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Summary and recommendations from a workshop organized under the auspices
of the NIMH, NIDA, and NINDS at Laguna Beach, CA in January 2002
Marc Tessier-Lavigne and Lubert Stryer, organizers
Contents:
Part I: Overview and Summary
- Opportunities and Challenges
The brain is the most complex organ in our body, responsible for perception,
behavior, cognition, memory, and consciousness. It is comprised of about
a trillion nerve cells, or neurons, whose intricate and precisely wired
connections underlie all of these functions. But the neurons are not
all the same: many thousands of different classes of neurons, defined
by a variety of criteria such as morphology, patterns of connectivity,
and expression of particular neurotransmitters and receptors, serve
as the cellular building blocks of the brain. Each of these neuronal
types has a specific physiological role in brain function. Neurological
and psychiatric diseases are diseases of particular neurons or neural
circuits.
The complexity of brain cell types and circuits is reflected in the
complexity of gene expression patterns in the brain. It is believed
that perhaps a third to half of all genes are largely or exclusively
dedicated to directing the development, maintenance and functioning
of the brain. With more than 30,000 genes in the human genome, the task
of mapping all genes to the many thousands of neuronal classes and neuronal
circuits Ð what is being called molecular neuroanatomy Ð might seem
beyond reach. In fact, this mapping is taking place. It is proving to
be remarkably informative and illuminating despite being performed on
a relatively small scale thus far, with about a thousand genes mapped,
and some mapped only in particular subregions of the brain. Such studies
have shown that analysis of gene expression in neurons can yield essential
information on neural development and function, such as the identity
of neurons involved in responses to particular drugs, or the genes that
control the development of particular classes of neurons. Such analysis
has also defined molecular markers of particular neuronal cell types,
helping with the taxonomy of brain cell types Ð the division of known
neuronal classes into further subclasses. Especially important, the
availability of cell type-specific molecular markers for particular
neuronal classes has provided tools to deliver genes and gene products
to those neurons (in ways discussed below), dramatically facilitating
the analysis of their development, connectivity, function, and dysfunction.
The potential medical benefits that will derive from this knowledge
are immense. The identification of genes expressed in particular classes
of neurons linked to specific diseases provides new drug targets for
the treatment of a wide range of ailments including stroke, spinal cord
injury, neurodegenerative diseases like Parkinson's disease, brain tumors,
schizophrenia, depression, anxiety disorders, and addiction. Neuronal
cell type-specific markers provide a means for developing gene therapies
that involved changing gene expression in particular neurons. They also
make it possible to visualize neural circuits in their normal and abnormal
states, which is likely to have a large impact on the diagnosis of disease
and the evaluation of the effectiveness of therapy. The identification
of transcription factors that control cell fate and connectivity in
the brain will accelerate the development of therapies to regenerate
nervous tissue.
In the 1990s, several Institutes of the National Institutes of Health,
recognizing the importance and promise of molecular neuroanatomy for
public health, launched the Brain Molecular Anatomy Project (BMAP),
a series of funding initiatives to map gene and gene product expression
to neuronal cell types to create a Molecular Brain Map. In January 2002,
a workshop was convened by NIMH, NINDS, and NIDA to bring together experts
in the field (Table 1) to take stock of existing efforts, formulate
recommendations for upcoming work in this field, and help establish
scientific priorities, especially in light of the exceptional opportunities
created by the completion of the Human Genome Project and the identification
of nearly all genes in the genome.
- A need to generate rapidly a Molecular Brain Map
A consensus view of the working group, reiterating the premise of BMAP,
is that enormous benefit will derive from a systematic, large-scale,
and organized effort to generate a Molecular Brain Map for humans and
the mouse. The utility of a systematic effort is well illustrated by
the Human Genome Project. Prior to the Project, the genome was already
being sequenced in a piecemeal fashion by thousands of investigators
world-wide, but these laboratory-based initiatives involved considerable
redundancy as well as inefficiencies because of their small scale. An
organized effort to sequence the human genome Ð and that of other species
Ð made it possible to achieve an enormous economy of scale and to complete
the sequencing of genomes much more rapidly, thereby empowering the
entire biomedical community and greatly accelerating the pace of discovery
of new knowledge and novel therapeutics. In the same way, the creation
of a Molecular Brain Map would eventually result from the independent
activities of individual investigators, but an economy of scale can
be achieved through more systematic efforts, like those already supported
by the NIH (see below). The acceleration of this process will in turn
accelerate the pace of discovery in the neurosciences, neurology, and
psychiatry.
- Summary of recommendations
The working group achieved consensus on the following principles, many
of which have already been incorporated into existing efforts at the
National Institutes of Health.
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It affirmed the importance of driving to completion the generation
of a Molecular Brain Map, a tool that will revolutionize the study
of both normal brain function and development, as well as neurological
and psychiatric disease.
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An impressive start has been made in initiating several approaches
to accomplish this goal, but the pace needs to be markedly accelerated.
At the next stage, the scope should also be broadened: It is essential
that functional circuits as well as individual neurons be mapped,
i.e. the Gene Expression Map needs to be supplemented with a Connectivity
Map. Both efforts would benefit at this stage from the simultaneous
pursuit of a broad survey of expression of all genes, and an in-depth
focus on particular model neural circuits.
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It affirmed the need to set standards for the generation, acquisition,
mining and sharing of data in this Map, to permit its efficient
construction and utilization.
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It catalogued a set of enabling reagents, datasets, and complementary
technologies that need to be developed to construct this Map efficiently
and to exploit it to the fullest for the study of brain function
and dysfunction (Tables 2 and 3).
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It affirmed the importance of full public access to the information,
reagents, and technologies that will be generated in this initiative,
to leverage these resources for the advancement of knowledge and
for biomedical progress.
In Parts II-IV of this report, we provide background information on
molecular neuroanatomy, including a description of existing large scale
initiatives, and discuss emerging opportunities. In part V, we discuss
in detail the recommendations and priorities formulated by the participants
that were summarized above.
Table 1: Workshop Participants
David J. Anderson, Ph.D.
California Institute of Technology |
Carolee Barlow, M.D., Ph.D.
The Salk Institute for Biological Studies |
Sydney Brenner, Ph.D.
The Salk Institute for Biological Studies |
Catherine Dulac, Ph.D.
Harvard University |
Gregor Eichele, Ph.D.
Baylor College of Medicine |
Scott Fraser, Ph.D.
California Institute of Technology |
Jeffrey M. Friedman, M.D., Ph.D.
The Rockefeller University |
Fred H. Gage, Ph.D.
The Salk Institute for Biological Studies |
Paul Greengard, Ph.D.
The Rockefeller University |
Bruce Hamilton, Ph.D.
University of California, San Diego, School of Medicine |
Mary-Beth Hatten, Ph.D.
The Rockefeller University |
Nathaniel Heintz, Ph.D.
The Rockefeller University |
Ali Hemmati-Brivanlou, Ph.D.
The Rockefeller University |
RenŽ Hen, Ph.D.
Columbia University College of Physicians and Surgeons |
Tom Jessell, Ph.D.
Columbia University College of Physicians and Surgeons |
Alexandra L. Joyner, Ph.D.
New York University Medical Center |
Eric Kandel, M.D.
Columbia University College of Physicians and Surgeons |
Larry Katz, Ph.D.
Duke University Medical Center |
Stuart Kim, Ph.D.
Stanford University School Of Medicine |
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Alex Kolodkin, Ph.D.
Johns Hopkins University
School of Medicine |
George Lake, Ph.D.
Institute for Systems Biology, Seattle |
Pat R. Levitt, Ph.D.
University of Pittsburgh School of Medicine |
David Lockhart, Ph.D.
The Salk Institute for Biological Studies |
Robert C. Malenka, M.D. Ph.D.
Stanford University School of Medicine |
Susan K. McConnell, Ph.D.
Stanford University |
Dennis O'Leary, Ph.D.
The Salk Institute for Biological Studies |
John Rubenstein, M.D., Ph.D.
University of California, San Francisco |
Edward Scolnick, M.D.
Merck Research Laboratories |
Lubert Stryer, M.D.
Stanford University |
Michael P. Stryker, Ph.D.
University of California, San Francisco |
Joseph S. Takahashni, Ph.D.
Northwestern University |
Marc Tessier-Lavigne, Ph.D.
Stanford University |
Roger Y. Tsien, Ph.D.
University of California, San Diego |
Arthur Toga, Ph.D.
University of California, Los Angeles |
Kamil Ugurbil, Ph.D.
University of Minnesota |
Chris A. Walsh, M.D., Ph.D.
Harvard Medical School
BIDMC Room 816
Harvard Institutes of Medicine |
Richard Woychick, Ph.D.
Lynx Therapeutics, Inc. |
Charles Zuker, Ph.D.
University of California, San Diego |
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NIH Program Staff |
James Battey, M.D., Ph.D.
National Institute of Deafness and Other Communication Disorders |
Robert Baughman, Ph.D.
National Institute of Neurological Disorders and Stroke |
Hemin Chin, Ph.D.
National Institute of Mental Health |
Stephen Foote, Ph.D.
National Institute of Mental Health |
Glen Hanson, Ph.D., D.D.S.
National Institute on Drug Abuse |
Michael Huerta, Ph.D.
National Institute of Mental Health |
Michael Iadorola, Ph.D.
National Institute on Dental and Craniofacial Research |
Gabrielle Leblanc, Ph.D.
National Institute of Neurological Disorders and Stroke |
Steven O. Moldin, Ph.D.
National Institute of Mental Health |
Bret Peterson, Ph.D.
National Center for Research Resources |
Jonathan Pollock, Ph.D.
National Institute on Drug Abuse |
Brad Wise, Ph.D.
National Institute on Aging |
Graeme Wistow, Ph.D.
National Eye Institute |
Observer |
John H. Williams, Ph.D.
The Wellcome Trust |
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Table 2: Enabling Reagents and Datasets
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A dataset of full-length transcripts/cDNAs expressed in the
nervous system; this dataset is well on its way to completion.
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A bank of Bacterial Artificial Chromosomes that permit transgenic
labeling and manipulation of major neuronal populations in the
mouse brain; only a few hundred of these exist today.
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A bank of short promoter elements for extending such manipulations
to primates and other non-genetic systems; few of these exist
at present.
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A set of antibody probes (for immunohistochemistry) that help
extend and leverage the Molecular Brain Map. A priority is the
generation of antibodies to the ~1,500 transcription factors
encoded in the genome, to help identify neuronal cell types
and stem cells; only a small fraction (~10%) of these exist
at present
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Table 3: Complementary Technologies
Short term:
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Improved methods for isolation of high-quality mRNA from small
numbers of neurons, including laser-capturing of mRNA from neurons
identified through expression of a transgenic reporter (such
as GFP), and for faithful linear amplification of cDNA from
the mRNA for gene expression analysis
Medium term and longer term:
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Improved methods for mapping neuronal circuits (identifying
all inputs to each neuron and all outputs from each neuron)
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Methods for detecting electrical activity in mammalian neurons
by optical recording using genetically-encoded reporters
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Methods for controlling activity in defined neurons, in particular
genetically-encoded modulators of electrical activity that can
be activated with specific signals such as pharmacological agents
or light
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Methods for detecting neuronal activity in deep brain structures
using such genetically-encoded reporters
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Methods for mapping patterns of neuronal activity onto patterns
of gene expression and neuronal interconnectivity
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Methods for persistent labeling of neurons over time, to follow
plastic changes in morphology, connections, or function
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Methods for visualizing changes in neuronal connections, such
as pulse-chase labeling of synaps
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Part II: Background: Gene-Based and Cell-Based Approaches
to Creating a Map
- Historical background
Using histological tools like the Golgi staining method, neuroanatomists
in the late 19th and early 20th centuries defined hundreds of different
neuronal cell types based on their location in the brain, morphology,
and connectivity. Throughout the 20th century, this number grew, and
neuroscientists were also able to assign particular physiological functions
to a large number of these neuronal types and many of the circuits linking
these cells. At present, the number of distinct neuronal cell types
is not precisely known, but it is estimated that there must be at least
several thousand. This estimate is supported by the finding of novel
subclasses whenever a particular population of neurons is studied in
detail. For example, a recent assessment of amacrine cells subtypes
in the retina, previously thought to number about a dozen, revealed
the existence of more than thirty easily definable subtypes. These thousands
of cell types, through their specific patterns of interconnections,
direct the functioning of the brain.
Subpopulations of neurons are increasingly being distinguished based
on their pattern of gene expression. Historically, molecular neuroanatomy
started with cellular pharmacology Ð the definition of the neurotransmitters
and neurotransmitter receptors made by particular neurons, using a variety
of physiological, in situ radioligand binding, and histochemical methods.
The development of the technique of immunohistochemistry accelerated
the mapping of proteins (such as neuropeptides) and other epitopes (such
as specific carbohydrate moieties) to particular neurons in cases where
a suitable antibody was available. However, it is the development of
sensitive and reproducible mRNA in situ hybridization techniques that
unleashed the systematic analysis of gene expression in neurons, because
this approach can be readily applied to all genes without requiring
the labor-intensive development of specific detection reagents (such
as antibodies); in all cases, a small gene fragment is sufficient to
develop an appropriate in situ hybridization probe. In situ hybridization
methods have been supplemented by transgenic (promoter-based, and BAC-based)
and knock-in approaches, which make it possible to visualize the pattern
of expression of particular genes using genetically encoded reporters
driven from the gene locus in transgenic mouse lines. (These approaches
are explained further below).
- Gene- (and Gene Product-) Based VS. Cell- (and Region-) Based Approaches
to Gene Expression Profiling
Existing powerful methods for mapping gene and gene product expression
are summarized in Table 4, and are divided into gene- (and gene product)
based and cell- (and region) based approaches. In situ hybridization
is an example of a gene-based method for gene expression analysis.
Such methods make it possible to detect a single gene product (e.g.
a particular mRNA) in a very large number of cells in brain slices.
A complementary approach is, however, provided by cell- (and region-)
based methods of analysis. Such methods involve isolating small
brain regions or, in the limit, specific neuronal populations or even
single cells, extracting mRNA from these cells, and subjecting them
to gene expression analysis using DNA arrays or other methods (such
as direct cDNA library sequencing). These methods make it possible to
detect a very large number (thousands) of gene products in a small number
of cells.
Table 4: Methods to Map Genes and Gene Products to Neurons
- Gene- (and Gene-Product) Based:
Method |
Limitations/Limiting Steps |
Current Applicability |
Histochemical
Radioligand binding
Immunohistochemistry
Transgenic: promoter-based
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Requires optimized stain
Requires optimized ligand
Requires antibodies
Requires promoters
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Current Applicability
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Transgenic: BAC-based or knock-in
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Limited by generation of constructs, ES cells, mice
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Hundreds to thousands of genes
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In situ hybridization
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Limited by tissue sectioning
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Thousands to tens of thousands of genes
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- Cell- (and Region) Based:
Methods for isolating cells and mRNA:
Dissection (for small or large region)
Cell marking and purification (e.g. by Fluorescence Activated
Cell Sorting)
Single cell picking
Laser-capture microdissection
Methods for analyzing gene expression
DNA arrays
cDNA library sequencing
Other (SAGE, MPSS, etc.)
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Gene-based and cell-based approaches are complementary, with different
advantages and disadvantages.
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Gene- (and gene-product) based approaches have the advantage
of providing a broad overview of any particular gene throughout
the brain. Of these methods, in situ hybridization has the highest
throughput. Its disadvantage can be limited cellular resolution,
particularly since only the cell body (or part of the cell body)
is labeled. In some instances, it is possible to tell within different
brain regions exactly which cells are expressing the gene, for
example when the gene is found in cells with a particular morphological
feature (such as a large cell body) that makes it possible to
distinguish them from other cells in the vicinity. In many cases,
however, it is not possible to assign the expressed gene to a
specific cell. As a consequence, when comparing two different
genes expressed in the same region, it is often not possible to
know whether the two are expressed by the same or different cells,
unless the expression analysis is performed simultaneously with
two probes that can be visualized independently (e.g. using two
fluorescent tags). Such double-labeling technologies are being
improved but are still limiting at present. Better cellular resolution
can be obtained by other gene- or gene-product based methods that
result in labeling of the neuron's processes, since shape and
connectivity often identify particular neurons. This can be achieved,
for instance, with transgenic approaches discussed in the next
section. Thus, although such approaches have a lower-throughput
than in situ hybridization, they help provide greater resolution.
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Cell- (and region-) based approaches have a complementary
set of advantages and disadvantages. In these approaches, the
entire pattern of genes expressed by a particular cell (or population
of like cells) can be identified by extracting mRNA from the cell(s)
and subjecting it to analysis using DNA arrays (or through some
other method such as direct cDNA library sequencing). These technologies
make it possible to determine the expression profile of a small
number of cells, and in some cases, even a single cell. What limits
these approaches is the difficulty of obtaining mRNA from just
the cells of interest. In experimental animals such as mice, specific
neuronal populations can often be isolated and purified (see below)
and used as a source of mRNA, but this approach is of limited
utility in the human brain. An alternative method is laser capture
microdissection, in which mRNA is directly isolated from specific
cells identified in fixed brain sections. Laser-capture is thus
more applicable to human tissue, but the method is still being
perfected (for instance, the captured mRNA can be degraded, a
technical problem that is likely to be resolved before long).
It is also limited by the ability to identify the neurons of interest
in tissue sections (discussed in more detail below).
Thus, gene-based approaches give broad coverage of all brain regions
but often with more limited cellular resolution. Cell-based approaches
can provide high cellular resolution and give information on the complete
set of transcripts expressed by a cell, but their throughput is lower
and they are more difficult to apply to the human brain. Both types
of approaches are needed.
- Tools to Deliver Genes to Particular Neurons Facilitate Cell-Based
Approaches
The utility of cell-based approaches is limited by the ability to isolate
and to purify particular neuronal populations (for approaches based
on cell isolation), or to recognize particular populations in tissue
sections (in the case of laser capture microdissection). Some select
populations of neurons can be purified based on physical characteristics,
such as size, through the use of probes (such as antibodies) directed
against particular cell surface epitopes, or by using fluorescent markers
injected into the termination sites of the neurons' axons, which are
taken up by the axons and retrogradely transported. However, these approaches
are currently applicable only to small numbers of neurons.
More general approaches to isolating particular populations of neurons
involve transgenic approaches in which expression of a genetically-encoded
reporter, such as the Green Fluorescent Protein (GFP) or some other
molecular tag is driven in the neurons of interest in transgenic mice.
The neurons can then be recognized and purified by some other method
that makes use of the reporter tag, e.g. by Fluorescence Activated Cell
Sorting using GFP fluorescence. (In principle, the molecular tagging
of neurons should also permit their identification in tissue sections
for laser-capture microdissection; current laser-capture methods are
not readily compatible with such molecular tagging, although it can
be expected that this technical problem will be solved before long).
The transgenic labeling approaches require the ability to drive reporter
expression in the cells. This is usually done by first identifying a
particular marker gene expressed in the neurons of interest; the marker
must be specific for those cells - at least in a particular region of
brain that can be isolated through dissection from any other regions
where the marker is expressed. Once an adequate marker gene is identified,
the generation of a transgenic mouse in which the reporter is expressed
from the marker gene locus is currently achieved primarily by three
methods.
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Short promoters. In the case of some marker genes, it is
possible to isolate a promoter element (stretch of DNA) that directs
expression of the reporter. One disadvantage of this approach is
that it is often labor-intensive and difficult to identify the promoter.
Another is that it can often be difficult to isolate a transgenic
mouse line in which the reporter, driven by the promoter, gives
faithful expression, because of position effects on integration
of the reporter construct in the host genome. One advantage, however,
is that small promoters can be used in viral delivery systems, which
can be used more readily in organisms other than mice (including
primates).
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Bacterial Artificial Chromosomes (BACs). As an alternative,
large (>50kB) bacterial artificial chromosomes (BACs) containing
the gene of interest as well as its control regions can be modified
to drive expression of a reporter construct in a pattern that mirrors
that of the starting gene when reintroduced into transgenic animals.
BACs have the disadvantage that they are too large for use in viral
vectors. However, in transgenic mice, BACs have some advantages
over small promoter elements: they are readily isolated, can contain
all the gene regulatory elements, and because of their size are
usually less subject to position effects on integration. In principle,
BACs can also be used in other species that are amenable to the
generation of transgenic animals (such as rats).
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Knock-ins. Another means of delivering reporters to particular
cell types is through knock-in technology in mice. In this approach,
a reporter is introduced into a particular marker gene locus by
homologous recombination in embryonic stem (ES) cells, and transgenic
mice are generated from the ES cells. This approach is applicable
only in species where knock-ins are possible, primarily mice. One
advantage of this over other transgenic approaches is that the marker
gene can be inactivated during the procedure, so that gene function
can be assessed. Traditionally, a disadvantage has been that making
knock-ins has been labor intensive, but this has been improving.
The ability to deliver constructs selectively to particular neuronal
populations is so important to generating and exploiting a Molecular
Brain Map that a high priority should be assigned to generating the
tools (such as BACs and promoter elements) that will make this possible
(Table 2).
- Tools to deliver genes to particular neuronal populations facilitate
tracing neuronal connections, and monitoring and manipulating neuronal
function
In addition to allowing the marking and isolation of particular populations
of neurons, these tools make it possible to deliver other transgenic
constructs to the neurons, which facilitates identifying patterns of
neuronal connections, and monitoring and manipulating electrical activity,
and manipulating neuronal function.
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Mapping connectivity. Traditionally, the connections a neuron
makes have been identified using electrophysiological recordings,
from histochemical techniques (such as the Golgi technique), or
through the use of anterograde or retrograde tracers (such as Horseradish
Peroxidase (HRP)) that make it possible visualize the patterns of
projections of individual neurons. These methods are laborious and
in many cases applicable only to small populations of cells. The
ability to drive expression of reporter genes in particular neuronal
populations makes it possible to readily trace their connections
by delivering genetically encoded reporters of neuronal projections
provided by proteins such as beta-galactosidase, alkaline phosphatase
or GFP (or modified versions of such proteins that are readily transported
down axons), which allow simple histochemical or fluorescent labeling
of axons of neurons making the reporter. In addition, much effort
is currently being devoted to devising genetically-encoded tracers
that are transported across synapses and hence permit transsynaptic
tracing of connections, both anterogradely and retrogradely, allowing
patterns of connectivity to be defined.
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Monitoring and manipulating neuronal activity. The labeling
of specific neuronal populations with genetically encoded fluorescent
markers like GFP makes it possible to identify these neurons in
slices or cultures of brain tissue, allowing for electrical recordings
with microelectrodes on these neurons. Potentially even more powerful
are genetically encoded reporters of electrical activity. At present,
indirect measures of electrical activity can be obtained with genetically
encoded reporters of cellular properties like intracellular calcium
concentration that can serve as indirect measures of electrical
activity. Proteins whose optical properties change with membrane
potential have been devised that can be used to monitor electrical
activity of model cells such as frog oocytes; the extension of this
technology to create similar proteins that can function in mammalian
neurons would make it possible to monitor electrical activity of
neurons through optical recording after delivery to these neurons
using the approaches described above. Similarly, genetically encoded
modulators of neuronal activity, such as particular ion channels
that can be opened or closed through use of pharmacological agents
or other means (e.g. by light stimulation), when delivered to particular
neuronal populations, provide tools to control neuronal activity
and thereby to assess neuronal function.
There are significant limitations on existing genetically encoded constructs
for tracing connections and monitoring and manipulating neuronal activity,
so that exploiting the Molecular Brain Map fully will require improving
both sets of technologies (Table 3).
Part III: Requirements of a Molecular Brain Map
With this background, we now discuss what needs to be discovered.
- A Molecular Map of the Adult Mouse Brain
We first discuss the challenges involved in establishing a Molecular
Brain Map for the normal adult mouse brain. We focus on the mouse because
its brain is highly analogous in structure and organization to the human
brain, but at the same time it is readily amenable to manipulation of
gene activity and function in a manner not yet possible in species more
closely related to humans. These properties have made the mouse the
key model organism for molecular studies of brain function and dysfunction,
and there was consensus at the workshop on the need to give highest
priority to generating a mouse Map.
A comprehensive Molecular Brain Map should provide the pattern of expression
of all genes in all neurons throughout the brain, and involves the following
component parts.
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Mapping all genes and splice variants. The existing Genome
Projects are in the process of completing the cataloguing of the
more than 30,000 genes in the genomes of the human and the mouse.
In the first instance, it will be important to describe the expression
of all these genes. A further complexity arises from the fact that
many genes are subject to alternative splicing, which can often
alter the function of gene products. This splicing is often poorly
understood. Ultimately, a comprehensive Map should incorporate information
on the specific splice variants for each gene that are expressed
by each neuron.
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Devising an Atlas of the brain onto which information can be
mapped. The enormous amount of information generated through
expression analysis will be of general utility only if it can be
organized in a way that makes it easily accessible by the community
of researchers. In practice, this means that the information must
be mapped onto a standard brain atlas, in which neuronal populations
are assigned particular coordinates. There are of course variations
in brain size and structure among individuals in any given species,
so that any atlas will be at best an idealization. It will be the
most accurate in the case of inbred strains of animals, such as
mice, that show the least variation between individuals. Efforts
have been made in the past decade to develop such atlases for mice
and other species, including humans.
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Integrating information obtained from gene-based and cell- (or
region) based approaches. As discussed above, gene-based approaches
such as in situ hybridization permit the mapping of all genes, but
the degree of cellular resolution is limited. Cell-based approaches
make it possible to define for particular cells the full complete
of genes that are expressed, but this must be done on a laborious
cell-by-cell basis. The two approaches are complementary, making
it desirable to use both, and to cross-reference the information
obtained by the two approaches.
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Mapping circuits as well as cells. Understanding the pattern
of interconnections of specific neural cells is essential to understanding
their roles in nervous system function and dysfunction. Therefore,
a comprehensive Brain Map should include not just information about
the patterns of gene expression of cells, but also about the connections
those cells make with other neural cells. The identification of
genes that can serve as markers for particular cell types, and whose
promoters can be used to drive cell-type specific expression of
transgenes, can help trace the connections of these cells, through
the transgenic expression in the cells of genetically encoded markers
of neural connectivity. A powerful variation on this theme, recently
developed, involves driving in the cells not the genetically encoded
marker itself, but rather a recombinase like cre that makes it possible
to activate a genetically encoded reporter delivered to the cells
by other means (e.g. using a virus). Technologies like these have
the potential to dramatically facilitate the tracing of connections
in the complex environment of the brain. While this type of tracing
has been initiated in an investigator-initiated way in several laboratories,
there is at present no systematic effort to accelerate the development
of a Connectivity Map; this should be given priority.
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Mapping proteins not just mRNAs. For technical reasons mentioned
above, the analysis of mRNA expression patterns is considerably
more straightforward than the analysis of the expression patterns
of their protein products, so that highest priority is being given
to high-throughput mRNA expression analysis. Ultimately, however,
it will be necessary to know cell type-specific expression patterns
of protein products and their subcellular localization on particular
portions of neurons or in specific intracellular compartments. The
improvement of proteomic methods is the focus of intense activity
in all areas of biomedical research, and these methods should be
incorporated into the generation of Molecular Brain Maps in an ongoing
way as they are developed.
One specific initiative in proteomics deserves mention and high priority
at this time: the generation of antibodies to transcription factors.
It is estimated that there are approximately 1,500 transcription factors
encoded in the genome. The identity of particular neural cell types
is controlled by combinatorial expression of specific transcription
factors, and the availability of antibody probes to detect transcription
factors in histological sections of the brain will accelerate attempts
to identify neural cells, including neural stem cells, and to devise
means to alter the development and fate of these cells for neural repair.
Furthermore, transcription factors as a class have proven in general
to be readily amenable to the generation antibodies that work in immunohistochemistry,
whereas many other important classes of proteins (e.g. G protein-coupled
receptors) are often more refractory. The combination of importance
and ease justifies giving priority to the generation of antibodies to
transcription factors (Table 2).
From this description, it is evident that the development of a comprehensive
Molecular Brain Map will be an iterative process, as information
from gene-based and cell-based approaches accumulates and is incorporated
into an ever more refined Atlas incorporating information not just about
the locations of cells but also about their interconnectivity and function.
In particular, it can be expected that in many cases what is thought
of as a single homogeneous class of neurons defined by expression of
a particular maker gene will, on further analysis, be discovered to
comprise two or more subpopulations. Such refinements, subdivisions
and reinterpretations are expected, and will be facilitated by the integration
of information obtained from gene-based and cell-based approaches, and
the integration of that information with other anatomical and functional
data. As part of this refinement process, more accurate cell-type specific
markers are likely to be defined that will permit gene manipulation
in particular populations of neurons with high selectivity.
- Three axes: species, developmental stage, and disease condition
A single Molecular Brain Map of the adult mouse brain would already
provide an invaluable tool, dramatically accelerating the pace of discovery
by freeing individual investigators of the need to derive the information
in a piecemeal and inefficient way. However, the full utility of the
Map will be evident only as a variety of Maps are generated to document
gene expression in different species, developmental stages, and disease
conditions.
-
Maps in different species. Just as important as the creation
of a Molecular Brain Map for the mouse is the creation of such a
map for the adult human brain. A number of approaches feasible in
the mouse are not possible in the human (e.g. those of a transgenic
nature), but in situ hybridization (gene-based) and laser-capture
microdissection (cell-based) are both possible. Thus, it should
be possible to generate such a Map for humans, though these limitations
in mapping technologies appropriate for the human brain, as well
as the variation in brain size and structure alluded to above, will
result in the generation of a lower-resolution Map, at least in
the first instance. After humans, a Molecular Map for the brain
of one or more non-human primates (whose genomes have been sequenced)
will be desirable, as primates can be excellent models for a variety
of higher brain functions that are either not present or not easily
studied in the mouse.
-
Maps at different developmental stages. Understanding how
the adult brain is generated during development will require creating
Maps at different stages in embryonic, fetal, and early postnatal
life. One or more Embryonic and Fetal Maps will help identify the
genes responsible for the generation and differentiation of neuronal
cells, as well as the genes important in establishing the initial
connectivity of the brain. One or more Postnatal Maps will help
elucidate mechanisms through which early sensory experience helps
shape the ultimate pattern of neuronal connections. High resolution
Maps at these stages will be most useful.
-
Maps in different states (disease, drug-treatment, injury, or
diverse normal physiological states) and strains. Important
clues to the causes of disease will come from generating Maps in
different disease states in both animal models such as the mouse,
and also in humans. Comparing Maps in different strains of the same
animal (e.g. different mouse or rat strains) that show significant
behavioral or physiological differences can similarly be expected
to shed light on the causes of these differences. Similarly, insight
into both drug mechanisms and some disease states will be obtained
by generating Maps following drug treatment, especially for those
drugs, such as anti-depressants, that require considerable time
to achieve their effects (and which therefore likely involve changes
in gene expression). Maps generated following injury or trauma to
the nervous system will provide information on the brain's response
to these insults, including on the behavior of stem cells, and changes
in gene expression that may either facilitate or impede regenerative
responses. Finally, even in the normal, uninjured brain, the generation
of different Maps is likely to be useful, for example in discerning
changes in gene expression that occur in particular learning paradigms.
In general, for each of these stages it is anticipated that low
resolution Maps might be generated in the first instance, with subsequent
high resolution mapping of particular brain regions fingered by
the first-pass analysis.
Part IV: Existing Large Scale Efforts Funded by
the NIH
The NIH recognized the need for a Molecular Brain Map in the 1990s. Many
pilot efforts have been funded to further the development of this Map,
and are not described here because of space constraints. Three large-scale
efforts funded at high levels by various Institutes of the NIH are, however,
discussed in detail in Appendix 1 and introduced briefly here.
- Creating a dataset of all transcripts expressed in the adult and
developing mouse brain, and a physical collection of cDNA probes for
each of these transcripts.
This resource and dataset, created by Dr. Bento Soares (University
of Iowa) complements the Genome Projects in helping identify transcripts
and splice-variants of genes expressed in the brain, and in generating
cDNA libraries and full-length cDNA/EST probes that can facilitate analysis
of these genes.
- Creating a database of gene expression patterns in the nervous system
The GENSAT project, initiated by Drs. Gabrielle Leblanc, Bob Baughman,
and colleagues at NINDS, aims to systematically map the expression patterns
of thousands of genes in histological sections of the mouse brain and
spinal cord in the adult and at three stages of development (E10.5,
E15.5, and P7). The gene expression data are being collected by two
groups of investigators, one led by Dr. Gregor Eichele (Baylor College
of Medicine and Max Planck Institute, Hannover), and another led by
Drs. Nathaniel Heintz, Mary-Beth Hatten (Rockefeller University) and
Alexandra Joyner (New York University). Dr. Eichele's group is collecting
data using high throughput in situ hybridization, whereas Dr. Heintz's
group is using BAC (bacterial artificial chromosome) transgenic technology.
In the latter approach, transgenic mouse lines are generated in which
expression of a reporter, Green Fluorescent Protein (GFP) is driven
in the same patterns as selected genes. The gene expression data from
both efforts is to be placed in a public database at the National Center
for Biotechnology Information (NCBI). The project is collecting data
for 300 genes in its first year, and aims to ramp up to at least a thousand
genes per year in future years.
- Creating Atlases of the mouse and human brains
Dr. Arthur Toga of the University of California at Los Angeles and
his colleagues have been developing computerized brain Atlases, and
tools to map data obtained from gene expression analysis or other approaches
(e.g. functional MRI) onto those Atlases. In the case of the mouse,
the result is a formal computerized representation of the mouse brain,
providing coordinates that define the diverse anatomical structures
and landmarks.
These projects are helping set the groundwork for accelerating the
generation of comprehensive Molecular Brain Maps for the human and the
mouse.
Part V: Goals and Priorities
The working group applauded existing large-scale efforts for the establishment
of a Molecular Brain Map, and achieved broad consensus on the following
priorities going forward, building on those initial efforts.
- A two-pronged approach: breadth and depth
-
Breadth: A first priority is to accelerate efforts like
those just mentioned to provide a broad but comprehensive survey
of expression of all genes in the adult mouse and human brains.
Achieving this goal involves several challenges.
-
Increased throughput. The current throughput of existing
efforts in the mouse is on the order of many hundreds of genes
a year. To deal with the more than 30,000 genes in the mammalian
genome in a matter of years rather than decades, it will therefore
be necessary to increase this throughput by an order of magnitude
at least.
-
Integrating and coordinating gene-based and cell-based approaches.
At present the highest throughput is provided by in situ hybridization
(a gene-based approach). Because of its limited cellular resolution,
however, it is necessary to pursue complementary approaches with
equal vigor. This includes transgenic approaches, such
as BAC-mediated or knock-in approaches, which are of lower throughput
but provide more detailed cellular resolution data on expression
of particular genes, and also provide tools to label particular
neuronal populations for cell-based approaches. Cell-based approaches,
in which mRNA is extracted from particular cells and probed (e.g.
using DNA arrays) to identify the transcript profile of
the cells, must also be pursued vigorously. In particular, laser-capture
microdissection holds high promise, particularly for use on
human tissue, but the technique needs to be improved significantly
(e.g. to improve the quality of recovered mRNA, and to permit
capture from marked cells). These efforts will all benefit from
coordination: for instance, in selecting genes for in situ
hybridization and BAC transgenic analysis a priority should be
given to identifying regional- and cell-type specific markers
that can then be used for cell-based approaches.
-
Broaden to include circuitry. An essential part of a Molecular
Brain Map will be information on the pattern of connections made
by individual neuronal populations. Mapping connectivity
has not been a focus of large-scale efforts to date, and should
become an integral part of such efforts.
-
Competition between centers and technologies. Since the
methods for most efficiently collecting information about gene
expression are still being worked out, it was deemed essential
to encourage competition between multiple centers and multiple
approaches.
-
Depth: A second priority is to focus in detail on a few
selected brain regions and/or functional circuits (such as the
retina, spinal cord, or cerebellum). The aim here is to characterize
in detail all the neuronal subtypes in the selected circuits, defining
not just their full complement of gene expression but also their
interconnectivity. These data would then be related to the functional
properties of the system. The reason for focusing on a few systems
in depth is that this would make it possible to discern whether
any organizational or analytic principles emerge relating
gene expression patterns to the structure and function of the circuit.
Such principles could then help guide and organize similar studies
in other brain regions.
- How many Maps?
-
The adult mouse brain will continue to be the first focus
of efforts to create a Molecular Brain Map, because of its relevance
to the human brain, and the powerful transgenic tools that facilitate
Map generation. It was deemed important, however, to initiate the
creation of additional Maps.
-
Priority should also be given to generating a Molecular Brain Map
for the adult human brain, despite the difficulty of obtaining
high quality post-mortem human brain tissue for mapping studies,
and the fact that transgenic approaches are not possible. These
limitations mean that the generation of this Map will lag behind
that of the mouse and have lower resolution, at least initially.
Nonetheless, given its central position in the analysis of behavior
and in biomedical research, even a limited Map for the human brain
will have broad utility.
-
It is likely to be desirable to generate several other Maps. Strong
arguments in the first instance can be made for the broad importance
of several Maps of the developing mouse brain (to illuminate
brain development and plasticity), and a Map of another adult
primate species (which will be more experimentally tractable
than the human brain, and closer in structure and function than
the mouse brain).
-
Yet other Maps are likely be important, but different constituencies
of basic and clinical researchers are likely to have different priorities.
In many cases, partial Maps may be sufficient. For example,
illuminating some neurological diseases may be achieved by focusing
mapping efforts on subregions of the brain or even particular neuronal
populations in either a mouse model of the disease or on post-mortem
human brain tissue.
- Need for a versatile repository for data
To be truly useful, the data generated by these approaches must be
organized into a central data repository that is easily accessible to
the community Ð the ÒGenbankÓ equivalent for brain gene expression.
All data must be mapped onto a digital brain Atlas, accessible
through graphical interfaces, that can integrate data from both quantitative
gene expression analysis (such as that provided from DNA arrays) with
histochemical data (immunostaining, in situ hybridization), and which
is accessible for Òwhere isÓ and Òwhat is inÓ queries. The format must
be user-friendly and make it straightforward for researchers
who are focusing on a particular brain region (for instance, researchers
interested in a particular region because of fMRI data implicating it
in some cognitive task) to obtain clues to the function of the region
from the data contained within the Map.
- Need for standards
The development of this database will require the establishment of
standards for the organization and display of data, as well as
standards for data collection that are compatible with the digital
atlas framework of the database. The absence of such standards is severely
limiting the utility of data that are already being generated by existing
large-scale efforts. Various Institutes at the NIH have initiated discussions
on setting these standards, and they should be encouraged to drive this
process to completion as rapidly as possible, broadly involving the
community in the process.
- Public access is essential
The full impact of a Molecular Brain Map will be felt only if all data
in the database is accessible to the scientific community at large.
Standards for the timing of public release of data therefore
need to be defined and implemented. Early release of data, for example
on a quarterly basis or more frequently, is essential both to ensure
access and to ensure quality control by the community. For example,
data generated in large-scale efforts funded by NIH and described in
Part IV should be released to the scientific community according to
these standards.
- Need for tools to leverage and extend the Molecular Brain Map
There was consensus on the need to develop novel technologies to allow
the Molecular Brain Map to be leveraged to its fullest.
The first priority is to develop a bank of specific promoters and
modified BACs, to permit delivery of transgenes to specific neuronal
populations, and the simultaneous improvement of efficient transgenic
and/or viral delivery methods for gene delivery in species other
than mouse (including rats and primates).
The impact of having this bank will be greatly increased by the further
development of genetically encoded reporter and modulator constructs
to allow: (i) the marking and isolation of neurons, (ii) the
tracing of all connections made by a neuron, (iii) the persistent
or time-lapse labeling of connections, to help identify plastic
changes in connections (iv) the detection of electrical activity
in neurons by optical and other means, and (v) the controlled
modulation of electrical activity in specific neuronal populations
(e.g. by expression of an ion channel that can be gated by a specific
pharmacological agent or by light). The latter two applications in particular
will help define the function of particular neurons and neuronal circuits.
Finally, whereas the analysis of gene transcripts (mRNAs) in neurons
is amenable to high-throughut analysis today and hence should be the
initial focus of effects to construct Molecular Brain Maps, the characterization
of protein products and their subcellular localization, i.e. the proteomic
characterization of neurons, is an essential longer term goal that
will rely on improvements in proteomic analysis methods throughout the
biomedical community. As discussed, one proteomic initiative that deserves
priority at this time is the generation of antibodies to transcription
factors.
These tools, reagents and methods are summarized in Tables 2 and 3.
- Need for organization and coordination
The successful development of a Molecular Brain Map will require a
concerted and large-scale effort. It is therefore imperative that an
ongoing Working Group be established, comprising members of the
scientific community as well as granting agencies, to monitor developments
and continually define and refine priorities for molecular neuroanatomy.
- Need for both coordinated large-scale projects and investigator-initiated
projects
The collection of initiatives required to generate and leverage a series
of Molecular Brain Maps require a mix of funding initiatives. Some aspects,
such as the high throughput generation, collection, and collation of
gene expression data, will benefit greatly from large-scale integrated
funding initiatives. Others, such as the development of tools to leverage
the Molecular Brain Maps, will continue to benefit from smaller-scale
individual investigator initiated projects. Both types of funding initiatives
should be supported by the NIH.
Appendix 1: Existing Large-Scale Efforts
Various institutes at the NIH recognized the need for a Molecular Brain
Map in the 1990s. Many small-scale efforts have been funded to further
the development of this Map, and are not described here in the interests
of space. Several large-scale efforts funded at high levels by various
Institutes of the NIH are, however, discussed.
- Creating a dataset of all transcripts expressed in the adult and
developing mouse brain, and a physical collection of cDNA probes for
each of these transcripts.
Under contract to the NIMH, Dr. Bento Soares (University of Iowa) has
undertaken the generation of cDNA libraries from mouse brain regions,
and the direct sequencing of cDNAs from these libraries, in an effort
to identify all transcripts expressed in the brain. In phase I, completed
in the year 2000, a non-redundant collection comprising approximately
30,000 brain and 9,000 retina cDNAs/ESTs was identified, re-arrayed,
sequence verified and made publicly available. In phase II, initiated
in September 2001, cDNA libraries enriched in full-length transcripts
are being generated from whole brain and eyes at various developmental
stages, and sequenced.
The identification of all transcripts has, of course, been greatly
accelerated by the sequencing of the human and mouse genomes. Dr. Soares's
project was initiated before it was clear how long the sequencing of
the human and mouse genomes would take. It still remains complementary
to the genome sequencing projects in important ways. First, programs
for identifying individual genes from genomic sequence remain imperfect,
so that cDNA sequencing efforts continue to provide valuable information
on the identity of individual genes. Second, direct sequencing of cDNAs
also provides important information on the usage of alternative exons
of particular genes (alternative splicing and promoter usage) that is
not always easily inferred from genomic sequence. Finally, the project
also provides a physical series of cDNA probes for each of the genes
that is identified.
- Mapping gene expression
-
Mapping gene expression through high-throughput in situ hybridization
As part of NINDS's GENSAT project, Dr. Gregor Eichele (Baylor College
and Max Planck Institute, Hannover) and his colleagues have undertaken
an effort to map gene expression through high-throughput in situ hybridization.
This has involved the development of a robot for performing reproducible
in situ hybridization analysis on sections of adult or embryonic brain,
which will in the first instance provide a collection of brain sections
on microscope slides on which the pattern of expression of individual
genes is visualized with a histochemical reaction product. The aim
of the project, in the first instance, is to map expression of over
one thousand genes per year to the adult mouse brain and the developing
brain (at E10.5, E15.5, and P7)
-
Mapping gene expression through generation of BAC transgenic mice
Also under the auspices of NINDS's GENSAT project, a consortium
of Dr. Nathaniel Heinz, Dr. Mary-Beth Hatten and Dr. Alex Joyner (Rockefeller
University and New York University) and their colleagues has undertaken
to use BAC (bacterial artificial chromosome) transgenic technology
to map gene expression in the brain. In this approach, for each gene
a transgenic mouse is generated in which the reporter GFP (green fluorescent
protein) is expressed in a pattern mimicking that of the starting
gene. This is achieved by isolating a bacterial artificial chromosome
(BAC) containing the gene locus of interest (including its regulatory
regions), recombining a GFP cDNA into the locus, and creating a transgenic
mouse containing the modified BAC. At high frequency, expression of
GFP in such mice is representative of expression of the endogenous
gene. The aim of the project is to ramp up to the production of about
a thousand modified BACs per year, which are then used to generate
transgenic mouse lines, followed by visualization of GFP in a select
series of sections from adult brains, and collection of images with
this information. This approach is complementary to the in situ hybridization
approach in (a). It is slower to make the modified BACs and transgenic
mouse lines than simply to perform in situ hybridization. However,
the GFP signal, unlike the in situ hybridization signal, can often
give more information on the particular cell type expressing the gene
because the morphology of the cell and its pattern of projections
often provides a unique identifier of the cell. In addition, the modified
BAC construct in principle provides a valuable tool that can be used
by other investigators in transgenic mouse lines to mark cells expressing
the gene or to deliver other gene-modifying constructs to those cells
for functional studies in transgenic mice.
-
Creation of Atlases of the mouse and human brains
Under a grant supported by NIMH, NINDS, NIDA, NIA, NIAAA, and NIDCD,
Dr. Arthur Toga of the University of California at Los Angeles, Dr.
Russell Jacobs at the California Institute of Technology, Dr. Larry
Swanson of the University of Southern California, and their colleagues,
have been developing computerized brain Atlases and tools to map data
obtained from gene expression analysis or other approaches (e.g. connectional
data, structural or functional MRI data, immunocytochemical data,
chemo- or cytoarchitectural data, etc. ) onto those Atlases. In the
case of the mouse, the result is a formal computerized representation
of the mouse brain, providing a systematic and comprehensive digital
space with links between a coordinate system and systems of nomenclature
for the structural subdivisions of the nervous system. In addition,
tools have been developed to map information derived from brain sections
onto this three-dimensional Atlas, making it possible to correct for
distortions of brain tissue that occur during various histological
procedures to visualize gene expression. Such Atlases are being developed
for adult mice and mice of specific ages through development. Similarly,
an Atlas of the human brain has been devised, and software tools generated
to import information derived from multiple modalities (e.g. fMRI)
and map it onto the Atlas.
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