
includes the serial analysis of gene expression [1] and ‘electronic Northerns’ in which the representation of sequences
in a database is used to measure the abundance of a particular transcript. The following comparison of methods for
detecting differential RNA expression includes gel-based
AFLP assays of cDNA, nylon filter arrays and two types of
microarrays. Examples using each of these three methods
in functional genomics research are referenced, and the
next step up in scale for the plant portion of this field is
illustrated by a brief look at some of the projects from the
NSF Plant Genome Research Program.
Gel-based transcript profiles
The first RNA profiling techniques developed were ‘differential display’ by Liang and Pardee [2] and arbitrarily
primed (AP) PCR by Welsh et al. [3], both of which use
arbitrary primers to amplify portions of cDNAs which are
then fractionated on a polyacrylamide sequencing gel. The
main difference between the two methods is that differential display uses an anchored oligo-dT primer plus one
arbitrary primer, whereas AP-PCR is not anchored to the
3′-end. Differential display has been used widely because it
is fast, inexpensive, sensitive and simple to perform. The
two techniques that it uses, PCR and denaturing polyacrylamide gel electrophoresis, are routine in molecular biology
labs. If a sufficient number of primers are tested, it should
be possible to identify most transcripts in an mRNA sample. A protocol is given in [4]. Differential display has been
used to isolate a large number of plant genes differentially
expressed during development [5,6], hormone response
[7,8], environmental stresses [9,10], defense responses
[11,12,13•] and nodule formation [14,15].
In spite of its popularity, differential display has several drawbacks. First, the number of false positives generated by this
technique can be unacceptable. The annealing of the arbitrary primers to the cDNA is done at relatively low
temperatures (e.g. 40°C), reducing some priming specificity
and producing autoradiograph band differences that do not
reflect real differences in gene expression. Recognized by
many as a major problem with conventional differential display, nonspecific priming can be reduced through
modifications to both the arbitrary and oligo-dT primers [16].
This problem can also be minimized by performing a number of replicate experiments, preferably using different RNA
preparations and PCR reactions, and only isolating bands
that are consistently, differentially represented. A second difficulty is that the fragments generated include only several
hundred bases from the 3′-end. Sequence from this region is
often insufficient to identify a gene, especially when using a
Microarray techniques to detect differential RNA expression in plants Baldwin, Crane and Rice
Some of the above drawbacks of differential display have
been overcome with amplified restriction fragment length
polymorphism (AFLP) of cDNA, as shown by Bachem et al.
[21] in the first application of this method for plant biology.
In this technique, the cDNA population is cut with two
restriction enzymes and adapters are ligated onto the resulting cohesive ends. Selective PCR primers that extend past
the adapters into the cDNA are used in the subsequent
amplification to reduce the number of bands present on the
denaturing gel. Again, the procedure is simple and rapidly
performed, and the number of mRNA species visualized is
limited only by how many pairs of restriction enzymes are
tried. The main advantage is stringent primer hybridization
to the adapters, thus reducing the variability of traditional
differential display. Also, because amplification can originate from any region of the cDNA there is a higher chance
of detecting homology to related genes in EST databases.
The problem of heterogeneity in the reamplified bands
must still be addressed when performing AFLP of cDNA.
Both gel-based methods of transcript profiling are very
useful and are easily and inexpensively performed. They
do not rely on EST databases or existing cDNA libraries,
allow detection of rare transcripts, and require relatively
small amounts of mRNA. The main disadvantages
include heterogeneity of final products, the need to clone
and sequence the product for identification, and the need
to isolate a full-length cDNA after obtaining the PCR
product. At Pioneer Hi-Bred, we are fortunate to have
access to the RNA profiling performed by the CuraGen
Figure 1
Defense
response
Band intensity
database from an unrelated organism. As a result, one must
often isolate a longer cDNA clone to identify the differentially expressed gene. Recent modifications to address this
problem include the development of long-distance differential display PCR, using hot start and rTth DNA polymerase
[17]. Finally, a third problem arises during cloning of the
identified fragment. Although the band can be excised from
the sequencing gel with surprising accuracy, there are usually several species of cDNA present in a band, leading to a
mixed population of candidates after reamplification and
cloning. We generally sequence six clones per band; we usually see a predominant species represented but sometimes
multiple Northern blots are required to identify the differentially expressed clone. A recent report comparing
expression in normal and mammoplastic epithelial tissues
describes dramatic reduction in the number of false positives
using gene-specific primers to reamplify differential display
products (bands were sequenced directly from the gel). Of
104 differentially displayed bands analyzed, 86% provided
readable sequencing runs [18]. This allowed identification of
62 differentially expressed genes, 32 of which matched
human ESTs of unknown function. This type of analysis
shows the value of RNA profiling for placing uncharacterized
ESTs into functional context. More often, high-throughput
screens such as dot-blot arrays are now being used in conjunction with more sensitive probes (e.g. riboprobes) to
increase the success rate of differential display [19,20].
97
Control
Band length (bp)
Current Opinion in Plant Biology
Fluorescence electropherograms from a CuraGen analysis.
Disease-resistant maize leaves were infected with a fungal pathogen,
Cochliobolus carbonum, for six hours. Replicate profiles of
RNA-derived fragments expressed during the resulting defense
response are compared to gel traces from control plants. The 47
base-pair band was induced 3.1-fold.
Corporation. PCR-amplified cDNA fragments are labeled
with fluorescent probes, run on a denaturing gel, and
detected by a fluorescence gel scanner. The resulting
electropherograms (Figure 1) look similar to a trace from
an automated DNA sequencer. Control and test RNA
samples are aligned and band differences are easily visualized. The reproducibility of bands is excellent. Bands of
interest must usually be cloned and sequenced for identification, although CuraGen has a computer program
which predicts band identity on the basis of fragment
length and known end sequences. A high quality and relatively complete EST database is required to make best
use of the CuraGen program. CuraGen estimates that
their standard protocol for generating cDNA fragments
produces 12,000 to 14,000 assayed bands per sample, with
an average coverage of three bands per gene.
Transcript profiles using arrays
The second major type of RNA profiling is based on
hybridization of transcripts to arrays of DNA molecules
bound to a solid support. In these systems the supportbound DNA is in excess, so that the amount of probe
hybridized to a particular DNA spot is a measure of the
abundance of that transcript in the mRNA population. In
general, the advantage of arrays is that they give quantitative information on the abundance of hundreds or
thousands (depending on the array design) of specific
98
Genome studies and molecular genetics
In practice, one can immobilize plasmid DNA, PCR products or oligonucleotides to the support, which may be glass,
nylon, nitrocellulose or silicon. The probe is usually cDNA
derived from polyA+ RNA and labeled with radioactive or
fluorescent nucleotides. The methods used and number of
clones analyzed depend on the needs and budget of the
researcher. Large-scale experiments done by outside companies can be extremely expensive. Smaller experiments,
such as spotting clones onto nylon membranes, can be performed in any laboratory. Array technologies have been
refined and combined with methods that enrich complex
probe pools [22,23,24•,25•,26], allowing identification of
rare but differentially expressed messages. We at Pioneer
Hi-Bred have experience using three array technologies:
spotting onto nylon membranes, Affymetrix GeneChips,
and the Molecular Dynamics/Amersham glass slide
Microarray Technology Access Program (MTAP).
collection that were known or hypothesized to be differentially regulated during plant/pathogen interactions. We
also included control cDNAs (e.g. maize actins, histones,
and ubiquitins, as well as human integrin). PCR-amplified
inserts or plasmid DNAs are transferred from 96-well
plates to an 864-dot format with a Biomek1000 robot
(Beckman) onto 8 × 12 cm nylon filters. Blots are
hybridized with 33P-labeled first-strand cDNA made from
polyA+ RNA isolated from test and control tissues.
Hybridizations are carried out in duplicate for each sample.
Data is captured on PhosphorImager screens and analyzed
with ImageQuant software (Molecular Dynamics).
Although labor intensive, this approach yields highly
reproducible results in our hands. Northern blots or other
profiling experiments are used to confirm candidates identified on filter arrays. These arrays rely on known EST
sequences and thus cannot directly identify new genes,
but new clones from our cDNA sequencing program can
be quickly added to the array and assayed under many disease and defence conditions. It should also be noted that
arrays can be an indirect discovery tool because the promoters of arrayed co-regulated genes serve as probes for
unknown regulatory factors.
Nylon filter arrays
Microarrays
Arrays of many cDNAs spotted or grown on nylon filters
have been developed by a number of groups for RNA
expression analyses [27–34] and Piétu et al. provide a very
nice example of the statistical treatment of resulting array
data [30]. The variety of gridding technologies in use illustrates how filter arrays can be modified to fit research
needs. These range from hand-held pinning devices which,
when patterns are offset, can make 1536 spots on a 7 × 12
cm rectangle [35•] to Qbots (Genomix Ltd., Christchurch
UK) capable of delivering nearly 60,000 spots to a 22 × 22
cm square. Robotics has made possible the generation of
HD (high-density) arrays on filters as well as on other supports [36•,37,38]. DNA or aliquots of bacterial colonies are
removed from 96- or 384-well plates and arranged in reproducible fashion, in patterns determined by the user. One
interesting recent report describes the application of old
computer printer parts (an Apple StyleWriterTM II thermal
jet printer) to this end [39]. Human cDNA arrays resulting
from collaborations within the IMAGE consortium are
available, along with detailed instructions for use [40,41].
Clontech markets ATLASTM arrays containing human,
mouse and rat cDNAs involved in, among other pathways,
apoptosis, stress response and cell-cycle regulation [42•].
Both Clontech and GenomeSystems offer custom clone
picking and array construction.
Initial reports utilizing microarrays for differential expression analyses have profiled RNA levels in Arabidopsis
[43,44••], mammals [45–47], yeast [48,49••,50••,51] and
bacteria [52]. Strawberry and petunia genes have been
microarrayed [53•] and there are undoubtedly many more
existing or planned applications of this technology for
plant research. Several recent reviews are available covering large-scale expression assays [36•], microarray theory
and design [54,55] and genomics applications [56,57]. The
microarray systems from Affymetrix and MTAP reflect the
two main approaches currently available for massively parallel assays of RNA expression: oligonucleotides on silicon
and PCR products on glass microscope slides.
genes simultaneously. Limiting the assay to a defined set
of genes reduces the value of arrays as a gene discovery
tool compared to the gel-based methods. They are, however, invaluable at providing a global view of gene
expression changes.
The in-house filter-based arrays developed by the Pioneer
Disease Resistance group provide a highly flexible and less
expensive means (about $50 per array, not including cost of
robotics) to follow expression of a reasonably large set of
interesting genes under many conditions. We made arrays
of cDNAs as part of our effort to characterize the defense
response in maize, and so chose about 850 ESTs from our
Oligomer microarrays on silicon
The Affymetrix GeneChip features a cassette enclosing
the oligomer microarray and a 250 µl chamber for
hybridization, washes and staining. mRNA is converted to
cDNA by reverse transcription from a primer that incorporates the T7 promoter, which allows subsequent in vitro
transcription using T7RNA polymerase to amplify each
cDNA into a cRNA population. This amplification by transcription boosts the sensitivity for rare mRNAs while
maintaining the original relative ratio of each message in
the population, and also allows for the incorporation of
biotinylated CTP and UTP. The cRNA is fragmented,
hybridized to the chip and stained with streptavidinphycoerythrin, which attaches fluorescent labels through high
affinity interaction with the biotin tags. A scanning confocal microscope detects laser-excited fluorescence from
hybridized cRNA. Sensitivity was reported to be sufficient
to detect rare transcripts present at less than 0.1 (on average) copies per cell in yeast [50••].
Microarray techniques to detect differential RNA expression in plants Baldwin, Crane and Rice
99
Table 1
Researchers in the 1998 NSF plant genome research program who are planning to develop expression profiling systems.
Project Principal investigator
(contacts)
Institution
Title
E-mail address
1
Pamela J Green
Michigan State University
Functional analysis of the Arabidopsis
genome via gene disruption and global
gene expression analysis
[email protected]
1
(Shauna Sommerville)
Carnegie Institute of Washington
Microarray contact
Shauna@Andrew2.
Stanford.edu
1
(John Ohlrogge)
Michigan State University
Microarray contact
[email protected]
1
(Mike Cherry)
Stanford University
Bioinformatics contact
cherry@genome.
stanford.edu
2
Virginia Walbot
Stanford University
Maize gene discovery, sequencing
and phenotypic analysis
[email protected]
2
(David Galbraith)
University of Arizona
Microarray contact
[email protected]
3
Lila Vodkin
University of Illinois Urbana-Champaign
Functional genomics program
for soybean
[email protected]
3
(Randy C Shoemaker)
Iowa State University
EST contact
[email protected]
4
Steven Tanksley
Cornell University
Development of tools for tomato functional
genomics: application to analysis of fruit
development, responses to pathogens and
genome synteny with Arabidopsis
[email protected]
5
Douglas R Cook
Texas A and M
Medicago truncatula as the nodal species
for comparative and functional legume genomics
drc1653@acs.
tamu.edu
5
(Katheryn A Van Den Bosch)
Texas A and M
Microarray contact
[email protected]
[email protected]
6
Hans Bohnert
University of Arizona
Genomics of plant stress tolerance
7
Thea A Wilkins
University of California at Davis
Structure and function of the cotton
genome: an integrated analysis of the genetics,
development and evolution of the cotton fiber
tawilkins@
ucdavis.edu
8
Nina V Federoff
Pennsylvania State University
New DNA microarray detection techniques
in the study of stress-induced changes in
plant gene expression
[email protected]
9
Rod A Wing
Clemson University
A BAC library resource of crop genomics
[email protected]
10
Bertrand Lemieux
University of Delaware
Genomic analysis of seed qualilty traits
in corn
[email protected]
Figure 2
Pseudo-color image of a maize GeneChip.
Tissue samples were from the same fungal
infection experiment used in Figure 1. cRNA
derived from control plants was labeled and
hybridized to the chip shown on the left.
A magnified section is shown adjacent to the
corresponding section from a second chip
that was hybridized with cRNA from infected
leaves. A set of 15 perfect match (PM) and
mismatch (MM) probes is indicated for a gene
that was induced twofold during the defense
response.
Fluorescence
PM
MM
Control
Current Opinion in Plant Biology
Defense response
100
Genome studies and molecular genetics
Figure 3
35
30
Genes
25
20
15
10
-5
-4.5
-4
-3.5
-3
-2.5
-2
-1.5
1.5
2
2.5
3
3.5
4
4.5
5
5.5
6
6.5
7
7.5
8
8.5
9
9.5
10
>10
5
Fold change
Current Opinion in Plant Biology
Distribution of differentially expressed maize genes during pathogen
defense. Affymetrix GeneChip analysis identified 117 genes that
consistently showed induced or repressed levels of RNA expression six
hours after various treatments with the fungal pathogen C. carbonum.
The maize GeneChip contains probes for 1500 ESTs or
genes synthesized on a 1.6 cm2 array. Most of these genes
are represented by twenty 20-nucleotide oligomers containing sequences predicted to provide high stringency
hybridization without cross-specificity for other cDNA
sequences from the Pioneer Hi-Bred EST database. Each
set of twenty probes is arrayed adjacent to a set of ‘mismatch’ probes that contain one incorrect nucleotide in the
middle of the oligomer — a hybridization signal from a mismatch probe indicates a gene-family member may be
contributing non-specific background for that probe. The
initial study utilizing this GeneChip was designed to detect
differentially expressed genes in leaf tissue infected with a
fungal pathogen (Figure 2). Chip-to-chip variation was
measured as the number of genes showing a signal difference of 1.5-fold or more between replicates. Comparing 16
replicates from several control and treatment hybridizations, the average chip-to-chip variation was 1.6% (standard
deviation 0.9) or about 24 genes in the array. These genes
varied by an average of 2.2-fold (standard deviation 1.0),
and the identities and distribution of probes contributing to
this variation appeared to be random. Monitoring such variation is important with this technique because comparisons
between mRNA samples require separate chips and
hybridization reactions. The initial data suggest these
arrays, and accompanying analysis software, are performing
very consistently across chips. Deviation among detected
fold-change values for differentially expressed genes has
also been reasonably low, especially when the magnitude of
change is greater than three fold. Accurate resolution of
smaller expression differences is problematic with all the
techniques reviewed, yet many of the genes that show
changes between RNA populations are in this class
(Figure 3, and [44••,46,49••,50••,51]). Consistently detecting and sorting out biologically relevant changes of 1.5 to
3-fold will continue to be a challenge.
Design and synthesis costs are at this time a constraint upon
unlimited use of oligomer chips, but these expenses may be
reduced as commercial microarray producers expand
beyond product development to full-scale production.
Incorporation of new array synthesis techniques may also
reduce chip design and production costs. Improvements in
quality control, hybridization protocols and fluorescence
staining are anticipated. Affymetrix, for example, is developing a chip and scanner capable of assaying 400,000
features [58], or 20,000 genes per chip, will allow most maize
genes to be arrayed in a manageable set. Improved photolithography methods, such as the use of micromirrors
rather than individual masks [59], may even allow
researchers to design and produce their own oligomer arrays.
cDNA microarrays on glass slides
Although there are currently no other plant GeneChip
arrays, a collaboration between Monsanto Co. and
Synteni/Incyte has developed an Arabidopsis glass slide
microarray [60]. Differential profiles for 1443 genes were
used to compare expression in leaf, root and two floral
tissue stages [44••]. Sensitivity was thought to be sufficient
to detect transcripts as rare as one copy per cell, and reproducibility between slides was measured as 2.8% of the
array elements varying by more than two fold. An advantage with this and related systems is the use of two
fluorescent dyes (Cy3 and Cy5) to separately label the
cDNA derived from samples to be compared. The cDNA
pools can then be mixed and hybridized to a single array,
and the ratio of Cy3 to Cy5 signals reflects the difference
in abundance for the targeted transcript. A similar dual-dye
strategy has been used in GeneChip experiments [61].
Another microarray option is the MTAP glass-based technique for in-house array production. The program provides a
robotic spotter that delivers PCR amplified cDNA to a
microscope slide. Fluorescence labeled first-strand probe is
produced by reverse transcription from the mRNA sample to
be assayed, and hybridization is carried out in 30 µl of solution under a coverslip. Hybridization signals are detected
using a scanning confocal microscope with a laser excitation
source. The MTAP robotic spotter deposits 1536 targets, in
duplicate, on each of 24 glass slides in about five hours.
Designs for a do-it-yourself glass slide microarray system are
available via the Internet from P Brown [62], and standard
lab robotics such as the Biomek 2000 [63] can be adapted to
produce similar microarrays. Current concerns include nonlinearity of Cy3 versus Cy5 responses at low fluorescence
intensities, reproducibility between arrays, and variation due
to slight differences in hybridization conditions. Slide attachment chemistries, hybridization solution reagents, and
alternative nucleotide derivatives for improved labeling and
hybridization are all active areas of research.
Future plant microarray resources
The 1998 awards in the NSF Plant Genome Research
Program reflect the rapid expansion of RNA expression
profiling in plant molecular biology [64]. Nine of the 23
Microarray techniques to detect differential RNA expression in plants Baldwin, Crane and Rice
funded abstracts propose development of techniques or
databases for large-scale expression analyses. The
Arabidopsis Functional Genomics Consortium intends to
create service facilities that will provide the plant research
community a knockout mutant screening service and glass
slide microarrays for dual-dye expression profiling, beginning in year two of their grant (Table 1, project 1). Initially
7000–10,000 singleton ESTs from the Michigan State
University collection will be arrayed as PCR fragments,
and an independent review panel will prioritize proposed
experiments that utilize the arrays. Expression profiles will
be made publicly available on a database accessible via the
World Wide Web. A similar ‘virtual center’ will focus on
EST sequencing, mutant generation and glass slide
microarrays for maize (project 2). The University of Illinois
Biotechnology Center plans to compare nylon filter and
glass slide arrays for soybean, using ESTs available from
the Soybean Growers Association, and will provide standard expression profiles in a public database (project 3).
Additional plant profiling is planned for tomato (project 4),
Medicago truncatula, basal, symbiotic and pathogen defense
gene expression (project 5), salt and water stress genes
(project 6), and cotton (project 7). Also, the Microarray
Facility at Pennsylvania State University is developing
Arabidopsis arrays with enhanced sensitivity using colloidal
gold labeling and surface plasmon resonance for detection
(project 8), and the Clemson University Genomics
Institute plans to expand its plant bacterial artificial chromosome (BAC) and EST library arrays and to prepare
microarrays for expression profiling (project 9). A collaboration has been formed to array Arabidopsis open reading
frames and maize embryo ESTs in a glass slide system with
detection of four dyes (project 10), and a microarray of
Arabidopsis defense-related genes is in use [65•].
Conclusions
Of the two main RNA profiling approaches — gel-based
assays and array hybridization — the gel-based techniques
have been used more extensively to isolate many important differentially expressed genes. Differential display
and AFLP of cDNA are inexpensive, rapid and can be performed in any laboratory. They are ‘open-ended’, that is to
say they are not limited to an existing EST database or
library of clones. They are excellent discovery tools to
identify specific genes whose expression levels differ in
two very similar populations of transcripts.
The solid-support arrays are more useful to give a broad
view of gene expression changes between samples,
although they also can be important discovery tools if the
arrays are large enough. Nylon-based filter arrays are
attractive for individual labs or for experiments where a
specific set of genes are studied. They allow flexibility for
quickly adding or removing clones from the array, and
require no special equipment for hybridization. Gridding
can be done by a robot or manually with a pinning device.
101
Large-scale commercial microarrays hold great promise,
but are still in the developmental stage, and a limited number of biologically important results have been published
so far. Recent investigations of cell cycle-regulated expression in yeast are examples of the scope of interesting
questions that can be addressed using arrays with genome
wide coverage [66,67••]. Such comprehensive tools will
undoubtedly become the most efficient way to monitor
gene expression changes in plant tissues. Currently these
arrays are limited to a few thousand clones, but within a
few years, systems providing nearly complete coverage of
the Arabidopsis and maize genomes should be available.
GeneChip and microscope slide methods are likely to be
used in plant profiling experiments that complement each
other. The Affymetrix package of multiple, independent
and specific probes and comprehensive analysis software is
well suited for initial surveys of gene expression. In-house
microarrays provide a highly flexible and less expensive
means to follow expression of a large set of interesting
genes under many conditions. The immediate capacity to
increase glass-slide array densities appears limited, and the
investment of time, labor and organization can be significant for a collection of tens of thousands of purified PCR
products. Whole-genome coverage may not always be necessary, however, and the ability to quickly add newly
identified genes (or probes for newly created transgenic
constructs) to a subset array will remain attractive. The
degree of detail with which biologists will be able to monitor changes in gene expression using any of these
approaches will allow huge leaps in our understanding of
plant gene regulation.
Note added in proof
The Chipping Forecast is a supplement to Nature Genetics
[68] that features fourteen perspectives and reviews on
microarray analysis. It is available at http://
genetics.nature.com/chips_interstitial.html or by calling 1800-524-0384 (US only) or + 1-615-377-3322 (outside the
US). Also, two other recent articles featured expression
profiling and differential display [69,70]. Additional
Internet resources and a discussion of microarray applications are provided by Kehoe, Villand and Somerville [71].
Acknowledgements
We thank our collaborators at CuraGen, Affymetrix, and Molecular
Dynamics/Amersham for technical advice and reviews. We appreciate the
support provided by our colleagues in genomics research at Pioneer Hi-Bred
and DuPont, and thank participants in the Plant Genome Research Program
for sharing project details.
References and recommended reading
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http://atlas.clontech.com
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A first look at massively parallel measurements of gene expression in plants;
data is available at the site listed in [60]. A number of tissue-specific or tissue-enhanced Arabidopsis genes are identified, and Figure 4 illustrates the
importance of carefully choosing samples to be compared. We also find that
comparisons of very different tissues such as leaf versus root produce profiles with an overwhelming number of differentially expressed genes, especially at lower fold-change levels. Comparison of two floral stages however,
or the same tissue with control versus test treatments, considerably reduces
the profile’s complexity.
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SY, Brown PO, Davis RW: Yeast microarrays for genome wide
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278:680-686.
Whole-genome expression patterns in yeast using cDNA arrayed on microscope slides. Provides an interesting synthesis of the resulting data with
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The Affymetrix set of GeneChips for whole-genome coverage in yeast.
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cell to hundreds of copies per cell, with low chip-to-chip variation.
51. Roth FP, Hughes JD, Estep PW, Church GM: Finding DNA regulatory
motifs within unaligned noncoding sequences clustered by wholegenome mRNA quantitation. Nat Biotechnol 1998, 16:939-945.
52. de Saizieu A, Certa U, Warrington J, Gray C, Keck W, Mous J:
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oligonucleotide arrays. Nat Biotechnol 1998, 16:45-48.
53. Lemieux B, Aharoni A, Schena M: Overview of DNA chip technology.
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Mol Breeding 1998, 4:277-289.
A broad examination of microarray uses in plant molecular biology, including
expression profiling, polymorphism mapping, genotyping and resequencing.
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16:40-44.
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Fiscal Year 1998 Awards Plant Genome Research Program
Collaborative Research and Infrastructure Projects on World Wide
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65. Arabidopsis functional genomics on World Wide Web URL:
•
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Philippe Reymond and Edward E Farmer (Université de Lausanne) have
printed a microarray containing approximately 150 Arabidopsis defenserelated genes to study the activity of different members of the jasmonate
family on global gene expression. Information about sharing this resource will
be available in early 1999.
66. Cho RJ, Campbell MJ, Winzeler EA, Steinmetz L, Conway A,
Wodicka L, Wolfsberg TG, Gabrielian AE, Landsman D, Lockhart DJ
et al.: A genome-wide transcriptional analysis of the mitotic cell
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Brown PO, Botstein D, Futcher B: Comprehensive identification of
cell cycle-regulated genes of the yeast Saccharomyces cerevisiae
by microarray hybridization. Mol Biol Cell 1998, 9:3273-3297.
Data from Cho et al. [66], three independent culture synchronization experiments and two cyclin induction experiments have been incorporated into a
massive set of results that identifies 800 cell cycle-regulated genes in yeast.
The published article and supporting databases can be found at
http://genome-www.stanford.edu/cellcycle/, and the site includes a search
feature to display expression patterns of requested genes. This work illustrates a number of expression profiling issues that will soon be faced by plant
researchers, including: the power of whole-genome coverage to reveal unexpected expression regulation; the need for statistical algorithms to help identify patterns in a gene's expression data and to cluster coordinately regulated
genes; the need for algorithms that can search for variations of a promoter
sequence motif and correlate their presence to the patterns revealed; the
advantages of compiling raw data into standardized or convertible sets that
will allow others to test for replication of results, addition of new profiles, and
meta-analyses across independent RNA, protein and metabolite profiles; and
finally the requirement for electronic accessibility, either from the researcher
or publisher, to data sets that are too large to print yet potentially very useful
to the reader when searched or re-analyzed from his or her perspective.
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A comparison of gel-based, nylon filter and microarray
techniques to detect differential RNA expression in plants
Don Baldwin*, Virginia Crane† and Douglas Rice‡
An initial application of plant genomics has been to monitor
gene expression on a scale much larger than previously
possible. Although multiplexed assays of RNA abundance have
developed more quickly than those for protein and metabolite
levels, some combination of these approaches will soon be
providing our best views yet into plant molecular biology. Three
techniques that have made contributions to the RNA transcript
portion of this combination are reviewed. Currently, each can
produce a profile of expression levels for a large but
incomplete set of plant genes, at reproducibly high levels of
accuracy and over a range of labor and financial expenses.
Addresses
Disease Resistance Group, Trait and Technology Development
Pioneer Hi-Bred International Inc., 7300 NW 62nd Ave., Johnston,
IA 50131-1004, USA
*e-mail: [email protected]
† e-mail: [email protected]
‡ e-mail: [email protected]
Current Opinion in Plant Biology 1999, 2:96–103
http://biomednet.com/elecref/1369526600200096
© Elsevier Science Ltd ISSN 1369-5266
Abbreviations
AFLP
amplified fragment length polymorphism
AP-PCR arbitrarily primed PCR
cDNA
complementary deoxyribonucleic acid
cRNA
complementary ribonucleic acid
EST
expressed sequence tag
HD
high-density
MTAP
Microarray Technology Access Program
PCR
polymerase chain reaction
Introduction
The ability to generate profiles of the abundance of RNA
transcripts has numerous applications in plant biology
including identification of tissue-specific or organ-specific
transcripts, developmental stage-specific transcripts, transcripts induced by environmental stresses, and transcripts
induced or repressed upon pathogen infection. Generally,
biologists are interested in those genes expressed differentially in two or more populations of RNA transcripts. In the
past, differentially expressed genes were usually identified
by subtractive hybridizations, differential plaque hybridizations, or protein gel differences, followed by
micro-sequencing or using antibodies to clone cDNAs. As
large sequence databases become available for plants, the
number of genes we would like to monitor becomes too
large for traditional analyses such as Northern blots. Ideally,
an expression assay covering all genes in the plant cell will
reveal how patterns change during differentiation, growth,
response to stress, etc. In the past few years, several techniques have become available to monitor the expression of
large numbers of genes. Most of these techniques are based
on gel fractionation of cDNAs or hybridization to DNAs
immobilized on a solid support. Another approach, not discussed further in this review, is sequencing-intensive and
includes the serial analysis of gene expression [1] and ‘electronic Northerns’ in which the representation of sequences
in a database is used to measure the abundance of a particular transcript. The following comparison of methods for
detecting differential RNA expression includes gel-based
AFLP assays of cDNA, nylon filter arrays and two types of
microarrays. Examples using each of these three methods
in functional genomics research are referenced, and the
next step up in scale for the plant portion of this field is
illustrated by a brief look at some of the projects from the
NSF Plant Genome Research Program.
Gel-based transcript profiles
The first RNA profiling techniques developed were ‘differential display’ by Liang and Pardee [2] and arbitrarily
primed (AP) PCR by Welsh et al. [3], both of which use
arbitrary primers to amplify portions of cDNAs which are
then fractionated on a polyacrylamide sequencing gel. The
main difference between the two methods is that differential display uses an anchored oligo-dT primer plus one
arbitrary primer, whereas AP-PCR is not anchored to the
3′-end. Differential display has been used widely because it
is fast, inexpensive, sensitive and simple to perform. The
two techniques that it uses, PCR and denaturing polyacrylamide gel electrophoresis, are routine in molecular biology
labs. If a sufficient number of primers are tested, it should
be possible to identify most transcripts in an mRNA sample. A protocol is given in [4]. Differential display has been
used to isolate a large number of plant genes differentially
expressed during development [5,6], hormone response
[7,8], environmental stresses [9,10], defense responses
[11,12,13•] and nodule formation [14,15].
In spite of its popularity, differential display has several drawbacks. First, the number of false positives generated by this
technique can be unacceptable. The annealing of the arbitrary primers to the cDNA is done at relatively low
temperatures (e.g. 40°C), reducing some priming specificity
and producing autoradiograph band differences that do not
reflect real differences in gene expression. Recognized by
many as a major problem with conventional differential display, nonspecific priming can be reduced through
modifications to both the arbitrary and oligo-dT primers [16].
This problem can also be minimized by performing a number of replicate experiments, preferably using different RNA
preparations and PCR reactions, and only isolating bands
that are consistently, differentially represented. A second difficulty is that the fragments generated include only several
hundred bases from the 3′-end. Sequence from this region is
often insufficient to identify a gene, especially when using a
Microarray techniques to detect differential RNA expression in plants Baldwin, Crane and Rice
Some of the above drawbacks of differential display have
been overcome with amplified restriction fragment length
polymorphism (AFLP) of cDNA, as shown by Bachem et al.
[21] in the first application of this method for plant biology.
In this technique, the cDNA population is cut with two
restriction enzymes and adapters are ligated onto the resulting cohesive ends. Selective PCR primers that extend past
the adapters into the cDNA are used in the subsequent
amplification to reduce the number of bands present on the
denaturing gel. Again, the procedure is simple and rapidly
performed, and the number of mRNA species visualized is
limited only by how many pairs of restriction enzymes are
tried. The main advantage is stringent primer hybridization
to the adapters, thus reducing the variability of traditional
differential display. Also, because amplification can originate from any region of the cDNA there is a higher chance
of detecting homology to related genes in EST databases.
The problem of heterogeneity in the reamplified bands
must still be addressed when performing AFLP of cDNA.
Both gel-based methods of transcript profiling are very
useful and are easily and inexpensively performed. They
do not rely on EST databases or existing cDNA libraries,
allow detection of rare transcripts, and require relatively
small amounts of mRNA. The main disadvantages
include heterogeneity of final products, the need to clone
and sequence the product for identification, and the need
to isolate a full-length cDNA after obtaining the PCR
product. At Pioneer Hi-Bred, we are fortunate to have
access to the RNA profiling performed by the CuraGen
Figure 1
Defense
response
Band intensity
database from an unrelated organism. As a result, one must
often isolate a longer cDNA clone to identify the differentially expressed gene. Recent modifications to address this
problem include the development of long-distance differential display PCR, using hot start and rTth DNA polymerase
[17]. Finally, a third problem arises during cloning of the
identified fragment. Although the band can be excised from
the sequencing gel with surprising accuracy, there are usually several species of cDNA present in a band, leading to a
mixed population of candidates after reamplification and
cloning. We generally sequence six clones per band; we usually see a predominant species represented but sometimes
multiple Northern blots are required to identify the differentially expressed clone. A recent report comparing
expression in normal and mammoplastic epithelial tissues
describes dramatic reduction in the number of false positives
using gene-specific primers to reamplify differential display
products (bands were sequenced directly from the gel). Of
104 differentially displayed bands analyzed, 86% provided
readable sequencing runs [18]. This allowed identification of
62 differentially expressed genes, 32 of which matched
human ESTs of unknown function. This type of analysis
shows the value of RNA profiling for placing uncharacterized
ESTs into functional context. More often, high-throughput
screens such as dot-blot arrays are now being used in conjunction with more sensitive probes (e.g. riboprobes) to
increase the success rate of differential display [19,20].
97
Control
Band length (bp)
Current Opinion in Plant Biology
Fluorescence electropherograms from a CuraGen analysis.
Disease-resistant maize leaves were infected with a fungal pathogen,
Cochliobolus carbonum, for six hours. Replicate profiles of
RNA-derived fragments expressed during the resulting defense
response are compared to gel traces from control plants. The 47
base-pair band was induced 3.1-fold.
Corporation. PCR-amplified cDNA fragments are labeled
with fluorescent probes, run on a denaturing gel, and
detected by a fluorescence gel scanner. The resulting
electropherograms (Figure 1) look similar to a trace from
an automated DNA sequencer. Control and test RNA
samples are aligned and band differences are easily visualized. The reproducibility of bands is excellent. Bands of
interest must usually be cloned and sequenced for identification, although CuraGen has a computer program
which predicts band identity on the basis of fragment
length and known end sequences. A high quality and relatively complete EST database is required to make best
use of the CuraGen program. CuraGen estimates that
their standard protocol for generating cDNA fragments
produces 12,000 to 14,000 assayed bands per sample, with
an average coverage of three bands per gene.
Transcript profiles using arrays
The second major type of RNA profiling is based on
hybridization of transcripts to arrays of DNA molecules
bound to a solid support. In these systems the supportbound DNA is in excess, so that the amount of probe
hybridized to a particular DNA spot is a measure of the
abundance of that transcript in the mRNA population. In
general, the advantage of arrays is that they give quantitative information on the abundance of hundreds or
thousands (depending on the array design) of specific
98
Genome studies and molecular genetics
In practice, one can immobilize plasmid DNA, PCR products or oligonucleotides to the support, which may be glass,
nylon, nitrocellulose or silicon. The probe is usually cDNA
derived from polyA+ RNA and labeled with radioactive or
fluorescent nucleotides. The methods used and number of
clones analyzed depend on the needs and budget of the
researcher. Large-scale experiments done by outside companies can be extremely expensive. Smaller experiments,
such as spotting clones onto nylon membranes, can be performed in any laboratory. Array technologies have been
refined and combined with methods that enrich complex
probe pools [22,23,24•,25•,26], allowing identification of
rare but differentially expressed messages. We at Pioneer
Hi-Bred have experience using three array technologies:
spotting onto nylon membranes, Affymetrix GeneChips,
and the Molecular Dynamics/Amersham glass slide
Microarray Technology Access Program (MTAP).
collection that were known or hypothesized to be differentially regulated during plant/pathogen interactions. We
also included control cDNAs (e.g. maize actins, histones,
and ubiquitins, as well as human integrin). PCR-amplified
inserts or plasmid DNAs are transferred from 96-well
plates to an 864-dot format with a Biomek1000 robot
(Beckman) onto 8 × 12 cm nylon filters. Blots are
hybridized with 33P-labeled first-strand cDNA made from
polyA+ RNA isolated from test and control tissues.
Hybridizations are carried out in duplicate for each sample.
Data is captured on PhosphorImager screens and analyzed
with ImageQuant software (Molecular Dynamics).
Although labor intensive, this approach yields highly
reproducible results in our hands. Northern blots or other
profiling experiments are used to confirm candidates identified on filter arrays. These arrays rely on known EST
sequences and thus cannot directly identify new genes,
but new clones from our cDNA sequencing program can
be quickly added to the array and assayed under many disease and defence conditions. It should also be noted that
arrays can be an indirect discovery tool because the promoters of arrayed co-regulated genes serve as probes for
unknown regulatory factors.
Nylon filter arrays
Microarrays
Arrays of many cDNAs spotted or grown on nylon filters
have been developed by a number of groups for RNA
expression analyses [27–34] and Piétu et al. provide a very
nice example of the statistical treatment of resulting array
data [30]. The variety of gridding technologies in use illustrates how filter arrays can be modified to fit research
needs. These range from hand-held pinning devices which,
when patterns are offset, can make 1536 spots on a 7 × 12
cm rectangle [35•] to Qbots (Genomix Ltd., Christchurch
UK) capable of delivering nearly 60,000 spots to a 22 × 22
cm square. Robotics has made possible the generation of
HD (high-density) arrays on filters as well as on other supports [36•,37,38]. DNA or aliquots of bacterial colonies are
removed from 96- or 384-well plates and arranged in reproducible fashion, in patterns determined by the user. One
interesting recent report describes the application of old
computer printer parts (an Apple StyleWriterTM II thermal
jet printer) to this end [39]. Human cDNA arrays resulting
from collaborations within the IMAGE consortium are
available, along with detailed instructions for use [40,41].
Clontech markets ATLASTM arrays containing human,
mouse and rat cDNAs involved in, among other pathways,
apoptosis, stress response and cell-cycle regulation [42•].
Both Clontech and GenomeSystems offer custom clone
picking and array construction.
Initial reports utilizing microarrays for differential expression analyses have profiled RNA levels in Arabidopsis
[43,44••], mammals [45–47], yeast [48,49••,50••,51] and
bacteria [52]. Strawberry and petunia genes have been
microarrayed [53•] and there are undoubtedly many more
existing or planned applications of this technology for
plant research. Several recent reviews are available covering large-scale expression assays [36•], microarray theory
and design [54,55] and genomics applications [56,57]. The
microarray systems from Affymetrix and MTAP reflect the
two main approaches currently available for massively parallel assays of RNA expression: oligonucleotides on silicon
and PCR products on glass microscope slides.
genes simultaneously. Limiting the assay to a defined set
of genes reduces the value of arrays as a gene discovery
tool compared to the gel-based methods. They are, however, invaluable at providing a global view of gene
expression changes.
The in-house filter-based arrays developed by the Pioneer
Disease Resistance group provide a highly flexible and less
expensive means (about $50 per array, not including cost of
robotics) to follow expression of a reasonably large set of
interesting genes under many conditions. We made arrays
of cDNAs as part of our effort to characterize the defense
response in maize, and so chose about 850 ESTs from our
Oligomer microarrays on silicon
The Affymetrix GeneChip features a cassette enclosing
the oligomer microarray and a 250 µl chamber for
hybridization, washes and staining. mRNA is converted to
cDNA by reverse transcription from a primer that incorporates the T7 promoter, which allows subsequent in vitro
transcription using T7RNA polymerase to amplify each
cDNA into a cRNA population. This amplification by transcription boosts the sensitivity for rare mRNAs while
maintaining the original relative ratio of each message in
the population, and also allows for the incorporation of
biotinylated CTP and UTP. The cRNA is fragmented,
hybridized to the chip and stained with streptavidinphycoerythrin, which attaches fluorescent labels through high
affinity interaction with the biotin tags. A scanning confocal microscope detects laser-excited fluorescence from
hybridized cRNA. Sensitivity was reported to be sufficient
to detect rare transcripts present at less than 0.1 (on average) copies per cell in yeast [50••].
Microarray techniques to detect differential RNA expression in plants Baldwin, Crane and Rice
99
Table 1
Researchers in the 1998 NSF plant genome research program who are planning to develop expression profiling systems.
Project Principal investigator
(contacts)
Institution
Title
E-mail address
1
Pamela J Green
Michigan State University
Functional analysis of the Arabidopsis
genome via gene disruption and global
gene expression analysis
[email protected]
1
(Shauna Sommerville)
Carnegie Institute of Washington
Microarray contact
Shauna@Andrew2.
Stanford.edu
1
(John Ohlrogge)
Michigan State University
Microarray contact
[email protected]
1
(Mike Cherry)
Stanford University
Bioinformatics contact
cherry@genome.
stanford.edu
2
Virginia Walbot
Stanford University
Maize gene discovery, sequencing
and phenotypic analysis
[email protected]
2
(David Galbraith)
University of Arizona
Microarray contact
[email protected]
3
Lila Vodkin
University of Illinois Urbana-Champaign
Functional genomics program
for soybean
[email protected]
3
(Randy C Shoemaker)
Iowa State University
EST contact
[email protected]
4
Steven Tanksley
Cornell University
Development of tools for tomato functional
genomics: application to analysis of fruit
development, responses to pathogens and
genome synteny with Arabidopsis
[email protected]
5
Douglas R Cook
Texas A and M
Medicago truncatula as the nodal species
for comparative and functional legume genomics
drc1653@acs.
tamu.edu
5
(Katheryn A Van Den Bosch)
Texas A and M
Microarray contact
[email protected]
[email protected]
6
Hans Bohnert
University of Arizona
Genomics of plant stress tolerance
7
Thea A Wilkins
University of California at Davis
Structure and function of the cotton
genome: an integrated analysis of the genetics,
development and evolution of the cotton fiber
tawilkins@
ucdavis.edu
8
Nina V Federoff
Pennsylvania State University
New DNA microarray detection techniques
in the study of stress-induced changes in
plant gene expression
[email protected]
9
Rod A Wing
Clemson University
A BAC library resource of crop genomics
[email protected]
10
Bertrand Lemieux
University of Delaware
Genomic analysis of seed qualilty traits
in corn
[email protected]
Figure 2
Pseudo-color image of a maize GeneChip.
Tissue samples were from the same fungal
infection experiment used in Figure 1. cRNA
derived from control plants was labeled and
hybridized to the chip shown on the left.
A magnified section is shown adjacent to the
corresponding section from a second chip
that was hybridized with cRNA from infected
leaves. A set of 15 perfect match (PM) and
mismatch (MM) probes is indicated for a gene
that was induced twofold during the defense
response.
Fluorescence
PM
MM
Control
Current Opinion in Plant Biology
Defense response
100
Genome studies and molecular genetics
Figure 3
35
30
Genes
25
20
15
10
-5
-4.5
-4
-3.5
-3
-2.5
-2
-1.5
1.5
2
2.5
3
3.5
4
4.5
5
5.5
6
6.5
7
7.5
8
8.5
9
9.5
10
>10
5
Fold change
Current Opinion in Plant Biology
Distribution of differentially expressed maize genes during pathogen
defense. Affymetrix GeneChip analysis identified 117 genes that
consistently showed induced or repressed levels of RNA expression six
hours after various treatments with the fungal pathogen C. carbonum.
The maize GeneChip contains probes for 1500 ESTs or
genes synthesized on a 1.6 cm2 array. Most of these genes
are represented by twenty 20-nucleotide oligomers containing sequences predicted to provide high stringency
hybridization without cross-specificity for other cDNA
sequences from the Pioneer Hi-Bred EST database. Each
set of twenty probes is arrayed adjacent to a set of ‘mismatch’ probes that contain one incorrect nucleotide in the
middle of the oligomer — a hybridization signal from a mismatch probe indicates a gene-family member may be
contributing non-specific background for that probe. The
initial study utilizing this GeneChip was designed to detect
differentially expressed genes in leaf tissue infected with a
fungal pathogen (Figure 2). Chip-to-chip variation was
measured as the number of genes showing a signal difference of 1.5-fold or more between replicates. Comparing 16
replicates from several control and treatment hybridizations, the average chip-to-chip variation was 1.6% (standard
deviation 0.9) or about 24 genes in the array. These genes
varied by an average of 2.2-fold (standard deviation 1.0),
and the identities and distribution of probes contributing to
this variation appeared to be random. Monitoring such variation is important with this technique because comparisons
between mRNA samples require separate chips and
hybridization reactions. The initial data suggest these
arrays, and accompanying analysis software, are performing
very consistently across chips. Deviation among detected
fold-change values for differentially expressed genes has
also been reasonably low, especially when the magnitude of
change is greater than three fold. Accurate resolution of
smaller expression differences is problematic with all the
techniques reviewed, yet many of the genes that show
changes between RNA populations are in this class
(Figure 3, and [44••,46,49••,50••,51]). Consistently detecting and sorting out biologically relevant changes of 1.5 to
3-fold will continue to be a challenge.
Design and synthesis costs are at this time a constraint upon
unlimited use of oligomer chips, but these expenses may be
reduced as commercial microarray producers expand
beyond product development to full-scale production.
Incorporation of new array synthesis techniques may also
reduce chip design and production costs. Improvements in
quality control, hybridization protocols and fluorescence
staining are anticipated. Affymetrix, for example, is developing a chip and scanner capable of assaying 400,000
features [58], or 20,000 genes per chip, will allow most maize
genes to be arrayed in a manageable set. Improved photolithography methods, such as the use of micromirrors
rather than individual masks [59], may even allow
researchers to design and produce their own oligomer arrays.
cDNA microarrays on glass slides
Although there are currently no other plant GeneChip
arrays, a collaboration between Monsanto Co. and
Synteni/Incyte has developed an Arabidopsis glass slide
microarray [60]. Differential profiles for 1443 genes were
used to compare expression in leaf, root and two floral
tissue stages [44••]. Sensitivity was thought to be sufficient
to detect transcripts as rare as one copy per cell, and reproducibility between slides was measured as 2.8% of the
array elements varying by more than two fold. An advantage with this and related systems is the use of two
fluorescent dyes (Cy3 and Cy5) to separately label the
cDNA derived from samples to be compared. The cDNA
pools can then be mixed and hybridized to a single array,
and the ratio of Cy3 to Cy5 signals reflects the difference
in abundance for the targeted transcript. A similar dual-dye
strategy has been used in GeneChip experiments [61].
Another microarray option is the MTAP glass-based technique for in-house array production. The program provides a
robotic spotter that delivers PCR amplified cDNA to a
microscope slide. Fluorescence labeled first-strand probe is
produced by reverse transcription from the mRNA sample to
be assayed, and hybridization is carried out in 30 µl of solution under a coverslip. Hybridization signals are detected
using a scanning confocal microscope with a laser excitation
source. The MTAP robotic spotter deposits 1536 targets, in
duplicate, on each of 24 glass slides in about five hours.
Designs for a do-it-yourself glass slide microarray system are
available via the Internet from P Brown [62], and standard
lab robotics such as the Biomek 2000 [63] can be adapted to
produce similar microarrays. Current concerns include nonlinearity of Cy3 versus Cy5 responses at low fluorescence
intensities, reproducibility between arrays, and variation due
to slight differences in hybridization conditions. Slide attachment chemistries, hybridization solution reagents, and
alternative nucleotide derivatives for improved labeling and
hybridization are all active areas of research.
Future plant microarray resources
The 1998 awards in the NSF Plant Genome Research
Program reflect the rapid expansion of RNA expression
profiling in plant molecular biology [64]. Nine of the 23
Microarray techniques to detect differential RNA expression in plants Baldwin, Crane and Rice
funded abstracts propose development of techniques or
databases for large-scale expression analyses. The
Arabidopsis Functional Genomics Consortium intends to
create service facilities that will provide the plant research
community a knockout mutant screening service and glass
slide microarrays for dual-dye expression profiling, beginning in year two of their grant (Table 1, project 1). Initially
7000–10,000 singleton ESTs from the Michigan State
University collection will be arrayed as PCR fragments,
and an independent review panel will prioritize proposed
experiments that utilize the arrays. Expression profiles will
be made publicly available on a database accessible via the
World Wide Web. A similar ‘virtual center’ will focus on
EST sequencing, mutant generation and glass slide
microarrays for maize (project 2). The University of Illinois
Biotechnology Center plans to compare nylon filter and
glass slide arrays for soybean, using ESTs available from
the Soybean Growers Association, and will provide standard expression profiles in a public database (project 3).
Additional plant profiling is planned for tomato (project 4),
Medicago truncatula, basal, symbiotic and pathogen defense
gene expression (project 5), salt and water stress genes
(project 6), and cotton (project 7). Also, the Microarray
Facility at Pennsylvania State University is developing
Arabidopsis arrays with enhanced sensitivity using colloidal
gold labeling and surface plasmon resonance for detection
(project 8), and the Clemson University Genomics
Institute plans to expand its plant bacterial artificial chromosome (BAC) and EST library arrays and to prepare
microarrays for expression profiling (project 9). A collaboration has been formed to array Arabidopsis open reading
frames and maize embryo ESTs in a glass slide system with
detection of four dyes (project 10), and a microarray of
Arabidopsis defense-related genes is in use [65•].
Conclusions
Of the two main RNA profiling approaches — gel-based
assays and array hybridization — the gel-based techniques
have been used more extensively to isolate many important differentially expressed genes. Differential display
and AFLP of cDNA are inexpensive, rapid and can be performed in any laboratory. They are ‘open-ended’, that is to
say they are not limited to an existing EST database or
library of clones. They are excellent discovery tools to
identify specific genes whose expression levels differ in
two very similar populations of transcripts.
The solid-support arrays are more useful to give a broad
view of gene expression changes between samples,
although they also can be important discovery tools if the
arrays are large enough. Nylon-based filter arrays are
attractive for individual labs or for experiments where a
specific set of genes are studied. They allow flexibility for
quickly adding or removing clones from the array, and
require no special equipment for hybridization. Gridding
can be done by a robot or manually with a pinning device.
101
Large-scale commercial microarrays hold great promise,
but are still in the developmental stage, and a limited number of biologically important results have been published
so far. Recent investigations of cell cycle-regulated expression in yeast are examples of the scope of interesting
questions that can be addressed using arrays with genome
wide coverage [66,67••]. Such comprehensive tools will
undoubtedly become the most efficient way to monitor
gene expression changes in plant tissues. Currently these
arrays are limited to a few thousand clones, but within a
few years, systems providing nearly complete coverage of
the Arabidopsis and maize genomes should be available.
GeneChip and microscope slide methods are likely to be
used in plant profiling experiments that complement each
other. The Affymetrix package of multiple, independent
and specific probes and comprehensive analysis software is
well suited for initial surveys of gene expression. In-house
microarrays provide a highly flexible and less expensive
means to follow expression of a large set of interesting
genes under many conditions. The immediate capacity to
increase glass-slide array densities appears limited, and the
investment of time, labor and organization can be significant for a collection of tens of thousands of purified PCR
products. Whole-genome coverage may not always be necessary, however, and the ability to quickly add newly
identified genes (or probes for newly created transgenic
constructs) to a subset array will remain attractive. The
degree of detail with which biologists will be able to monitor changes in gene expression using any of these
approaches will allow huge leaps in our understanding of
plant gene regulation.
Note added in proof
The Chipping Forecast is a supplement to Nature Genetics
[68] that features fourteen perspectives and reviews on
microarray analysis. It is available at http://
genetics.nature.com/chips_interstitial.html or by calling 1800-524-0384 (US only) or + 1-615-377-3322 (outside the
US). Also, two other recent articles featured expression
profiling and differential display [69,70]. Additional
Internet resources and a discussion of microarray applications are provided by Kehoe, Villand and Somerville [71].
Acknowledgements
We thank our collaborators at CuraGen, Affymetrix, and Molecular
Dynamics/Amersham for technical advice and reviews. We appreciate the
support provided by our colleagues in genomics research at Pioneer Hi-Bred
and DuPont, and thank participants in the Plant Genome Research Program
for sharing project details.
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Data from Cho et al. [66], three independent culture synchronization experiments and two cyclin induction experiments have been incorporated into a
massive set of results that identifies 800 cell cycle-regulated genes in yeast.
The published article and supporting databases can be found at
http://genome-www.stanford.edu/cellcycle/, and the site includes a search
feature to display expression patterns of requested genes. This work illustrates a number of expression profiling issues that will soon be faced by plant
researchers, including: the power of whole-genome coverage to reveal unexpected expression regulation; the need for statistical algorithms to help identify patterns in a gene's expression data and to cluster coordinately regulated
genes; the need for algorithms that can search for variations of a promoter
sequence motif and correlate their presence to the patterns revealed; the
advantages of compiling raw data into standardized or convertible sets that
will allow others to test for replication of results, addition of new profiles, and
meta-analyses across independent RNA, protein and metabolite profiles; and
finally the requirement for electronic accessibility, either from the researcher
or publisher, to data sets that are too large to print yet potentially very useful
to the reader when searched or re-analyzed from his or her perspective.
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70. Seehaus K, Tenhaken R: Cloning of genes by mRNA differential
display induced durring the hypersensitive reaction of soybean
after inoculation with Pseudomonas syringae pv. glycinea. Plant
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