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Gene Chips and Functional Genomics
A new technology will allow environmental health scientists to track
the expression of thousands of genes in a single, fast and easy test
Hisham Hamadeh and Cynthia A. Afshari
J
ust as physics and the space program
dominated the century that is now
ending, biotechnology will dominate
the coming one. As if to underscore this
point, the Human Genome Project and
Celera Genomics jointly announced
earlier this year that they had succeeded in sequencing most of the human
genome. This and other biotechnological advances grab our attention because
they offer at least the promise of improving our lives and health through
the development of better drugs, more
efficient diagnostics, healthier foods
and a cleaner environment.
In this new era, novel technologies
are supplementing traditional biological methods. Computing tools coupled
with sophisticated engineering devices
now facilitate discovery in specialized
areas such as genetics. The rapid sequencing of the entire genome of people, as well as that of other organisms,
provides a wealth of information about
who we are genetically. However,
whereas our complete genetic code
will soon be known, we will not unHisham Hamadeh is a postdoctoral fellow at the
National Institute of Environmental Health
Sciences Microarray Center (NMC). He received
his Ph.D. in toxicology from the University of
California, Irvine. Cynthia Afshari is a staff
scientist and a director of the Microarray Center at
the National Institute of Environmental Health
Sciences. She received her Ph.D. in toxicology
from the University of North Carolina at Chapel
Hill. Hamadeh and Afshari are investigating how
to use new genomic technologies such as cDNA
microarrays to discern new information about how
nonmutagenic carcinogens convert normal cells to
cancer cells. Address: Laboratory of Molecular
Carcinogenesis, P.O. Box 12233, National
Institute of Environmental Health Sciences,
Research Triangle Park, NC 27709.
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American Scientist, Volume 88
derstand the meaning—the translation—of the code for quite some time.
Among the emerging new technologies are those that take us to that next
step in discerning gene function.
One such advance merges inventions
from the semiconductor and computer
industry with laser engineering and
with high-level mathematical computations. This technological amalgam underlies the DNA microarray or, as it is
better known, gene-chip technology. Microarrays will allow scientists and physicians to assess the genetic status of an
entire organ, or maybe someday, an entire organism, even if they do not know
the exact function of every gene. In our
laboratory, we are especially interested
in understanding how environmental
toxicants may affect gene expression,
and we are applying gene-chip technology toward this end.
Gene Expression
The most basic living unit of an organism is the cell. Organs comprise a collection of multiple cell types that work
in concert to provide structure and
function to the organ system. Within
the center of each cell lies the nucleus.
And within the nucleus can be found
the genetic material—DNA—that contains the code for producing almost all
of the cellular machinery. DNA, or deoxyribonucleic acid, serves as a template for the enzymes and proteins that
give each cell type its unique functional and morphological characteristics.
Each DNA molecule is a string of
smaller subunits called nucleotides,
and encrypted in the sequence of
DNA’s nucleotides is the order in
which different amino acids should be
strung together to make proteins. Pro-
teins are often referred to as “the workhorses of the cell,” as they provide the
cell with much of its structure and carry out almost all of its functions.
Within each cell of each individual
the DNA code is identical. Yet the individual contains any number of specialized cells, such as those that make up
muscle, skin, nerve and the immune
system. This fact forces us to ask how
specialized cell types become differentiated. How, for example, does an immune cell “know” to produce antibodies in response to bacteria? Why does a
neuron manufacture the structures and
chemicals to conduct nerve impulses
but not to produce antibodies?
The answer is that only a subset of
the DNA code is “expressed” in each
cell type. The expressed genes of the
immune cell, for example, include
those encoding the manufacture of antibodies, whereas the antibody genes
remain unexpressed in neurons. This
differential expression of the DNA
code is what makes each cell unique
and provides the basis for cellular
function and processes.
The first phase of the genomic era
has focused on elucidating the exact sequence of the nucleotides in the DNA
code. With that part of the work nearly
completed, investigators now want to
know how the DNA code translates
into gene function. They want to learn
which genes are responsible for important healthy functions and which,
when they become damaged, contribute to disease. They also want to
understand how and when signals external to the cell stimulate gene expression within it. Investigators would like
to understand, for example, how the
immune cell translates the presence of
© 2000 Sigma Xi, The Scientific Research Society. Reproduction
with permission only. Contact [email protected].
Wesley Docxe (Photo Researchers, Inc.)
Figure 1. Kuwait City in 1991 was shrouded in a haze of pollution generated by the oil fires set during the Gulf War. At the time, physicians and
scientists worried about the future health effects of toxicants in the intense air pollution. In the future, such determinations may be made with
the use of an important new technology—the DNA microarray, also known as the gene chip. Using gene chips, toxicologists may be able to pinpoint the exact genetic effects of noxious environmental chemicals—even if they do not know the precise compounds in the environment.
bacteria into gene expression of an antibody gene. Accordingly, the new field
of “functional genomics” focuses on
the expression of the DNA.
DNA expression proceeds in several
steps. First, specific DNA segments
corresponding to individual genes are
copied from DNA into RNA molecules, which are chemically very similar to DNA. In this step, RNA molecules are said to be “transcribed” from
DNA, an operation that takes place in
the cell’s nucleus. As the archive for a
cell’s genetic instructions, nuclear
DNA is too precious to be shuffled
around the cell. Instead, the shorterlived RNA copy moves from the nucleus to the cytoplasm where its
code—its nucleotide sequence—is
“translated,” such that amino acids are
strung together to form proteins.
One way, then, to determine which
genes are being expressed at any given
time is to cull all of the RNA molecules
transcribed in a cell at that moment. In
this way, a scientist can determine
which gene or genes are active during
an important cellular activity—cell division, for example. Those RNAs are
likely coding for proteins whose specific function is to contribute to cell division, particularly if they are not transcribed when the cell is at rest. To make
that determination, scientists would
want to compare the cluster of RNAs
produced in a dividing cell with those
produced by a resting cell. Microarrays
allow for many such comparisons. In
our lab, for example, we are primarily
interested in comparing RNA molecules transcribed under normal conditions with those transcribed when the
cell is exposed to a toxic environmental
chemical. Microarrays allow us to assess very quickly all of the RNA molecules being transcribed in a cell at a
given time under particular circumstances. We can do this, even if we do
not know the exact function for each
gene. Yet knowing when that gene is
expressed may ultimately help us learn
the gene’s function as well.
Microarrays
Until recently, assessing RNA in cells
was painstaking and time-consuming.
In 1995, researchers including Patrick
Brown and colleagues at Stanford University developed a new technology
adapted from the microchips used by
the computer industry. The resulting
DNA microarrays—the so-called gene
chips—are indeed potent investigative
tools, where the status of thousands of
genes from any biological origin can be
monitored simultaneously for changes
in levels of gene expression. The difference between the old and new methods
is striking. Traditional assays measure
RNA transcripts from one gene at a time
over a three-day period. Gene chips can
measure transcripts from thousands of
genes in a single afternoon.
The theory behind the gene chip is
fairly simple and exploits a basic fact of
the chemistry of DNA and RNA. An
RNA molecule can bind with its DNA
template, but not with DNA templates
whose sequences are very different
© 2000 Sigma Xi, The Scientific Research Society. Reproduction
with permission only. Contact [email protected].
2000
November–December
509
untreated (control) cell
treated cell
nucleus
DNA
gene 1
gene 3
gene 5
gene 2
gene 4
RNA 1
RNA 5
gene 1
protein
5
protein
1
gene 3
gene 5
gene 2
gene 4
RNA 1
RNA 4
protein
4
protein
1
cytoplasm
Figure 2. Gene chips exploit some basic facts of molecular biology in order to determine the
subset of all the cell’s genes that are being expressed at any particular time. DNA is the
archival molecule found in the nucleus that contains the instructions—the genes—for making
proteins. The hypothetical cell shown here has five representative genes altogether. In the untreated, or control, cell only gene 1 and gene 5 are being expressed. In the treated cell gene 1
and gene 4 are being expressed. Expression begins when an RNA copy of the gene is made in
the nucleus. The RNA message is shuttled into the cytoplasm to guide the manufacture of proteins. Thus RNA 1 is copied, or transcribed, from gene 1 and is later “translated” into protein
1 in the cytoplasm. Likewise, gene 5 is transcribed into RNA 5 and translated into protein 5.
from its own. A gene chip holds copies
of most of the DNA templates contained within a particular cell. The subset of genes being expressed by that
cell type at any given time is expressed
as a group of RNA molecules, which
serve as messages to the protein-manufacturing machinery. In the laboratory, those RNA messages are transcribed once more to form
complementary DNA (cDNA) message molecules. A cDNA can also bind
with its complementary DNA tem-
gene 1
gene 3
gene 2
gene 5
plate. When the cDNAs are exposed to
the DNA chip, the message molecules
recognize and adhere to the spots on
the chip corresponding to their DNA
templates. These message molecules
have been tagged with fluorescent
dyes, so when scientists look at this
chip, they can see the pattern of genes
being expressed at any particular time.
They can also compare a spot and note
that a gene is not being expressed under one circumstance, but it is under
another. That is, no message is being
gene 1
gene 3
manufactured under, say, the normal
situation, but it is manufactured when
the cell is exposed to a toxic chemical.
A DNA chip is made using a glass
microscope slide, 7.62 centimeters by
2.54 centimeters and about 1.2 millimeters thick. Samples of DNA, in the
form of spots, are “printed” on the
slide, using a procedure similar to the
one used to print computer chips. The
DNA spots adhere to the slide, each
spot being a cloned DNA sequence
that represents a gene. The DNA molecules that make up the spots include
either fully sequenced genes of known
function, or collections of partially sequenced, unknown genes.
Chip manufacturing—printing or
spotting—is done with a machine
called an arrayer. Most arrayers are still
custom-built instruments featuring a
high-speed robotic arm fitted with a
number of pins. The arm is controlled
by software that allows the user to
place genes in select areas and configurations on the glass slide to generate a
cDNA microarray chip. The pins resemble the tips of quill pens. By capillary action, each pin draws up a small
amount of a solution containing the
DNA for a single gene and deposits it
in a precise location on a glass slide.
Since the arm holds many such pins,
many genes are deposited on the slide
at a time. Computers keep track of the
location of each gene on the gene chip.
The arrayer is housed in a clean
chamber where temperature and humidity are monitored and maintained
constant so as to produce consistent
and evenly sized spots. In some configurations it is possible to print up to
gene 5
gene 4
gene 2
gene 4
amplify
gene 1
gene 2
gene 3
gene 4
gene 5
Figure 3. Gene chips carry copies of many of the cell’s genes. Scientists remove the DNA from the cell through several molecular biological
methods, isolate and fragment the long DNA molecule into segments corresponding to individual genes (or sometimes very large fragments of
a gene sequence), which are then amplified. Each gene is then placed in a solution, and small amounts of each solution are placed into the wells
of a well plate.
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American Scientist, Volume 88
© 2000 Sigma Xi, The Scientific Research Society. Reproduction
with permission only. Contact [email protected].
arrayer
pins
e1
gen ene 2 3
g gene e 4
gen ene 5
a
g
1
Figure 4. Genes are then plated onto a glass slide by a robotic arm called an arrayer. The arrayer has a number of pins that are first dipped into the well plate, drawing out a small bit of
each solution on each pin (a). The pins then “print” the chip by releasing the solution onto a
glass slide (b). The gene chip (c) now contains spots, each containing the DNA for one gene.
The slides to be spotted are placed on the trays shown in the photograph, and the robotic arm
of the arrayer moves over each slide. A computer keeps track of the position of each gene spot.
(Photograph courtesy of the authors.)
50,000 genes on one chip, and efforts
are underway to increase that number as demand grows. The spotted
genes/DNA are linked to the surface
of the glass slide by either covalent
bonds or charge interactions.
Comparing Samples
Once the gene chip is prepared and is
spotted with the entire set of cDNAs
from the cell or tissue of interest, investigators can use it to look at gene expression in various cells and organs under different circumstances. This again
is done by withdrawing message molecules from the sample cells or organs to
see exactly which subset of genes is being expressed at any given moment. In
this way, patterns of gene expression
may be compared from a normal versus diseased tissue, an untreated versus drug or chemically treated cell, or a
normal versus a mutant cell.
Messages in the form of RNA may
be derived from any species, including
bacteria, fungi, plants or animals. Most
RNA molecules code for protein and
are shuttled from the cell nucleus to the
cytoplasm and there are translated into
protein. These so-called messenger
RNA molecules (mRNA) can contain
between 400 to 10,000 nucleotides, the
sequence of which serves to indicate
the corresponding amino acid sequence of a protein.
The number of copies of the RNA
“message” transcribed from a gene often relates directly to the quantity of
protein ultimately produced. For example, if a large amount of protein will be
required, a large number of RNA transcripts for that protein will probably be
present in the cell’s cytoplasm. A small
amount of RNA in the cytoplasm may
indicate that a small amount of protein
is to be made. Therefore, by measuring
the amount of message in the cell, scientists can not only determine which
genes are being expressed, they can
also determine at what levels they are
being expressed. This is especially useful for comparisons between samples.
Often scientists want to know whether
certain conditions alter the level of gene
expression—that is, whether a particular gene is expressed in greater or lesser
quantities in response to some environmental exposure.
Differential expression measurements
are carried out using a simultaneous,
two-color fluorescence hybridization
scheme. cDNAs are converted from
RNA molecules in the presence of nucleotides to which a fluorescent colored
2
3
4
5
glass slide
b
1
2
3
4
5
gene chip
c
dye has been attached. Different colors
can be given to the message derived
from different cells, such that the message from the control cells can be tagged
green, for example, whereas the message
from chemically treated cells might be
tagged red.
The color-coding allows for a very
clear way of comparing the quantities
of message from each cell. The fluorescently labeled messages derived from
different groups of cells are mixed and
bound simultaneously on the same
cDNA microarray chip. The array is
then optically scanned at two wavelengths using independent lasers to excite the two fluorescent dyes at 632 and
532 nanometers for the red and green
labels, respectively. Information from
the scanner is translated into images
corresponding to the two dyes scanned,
and this is sent to a computer for further analysis. The computer produces
two different pictures of the gene chip.
One shows the location of all the spots
© 2000 Sigma Xi, The Scientific Research Society. Reproduction
with permission only. Contact [email protected].
2000
November–December
511
untreated (control) cell
treated cell
nucleus
DNA
gene 1
gene 3
gene 5
gene 2
gene 4
RNA 1
RNA 5
gene 1
protein
5
protein
1
gene 3
gene 5
gene 2
gene 4
RNA 1
RNA 4
protein
4
protein
1
cytoplasm
a
RNA isolation
RNA 5
RNA 1
RNA 5
RNA 1
RNA 5
RNA 1
RNA 1
RNA 1
RNA 4
RNA 5
RNA 4
RNA 4
RNA 1
RNA 4
RNA 1
RNA 1
fluorescent
tag (green)
fluorescent
tag (red)
reverse transcription
cDNA 1
cDNA 5 cDNA 1
cDNA 4
cDNA 1
cDNA 5
cDNA 1
cDNA 5
cDNA 5
cDNA 4
cDNA 1
cDNA 4
cDNA 1
cDNA 1
cDNA 1
cDNA 4
b
cDNA 1
1
DNA
cDNA 4
2
DNA
3
DNA
4
DNA
cDNA 5
5
DNA
to laser scanner
c
1
2
3
4
5
+
green channel
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1
2
3
4
red channel
5
=
1
2
3
4
5
relative expressions
lit in green and notes the intensity of
the green spots. The other picture notes
the location and intensity of all of the
red spots.
These two images are then overlaid
using specialized software that assigns
a color for each tag and compares the
two images. The result is a very colorful display of spots ranging between
green and red. From this, scientists can
determine the relative abundance of
message manufactured in each cell.
For example, if a gene is expressed
in equal amounts in both the control
and the treated samples, then the computer will note equal amounts of red
dye and green dye. The computer will
indicate such a spot as yellow. Should a
gene be highly expressed in the control
cell, the one where the messages are
colored green, but less so in the treated
cell, then the spot will show up as predominantly green. If the gene is expressed in the treated cell but less so in
the control, the spot will show up as
predominantly red.
Analysis of Data
Image-analysis software generates a
report that contains numerical data,
which are more informative than the
colorful spotted figure. The results are
generated in a variety of formats depending on the software used. The report contains ratios calculated for each
Figure 5. Gene expression can be discerned
by determining which genes are being transcribed into RNA at a particular time or under particular circumstances. RNA message
is not very stable, so after it is extracted from
the cell, it is converted via a process called reverse transcription into complementary DNA
(cDNA) (a). Different fluorescent tags are incorporated into the cDNAs as they are being
made, so scientists can distinguish the message molecules derived from the control cell
from those coming from the treated cell. All
of the tagged message molecules are mixed
together in a test tube and then spread onto
the gene chips (b). Messages can bind with
spots corresponding to their template DNA
molecules on the gene chip, but not with other spots. The next step is to determine how
much message corresponding to each gene
has been derived from each biological sample (c). For example, both the control and the
treated cells produce message for gene 1, so
equal amounts of green and red-tagged message molecules adhere to spot 1 on the chip.
Message 4 is made only by the treated cell, so
only red-tagged message 4 molecules adhere
to spot 4. Similarly, message 5 is produced
only by the control cell, so only green-tagged
molecules adhere to spot 5.
© 2000 Sigma Xi, The Scientific Research Society. Reproduction
with permission only. Contact [email protected].
croarray data is called “clustering.” Clustering programs use predefined algorithms to group significantly changed
genes according to their strength of expression or pattern of expression across
different experiments.
Figure 6. Laser-based scanners can determine how much red or green fluorescence is emanating from each spot on each chip. The chip is scanned on the “green” channel to determine first
how much green fluorescence is coming from each spot and then again on the “red” channel.
The data from the two separate channels are then summed by a computer to yield a color-coded guide to gene expression. When a gene is expressed at equal levels in different cells, as is
gene 1 in Figure 5, the mixture of their message tags should register yellow. Messages expressed exclusively in one or the other cell type will register as either mostly green or red. Different ratios of red- and green-tagged message molecules will yield a gradient of colors from
pure green to pure red.
gene. These are derived from the intensity values of the two color scans. A
gene expressed in equal intensities in
the two samples would exhibit a ratio
close to one. Using a statistical formula, the software determines the set of
genes whose expression is significantly altered in the treated cells. This
method is highly sensitive. It is possible to detect changes in the expression
level of a gene of about 1.5 times using
this technology.
The amount of data that results from
these experiments can often be overwhelming. A single gene chip may
generate over 10,000 data points. The
volume of data grows exponentially
when one uses multiple sets of chips,
as is the case when replicate experi-
ments are performed. In addition, for
some biological studies it may be necessary to examine changes in gene expression over multiple time points or
with varying dose levels.
The reams of data pose a considerable analytical problem, one that many
biological researchers regard as the
toughest part of a study. The emerging
science of bioinformatics becomes very
helpful in that case. Bioinformatics is
the discipline in which large amounts
of data are sorted into intuitive databases, analyzed and presented in an
understandable form.
Analytical software draws comparisons between samples and genes across
different biological conditions. One
method that has been adapted for mi-
Complementing Genomic Resources
A subset of the spots plated onto a chip
carrys known genes, but most microarray chips will contain a significant portion of unknown genes. The functions
of many of these unknown genes may
be revealed with the help of computing
and bioinformatics resources. Much of
the information generated is filed in
large-scale public databases.
These databases are constantly updated with information such as the sequences of discovered genes, their current known function and their latest
nomenclature. The National Center for
Biotechnology Information (NCBI), a
branch of the National Institutes of
Health, creates public databases, conducts research in computational biology, develops software tools for analyzing genome data and disseminates
biomedical information. An example of
such a database is UniGene, which is
an experimental system for automatically partitioning sequences in the larger GenBank database into a non-redundant set of gene-oriented clusters. Each
UniGene “cluster” contains sequences
that represent a unique gene, as well as
related information, such as the tissue
types in which the gene is expressed.
In addition to sequences of well-characterized genes, hundreds of thousands
of novel expressed sequence tag (EST) sequences—sequences from genes that remain undidentified that are known only
through their message—can be found
Figure 7. Once processed through the computer, actual gene chips show up as a colorful display of spots. Shown here are the results from three
gene chips each containing the same set of genes. Chips are processed in duplicate or triplicate to ensure consistency of results. (Image courtesy
of the authors.)
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2000
November–December
513
class 1
CLASS 1
class 2
CLASS 2
Figure 8. Results from gene chips are further processed statistically to uncover patterns in the
spots. The cluster diagram here clearly distinguishes the expression profiles of cells exposed
to two different classes of environmental toxicants. Chemical class 1 activates a particular
suite of genes, whereas class 2 chemicals activate a different suite of genes, which are silenced
by class 1 chemicals. From such clustering data, environmental scientists can describe a “taxonomy” of chemicals, noting which chemicals give related gene responses. (Image courtesy of
the authors.)
A
known agents
B
in UniGene. This collection is an invaluable resource for microarray researchers, since a lot of the spots printed
on chips are ESTs. Consequently, this resource facilitates the identification of a
gene for which large-scale analysis indicates an involvement of some of the
ESTs. Microarray users’ results depend
on these databases to ensure that their
data reflect the latest updates on genes.
This ultimately makes a microarray
data set even more meaningful. In the
near future, databases of expression
profiles will be publicly available. These
databases include information about the
sample quality and conditions under
which it was produced, hybridization
conditions and quality, scanning quality
and outlier lists. This database will be
made available to all scientists interested in learning from the data. The database user or “virtual experimenter” will
have information about many different
compounds and their signature effects
within the context of the defined biological model.
C
unknown agent
raw data
toxicant
signature
no match
no match
match
Figure 9. Databases of gene responses to known chemicals may one day help environmental scientists make determinations about the likely
health effects of chemicals that are unfamiliar to them. In this example, the gene expression pattern of a cell exposed to an unknown chemical
agent is compared with patterns from known agents. The pattern of the unknown agent is different from chemicals those of B and C, but matches the pattern seen with chemical A. It may be possible that the unknown agent is chemically similar to chemical A. It also seems likely that the
unknown agent will affect the health of an individual in the same way that chemical A does. As more and more expression profiles are filed in
databases, gene chips will be employed in many important applications, including determining the action of pharmaceutical agents and diagnosing diseases.
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American Scientist, Volume 88
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with permission only. Contact [email protected].
Impact of cDNA Microarrays
Microarray technology will undoubtedly have a profound impact on many
avenues of biological and biomedical
research, including toxicology, the
main focus of our laboratory. Toxicology seeks to understand how chemicals
from natural, synthetic or endogenous
sources might affect humans and the
environment. Here, scientists correlate
gene expression patterns with biological and pathological assays to determine whether particular chemicals are
harmful.
Toxicologists play an important role
in defining the conditions under which
chemicals may be safely employed for
good causes and when a particular
chemical should be avoided. Toxicologists also use gene-expression data to
understand how particular toxicants
affect the inner workings of the cell.
In the early days of toxicological assessment, it took months or years to establish the relation between a compound and the pathway it altered. In
those days, investigators were unable
to predict the key cellular players involved in the reaction of an organism
to some form of environmental insult.
These investigators were put in the position of essentially guessing which of
the hundreds of cellular pathways
might be affected. Testing these guesses to produce concrete results required
the time and energy of many research
teams working in concert for years,
building on the information provided
by previous groups. That the whole
process might someday be undertaken
by a group during a much shorter period of time was, just a few years ago,
unimaginable.
New advances in genomics technology, such as the cDNA microarray
chip, offer major shortcuts to many of
our research problems. Investigators
may identify important components in
cellular pathways and characterize genetic footprints diagnostic for exposure
to certain compounds. This technology may allow us to predict the cellular
effects of new compounds—a boon not
only to toxicologists but to the pharmaceutical industry as well. Use of this
technology increases the efficiency of
testing compounds for toxicological or
pharmaceutical action and betters our
understanding of which compounds to
advance to later stages of clinical trials
in humans.
As our use and expertise with microarray technology grows, we will have
databases with expression profiles for
hundreds, even thousands of genes.
One will then be able to compare a new
compound’s expression profile to existing profiles. One might even be able to
link the gene expression profile with
chemical structure and predict which
part of a certain molecule is responsible
for the gene expression response. This
technology improves our understanding of the effects of how introducing a
gene into an animal might influence
other biological functions.
Microarrays are certainly a giant leap
into the future of performing quality biological research that holds the promise
to aid in discovery of better chemicals,
diagnostics and pharmaceutical compounds and ultimately, to improve the
quality of life of future generations.
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