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Just the Facts: A Basic Introduction to the
Science Underlying NCBI Resources

MICROARRAYS: CHIPPING AWAY AT THE MYSTERIES OF SCIENCE AND
MEDICINE

The proper and
harmonious expression of a large number of genes is a
critical component of normal growth and development and
the maintenance of proper health. Disruptions or changes
in gene expression are responsible for many diseases.

With only a few exceptions, every cell of the body contains a
full set of chromosomes and identical genes. Only a fraction of
these genes are turned on, however, and it is the subset that is
"expressed" that confers unique properties to each cell type.
"Gene expression" is the term used to describe the
transcription of the information contained within the DNA,
the repository of genetic information, into messenger RNA (mRNA)
molecules that are then translated into the proteins that perform
most of the critical functions of cells. Scientists study the kinds
and amounts of mRNA produced by a cell to learn which genes are
expressed, which in turn provides insights into how the cell
responds to its changing needs. Gene expression is a highly complex
and tightly regulated process that allows a cell to respond
dynamically both to environmental stimuli and to its own changing
needs. This mechanism acts as both an "on/off" switch
to control which genes are expressed in a cell as well as a
"volume control" that increases or decreases the level of
expression of particular genes as necessary.

Enabling Technologies

Biomedical research evolves and advances not
only through the compilation of knowledge but also through the
development of new technologies. Using traditional methods to
assay gene expression, researchers were able to survey a
relatively small number of genes at a time. The emergence of
new tools enables researchers to address previously
intractable problems and to uncover novel potential targets
for therapies. Microarrays allow scientists to analyze
expression of many genes in a single experiment quickly and
efficiently. They represent a major methodological advance and
illustrate how the advent of new technologies provides
powerful tools for researchers. Scientists are using
microarray technology to try to understand fundamental aspects
of growth and development as well as to explore the underlying
genetic causes of many human
diseases.

DNA Microarrays: The Technical Foundations

Two recent complementary advances, one in knowledge and one in
technology, are greatly facilitating the study of gene expression
and the discovery of the roles played by specific genes in the
development of disease. As a result of the Human Genome Project,
there has been an explosion in the amount of information available
about the DNA sequence of the human genome. Consequently,
researchers have identified a large number of novel genes within
these previously unknown sequences. The challenge currently facing
scientists is to find a way to organize and catalog this vast amount
of information into a usable form. Only after the functions of the
new genes are discovered will the full impact of the Human Genome
Project be realized.

The second advance may facilitate the identification and
classification of this DNA sequence information and the assignment
of functions to these new genes: the emergence of DNA microarray
technology. A microarray works by exploiting the ability of a
given mRNA molecule to bind specifically to, or hybridize to,
the DNA template from which it originated. By using an array
containing many DNA samples, scientists can determine, in a single
experiment, the expression levels of hundreds or thousands of genes
within a cell by measuring the amount of mRNA bound to each site on
the array. With the aid of a computer, the amount of mRNA bound to
the spots on the microarray is precisely measured, generating a
profile of gene expression in the cell.

A
microarray is a tool for analyzing gene
expression that consists of a small membrane or glass
slide containing samples of many genes arranged in a
regular
pattern.

Why Are Microarrays Important?

Microarrays are a significant advance both because they may
contain a very large number of genes and because of their
small size. Microarrays are therefore useful when one wants
to survey a large number of genes quickly or when the sample to be
studied is small. Microarrays may be used to assay gene expression
within a single sample or to compare gene expression in two
different cell types or tissue samples, such as in healthy and
diseased tissue. Because a microarray can be used to examine the
expression of hundreds or thousands of genes at once, it promises to
revolutionize the way scientists examine gene expression. This
technology is still considered to be in its infancy; therefore, many
initial studies using microarrays have represented simple surveys of
gene expression profiles in a variety of cell types. Nevertheless,
these studies represent an important and necessary first step in our
understanding and cataloging of the human genome.

As more information accumulates, scientists will be able to use
microarrays to ask increasingly complex questions and perform more
intricate experiments. With new advances, researchers will be able
to infer probable functions of new genes based on similarities in
expression patterns with those of known genes. Ultimately, these
studies promise to expand the size of existing gene families, reveal
new patterns of coordinated gene expression across gene families,
and uncover entirely new categories of genes. Furthermore, because
the product of any one gene usually interacts with those of many
others, our understanding of how these genes coordinate will become
clearer through such analyses, and precise knowledge of these
inter-relationships will emerge. The use of microarrays may also
speed the identification of genes involved in the development of
various diseases by enabling scientists to examine a much larger
number of genes. This technology will also aid the examination of
the integration of gene expression and function at the cellular
level, revealing how multiple gene products work together to produce
physical and chemical responses to both static and changing cellular
needs.

What Exactly Is a DNA Microarray?

DNA Microarrays are small, solid supports onto which the
sequences from thousands of different genes are immobilized, or
attached, at fixed locations. The supports themselves are usually
glass microscope slides, the size of two side-by-side pinky
fingers, but can also be silicon chips or nylon
membranes. The DNA is printed, spotted, or actually synthesized
directly onto the support.

The American Heritage Dictionary defines "array" as "to
place in an orderly arrangement". It is important that the gene
sequences in a microarray are attached to their support in an
orderly or fixed way, because a researcher uses the location of each
spot in the array to identify a particular gene sequence. The spots
themselves can be DNA, cDNA, or oligonucleotides.

An oligonucleotide,
or oligo as it is commonly called, is a short fragment of a
single-stranded DNA that is typically 5 to 50 nucleotides
long.

Designing a Microarray Experiment: The Basic Steps

One might ask, how does a scientist extract information about a
disease condition from a dime-sized glass or silicon chip containing
thousands of individual gene sequences? The whole process is based
on hybridization probing, a technique that uses fluorescently
labeled nucleic acid molecules as "mobile probes" to identify
complementary molecules, sequences that are able to base-pair
with one another. Each single-stranded DNA fragment is made up of
four different nucleotides, adenine (A), thymine (T), guanine (G),
and cytosine (C), that are linked end to end. Adenine is the
complement of, or will always pair with, thymine, and guanine
is the complement of cytosine. Therefore, the complementary sequence
to G-T-C-C-T-A will be C-A-G-G-A-T. When two complementary sequences
find each other, such as the immobilized target DNA and the mobile
probe DNA, cDNA, or mRNA, they will lock together, or
hybridize.

Now, consider two cells: cell type 1, a healthy cell, and cell
type 2, a diseased cell. Both contain an identical set of four
genes, A, B, C, and D. Scientists are interested in
determining the expression profile of these four genes in the two
cell types. To do this, scientists isolate mRNA from each cell type
and use this mRNA as templates to generate cDNA with a
"fluorescent tag" attached. Different tags (red and green)
are used so that the samples can be differentiated in subsequent
steps. The two labeled samples are then mixed and incubated with a
microarray containing the immobilized genes A, B, C, and
D. The labeled molecules bind to the sites on the array
corresponding to the genes expressed in each cell.

A DNA Microarray Experiment

1. Prepare your DNA chip using your
chosen target DNAs.

3. Incubate your hybridization mixture
containing fluorescently labeled cDNAs with your DNA
chip.

4. Detect bound cDNA using
laser technology and store data in a computer.

5. Analyze data
using computational methods.

2. Generate a hybridization solution
containing a mixture of fluorescently labeled
cDNAs.

After this hybridization step is complete, a researcher will
place the microarray in a "reader" or "scanner" that consists
of some lasers, a special microscope, and a camera. The fluorescent
tags are excited by the laser, and the microscope and camera work
together to create a digital image of the array. These data are then
stored in a computer, and a special program is used either to
calculate the red-to-green fluorescence ratio or to subtract out
background data for each microarray spot by analyzing the digital
image of the array. If calculating ratios, the program then creates
a table that contains the ratios of the intensity of red-to-green
fluorescence for every spot on the array. For example, using the
scenario outlined above, the computer may conclude that both cell
types express gene A at the same level, that cell 1 expresses
more of gene B, that cell 2 expresses more of gene C,
and that neither cell expresses gene D. But remember, this is
a simple example used to demonstrate key points in experimental
design. Some microarray experiments can contain up to 30,000 target
spots. Therefore, the data generated from a single array can mount
up quickly.

The Colors of a
Microarray

Reproduced with permission from the Office of
Science Education, the National Institutes of
Health.

In this
schematic:

GREEN represents Control DNA, where either DNA or
cDNA derived from normal tissue is hybridized to the target
DNA.

RED
represents Sample DNA, where
either DNA or cDNA is derived from diseased tissue hybridized
to the target DNA.

YELLOW represents a combination of Control and Sample
DNA, where both hybridized equally to the target
DNA.

BLACK represents areas where
neither the Control nor Sample DNA hybridized to the
target DNA.

Each spot on an array is associated
with a particular gene. Each color in an array represents
either healthy (control) or diseased (sample) tissue.
Depending on the type of array used, the location and
intensity of a color will tell us whether the gene, or
mutation, is present in either the control and/or sample DNA.
It will also provide an estimate of the expression level of
the gene(s) in the sample and control
DNA.

Types of Microarrays

There are three basic types of samples that can be used to
construct DNA microarrays, two are genomic and the other is
"transcriptomic", that is, it measures mRNA levels. What
makes them different from each other is the kind of immobilized DNA
used to generate the array and, ultimately, the kind of information
that is derived from the chip. The target DNA used will also
determine the type of control and sample DNA that is used in the
hybridization solution.

I. Changes in Gene Expression Levels

Determining the level, or volume, at which a certain gene is
expressed is called microarray expression analysis, and the
arrays used in this kind of analysis are called "expression
chips". The immobilized DNA is cDNA derived from the mRNA of
known genes, and once again, at least in some experiments, the
control and sample DNA hybridized to the chip is cDNA derived from
the mRNA of normal and diseased tissue, respectively. If a gene is
overexpressed in a certain disease state, then more sample cDNA, as
compared to control cDNA, will hybridize to the spot representing
that expressed gene. In turn, the spot will fluoresce red with
greater intensity than it will fluoresce green. Once researchers
have characterized the expression patterns of various genes involved
in many diseases, cDNA derived from diseased tissue from any
individual can be hybridized to determine whether the expression
pattern of the gene from the individual matches the expression
pattern of a known disease. If this is the case, treatment
appropriate for that disease can be initiated.

As researchers use expression chips to detect expression
patterns— whether a particular gene(s) is being expressed more
or less under certain circumstances—expression chips may also be
used to examine changes in gene expression over a given period of
time, such as within the cell cycle. The cell cycle is a
molecualr network that determines, in the normal cell, if the cell
should pass through its life cycle. There are a variety of genes
involved in regulating the stages of the cell cycle. Also built into
this network are mechanisms designed to protect the body when this
system fails or breaks down because of mutations within one of the
"control genes", as is the case with cancerous cell
growth. An expression microarray "experiment" could be designed
where cell cycle data are generated in multiple arrays and
referenced to time "zero". Analysis of the collected data could
further elucidate details of the cell cycle and its "clock",
providing much needed data on the points at which gene mutation
leads to cancerous growth as well as sources of therapeutic
intervention.

In the same way, expression chips can be used to develop new
drugs. For instance, if a certain gene is overexpressed in a
particular form of cancer, researchers can use expression chips to
see if a new drug will reduce overexpression and force the cancer
into remission. Expression chips could also be used in disease
diagnosis as well, e.g., in the identification of new genes involved
in environmentally triggered diseases, such as those diseases
affecting the immune, nervous, and pulmonary/respiratory
systems.

II. Genomic Gains and Losses

DNA repair genes are thought to be the body's frontline
defense against mutations and, as such, play a major role in cancer.
Mutations within these genes often manifest themselves as lost or
broken chromosomes. It has been hypothesized that certain
chromosomal gains and losses are related to cancer progression and
that the patterns of these changes are relevant to clinical
prognosis. Using different laboratory methods, researchers can
measure gains and losses in the copy number of chromosomal regions
in tumor cells. Then, using mathematical models to analyze these
data, they can predict which chromosomal regions are most likely to
harbor important genes for tumor initiation and disease progression.
The results of such an analysis may be depicted as a hierarchical
treelike branching diagram, referred to as a "tree model of tumor
progression".

Researchers use a technique called microarray Comparative Genomic
Hybridization (CGH) to look for genomic gains and losses or
for a change in the number of copies of a particular gene involved
in a disease state. In microarray CGH, large pieces of genomic DNA
serve as the target DNA, and each spot of target DNA in the array
has a known chromosomal location. The hybridization mixture will
contain fluorescently labeled genomic DNA harvested from both normal
(control) and diseased (sample) tissue.

Therefore, if the number of copies of a particular target gene
has increased, a large amount of sample DNA will hybridize to those
spots on the microarray that represent the gene involved in that
disease, whereas comparatively small amounts of control DNA will
hybridize to those same spots. As a result, those spots containing
the disease gene will fluoresce red with greater intensity than they
will fluoresce green, indicating that the number of copies of the
gene involved in the disease has gone up.

III. Mutations in DNA

When researchers use microarrays to detect mutations or
polymorphisms in a gene sequence, the target, or immobilized DNA, is
usually that of a single gene. In this case though, the target
sequence placed on any given spot within the array will differ from
that of other spots in the same microarray, sometimes by only one or
a few specific nucleotides. One type of sequence commonly used in
this type of analysis is called a Single Nucleotide
Polymorphism, or SNP, a small genetic change or variation
that can occur within a person's DNA sequence. Another difference in
mutation microarray analysis, as compared to expression or
CGH microarrays, is that this type of experiment only requires
genomic DNA derived from a normal sample for use in the
hybridization mixture.

Once researchers have established that a SNP pattern is
associated with a particular disease, they can use SNP microarray
technology to test an individual for that disease expression pattern
to determine whether he or she is susceptible to (at risk of
developing) that disease. When genomic DNA from an individual is
hybridized to an array loaded with various SNPs, the sample DNA will
hybridize with greater frequency only to specific SNPs associated
with that person. Those spots on the microarray will then fluoresce
with greater intensity, demonstrating that the individual being
tested may have, or is at risk for developing, that disease.

In Brief: Microarray Applications

Microarray
type

Application

CGH

Tumor
classification, risk assessment, and prognosis
prediction

Expression analysis

Drug
development, drug response, and therapy
development

Mutation/Polymorphism analysis

Drug
development, therapy development, and tracking disease
progression

NCBI and Microarray Data Management

Why is it necessary to have a uniform system that will manage and
provide a disbursement point for microarray data? Consider the
amount of data that can potentially be generated using a single
microarray chip. Suppose that chip contains 30,000 spots of target
DNA. Researchers interpreting the data generated by that chip would
need to know the biological identity of each target—what gene is
where; the biological properties of the control and sample DNA; the
experimental conditions and procedures used in setting up the
experiment; and finally, the results. Although experiments such as
these will undoubtedly push forward our current understanding of
gene expression and regulation, many new challenges are presented in
terms of data tracking and analysis.

What Is GEO?

As we have just alluded, microarray technology is one of the most
recent and important experimental breakthroughs in molecular
biology. Today, proficiency in generating data is fast overcoming
the capacity for storing and analyzing it. Much of this information
is scattered across the Internet or is not even available to the
public. As more laboratories acquire this technology, the problem
will only get worse. This avalanche of data requires standardization
of storage, sharing, and publishing techniques.

To support the public use and dissemination of gene expression
data, NCBI has launched the Gene Expression
Omnibus, or GEO. GEO represents NCBI's effort to
build an expression data repository and online resource for the
storage and retrieval of gene expression data from any organism or
artificial source. Many types of gene expression data, such as those
types discussed in this primer, are accepted and archived as a
public dataset.

Developing MAML: Reading Off the Same Platform

Microarray Markup Language, developed by the "MAML"
working group of MGED, the Microarray Gene Expression
Database, is a first attempt to provide a standard platform for
submitting and analyzing the enormous amounts of microarray
expression data generated by different laboratories around the
world. The goal of this group, which includes NCBI investigators, is
to facilitate the adoption of standards for DNA-array experiment
annotation and data representation, as well as the introduction of
standard experimental controls and data normalization methods. The
underlying goal is to facilitate the establishment of gene
expression data repositories, the comparability of gene expression
data from different sources, the interoperability of different gene
expression databases, and data analysis software.

MAML proposes a framework for describing information about a
DNA-array experiment and a data format for communicating this
information, including details about:

Experimental design: the set of the hybridization
experiments as a whole

Array design: each array used and each spot on the
array

Samples: samples used, the extract preparation, and
labeling

Hybridizations: procedures and parameters

Measurements: images, quantitation, and
specifications

Controls: types, values, and specifications

MAML is independent of the particular experimental platform and
provides a framework for describing experiments done on all types of
DNA arrays, including spotted and synthesized arrays, as well as
oligo and cDNA arrays. What's more, MAML provides format to
represent microarray data in a flexible way, which allows analysis
of data obtained from not only any existing microarray platforms but
also many of the possible future variants, including protein
arrays.

Although the data in GEO are not currently provided in MAML
format, it is NCBI's goal to have the data delivered in a number of
formats, including MAML, soon to be replaced by a more recent
version called MAGEML (MicroArray Gene Expression Markup
Language).

The Benefits of GEO and
MAML

By storing vast amounts of data on gene expression
profiles derived from multiple experiments using varied
criteria and conditions, GEO will aid in the study of
functional genomics—the development and application of
global experimental approaches to assess gene function

GEO will facilitate the cross-validation of data
obtained using different techniques and technologies and
will help set benchmarks and standards for further gene
expression studies

By making the information stored in GEO publicly
available, the fields of bioinformatics and functional
genomics will be both promoted and advanced

That such experimental data should be freely accessible
to all is consistent with NCBI's legislative mandate and
mission: to develop new information technologies to aid in
the understanding of fundamental molecular and genetic
processes that control health and disease

The Promise of Microarray Technology in Treating Disease

Now that you understand the concept behind array technology,
picture this: a hand-held instrument that a physician could use to
quickly diagnose cancer or other diseases during a routine office
visit. What if that same instrument could also facilitate a
personalized treatment regimen, exactly right for you? Personalized
drugs. Molecular diagnostics. Integration of diagnosis and
therapeutics. These are the long-term promises of microarray
technology. Maybe not today or even tomorrow, but someday. For the
first time, arrays offer hope for obtaining global views of
biological processes—simultaneous readouts of all the body's
components—by providing a systematic way to survey DNA and RNA
variation. NCBI, by continuing its efforts to provide a standard
format for microarray data and to provide free, universal access to
that data, will help the scientific community in making those
promises realities.

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Revised: July 27,
2007.

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What
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