Introduction:
The completion of the draft sequence of the mouse genome represents a significant milestone in biology, with particularly important implications for neuroscience. This advance paves the way for a deeper understanding of the brain, propelling neuroscience into a new era of discovery. (NATURE NEUROSCIENCE, 2003).
The Rise of Post-Genomic Neuroscience:
While the sequencing of the human genome and that of other organisms has been conducted with a “big science” approach, neuroscience has traditionally focused on hypothesis-driven studies conducted by small groups of researchers. However, the success of large-scale genome sequencing, achieved by the development of high-throughput technologies and advanced algorithms, suggests that neuroscience may also benefit from a similar approach. (NATURE NEUROSCIENCE, 2003).
Mapping Gene Expression in the Brain:
The first crucial step in the postgenomic era of neuroscience is to map the expression pattern of each of the approximately 30,000 genes in the mammalian genome. Early studies, such as those describing the expression of mouse orthologs for every known gene on human chromosome 21, have revealed that a surprisingly high proportion of these genes are expressed in the brain, many with distinct regional expression patterns (NATURE NEUROSCIENCE, 2003).
Unraveling the Cellular Complexity of the Brain:
The brain is composed of a variety of cell types, and complete characterization of these cells requires a combination of approaches. Dissection-based techniques such as PCR and microarray analysis allow rapid analysis of multiple genes but lack spatial resolution. In situ hybridization offers better resolution but is generally not sufficient to identify specific cell types. A promising alternative is the labeling of individual genes in transgenic animals with markers such as green fluorescent protein (GFP), revealing their in vivo expression patterns and allowing purification of specific cell types for molecular analysis. (NATURE NEUROSCIENCE, 2003).
Unraveling Cellular Identity Through Gene Expression:
Although the exact number of cell types in the brain remains unknown, a classification based on gene expression is likely to reveal many more subtypes than are recognized by traditional morphological criteria. An efficient approach may be to start with transcription factors, powerful markers for the study of neural development. It is plausible that specific combinations of transcription factor expression determine many other cellular properties, including morphology, excitability, connectivity, and synaptic properties. (NATURE NEUROSCIENCE, 2003).
Impact of Cellular Characterization on Brain Function:
A complete inventory of the cellular components of the nervous system would be an invaluable resource for developmental studies and for understanding brain function. Uncertainty about the cell type being recorded limits many systems-level studies, especially in intact animals. A comprehensive molecular description would allow correlation of firing patterns with cell identity and functional properties. Furthermore, new genetic tools would enable manipulation of the activity of specific cell types in vivo. (NATURE NEUROSCIENCE, 2003).
Scaling to Full Genome and Brain:
Although many postgenomic approaches are already feasible on a small scale, scaling up these efforts to the genome and whole brain presents a considerable challenge. Neuroscience can benefit from the experiences of the genomics community, particularly with regard to data sharing, software development, and political organization. (NATURE NEUROSCIENCE, 2003).
Lessons from Genomics:
Data sharing is essential for rapid progress, and the genomics community has demonstrated this by adhering to the “Bermuda Rules,” which require data to be made available quickly in public archives. Neuroscience needs to overcome its reluctance to share data and embrace this practice (NATURE NEUROSCIENCE, 2003).
Software and Standards:
The analysis of “neuromics” data – gene expression catalogs, digital atlases of brain anatomy, databases of neuronal morphology and physiology, software for serial reconstruction of electron microscopy, among others – will require robust and interoperable software. Software diversity is essential for the evolution of the field, but interoperability must be guaranteed through standards defined by some central authority (NATURE NEUROSCIENCE, 2003).
Vision and Leadership:
The success of the Human Genome Project was due in part to the ability of its leaders to present a bold vision that captured the imagination of politicians and the public. Neuroscience needs a similar vision to secure the support and funding needed for its large-scale endeavors in the post-genomic era. (NATURE NEUROSCIENCE, 2003).
Conclusion:
Neuroscience is on the cusp of a profound transformation in the post-genomic era. By embracing the lessons learned from genomics and developing the necessary technologies and approaches, neuroscientists can unlock the mysteries of the brain in unprecedented ways, paving the way for new discoveries and treatments for neurological diseases.
Reference:
NATURE NEUROSCIENCE. Neuroscience in the post-genome era. Nature Neuroscience, vol. 6, no. 1, p. 1, 2003.
