Philip Hieter, Mark Boguski

P. Hieter is at the Center for Molecular Medicine and Therapeutics, Department of Medical Genetics, University of British Columbia, Vancouver, BC, V6T124 Canada. M. Boguski is at the National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD, USA 20892. 

To fully understand functional genomics, we must examine its roots. The term "genome" itself is more than 75 years old and refers to an organism's complete set of genes and chromosomes. The term "genomics" was coined rather recently (in 1986) by Thomas Roderick to describe the scientific discipline of mapping, sequencing, and analyzing genomes and to provide a name for the new journal Genomics (1). The term has become universally accepted over the past decade. Genomics is now undergoing, however, a transition or expansion from the mapping and sequencing of genomes (the original stated goals of the Human Genome Project) to an emphasis on genome function. To reflect this shift, genome analysis may now be divided into "structural genomics" and "functional genomics." Structural genomics represents an initial phase of genome analysis and has a clear end point--the construction of high-resolution genetic, physical, and transcript maps of an organism. The ultimate physical map of an organism is its complete DNA sequence.

Functional genomics represents a new phase of genome analysis. It provides a fertile ground for (and will require) creative thinking in developing innovative technologies that make use of the vast resource of structural genomics information. Specifically, functional genomics refers to the development and application of global (genome-wide or system-wide) experimental approaches to assess gene function by making use of the information and reagents provided by structural genomics. It is characterized by high throughput or large-scale experimental methodologies combined with statistical and computational analysis of the results. The fundamental strategy in a functional genomics approach is to expand the scope of biological investigation from studying single genes or proteins to studying all genes or proteins at once in a systematic fashion. Computational biology will perform a critical and expanding role in this area: whereas structural genomics has been characterized by data management, functional genomics will be characterized by mining the data sets for particularly valuable information. Functional genomics promises to rapidly narrow the gap between sequence and function and to yield new insights into the behavior of biological systems.

Several recent studies fall under the operational definition of functional genomics. The recent completion (2) of the genome sequence of the budding yeast Saccharomyces cerevisiae (in other words, completion of the structural genomics phase) has provided the raw material to begin exploring the potential power of functional genomics approaches. An international consortium of yeast biologists is systematically constructing a comprehensive set of yeast strains, each of which will be deleted for one of the roughly 6000 predicted genes (3). Individual yeast open reading frames (ORFs) are being systematically replaced by oligonucleotide "bar codes," which can be used in a polymerase chain reaction (PCR) or DNA microarray assay for revealing those strains that survive under particular conditions (4). This reference collection will be made publicly available as soon as it is finished and will provide yeast researchers specializing in the study of a particular cellular process or class of genes the opportunity to devise assays or genetic screens utilizing the strain set. Three recently devised methods for obtaining genome-wide mRNA expression data, oligonucleotide "chips" (5), SAGE (6) and DNA microarrays (7), are particularly powerful in the context of knowing the entire genome sequence (and thus all genes) (8). The report by De Risi et al. in this issue (9) provides a powerful example of the way in which the DNA microarray methodology can provide a global view of changes in gene expression patterns in response to physiological shifts or manipulation of transcriptional regulators. The SAGE method, in the context of nearly comprehensive expressed sequence tag (EST) data, has also been elegantly applied to analysis of genes differentially expressed in human cancer (10).

In addition, knowledge of the yeast genome sequence has made feasible the systematic analysis of protein-protein interactions for all 6000 yeast proteins by means of the two-hybrid method (11). Analysis of all 18 million pair-wise combinations is under way. Furthermore, partial protein sequences from high-resolution, two-dimensional gels and electrospray mass spectrometry of protein complexes can be used to unambiguously assign peptides to specific gene sequences in the context of the whole genome sequence (12, 13).

As Peter Goodfellow has said (14), the central belief embedded in functional genomics is that the complete sequence of the genomes of many organisms, including humans, will change the way we do biology. Daniel Tosteson, dean of the Harvard Medical School, described the situation more explicitly: "In the past we have had functions in search of sequences. In the future, pathology and physiology will become `functionators' for the sequences" (15). Traditional disciplines are already adopting a genome-scale viewpoint when it comes to approaching research problems. One example is the Cancer Genome Anatomy Project (CGAP), which seeks to foster infrastructure and new methodologies for cancer detection, diagnosis, prognosis, and therapy (16). Functional genomics will not only make traditional research approaches more productive and efficient, but will also supplement the detailed understanding of gene function provided by traditional approaches with a powerful new perspective on the holistic operation of biological systems. Functional genomics, however, will not replace the time-honored use of genetics, biochemistry, cell biology, and structural studies in gaining a detailed understanding of biological mechanisms. The extent to which any functional genomics approach actually defines the function of a particular protein (or set of proteins) will vary depending on the method and gene involved. In general, the functional information gained will provide a framework and a starting point for further analysis (17, 18), much like a primary genetic screen identifies candidate genes that require extensive subsequent validation.

We are entering a phase in which we shall see more functional genomics data and hear less hype. Despite the unprecedented volume of data being generated from individual experiments, rigorous, reproducable design must be the watchword, so that emerging technologies can be fairly evaluated. The traditional format of scientific publication cannot reflect the scope and depth of data being produced. Summaries of results and conclusions in publications are certainly of interest, but are not very useful for subsequent analysis or utilization of the data by others and may not even be adequate for effective peer review. A key issue regarding the access to data from publicly funded, genome-scale, functional analyses must be addressed. A great legacy of the structural genomics era is the philosophy and practice of the public release of data that we hope will carry over to the functional genomics age. The timely submission of expression data, for example, in some standard format independent of specific technique, would lead to the most effective analysis and utilization of the results by the scientific community.

REFERENCES AND NOTES

1. V. McKusick, Genomics, in press.
2. A. Goffeau, et al., Science 274, 546 (1996) [Abstract/Full Text].
3. S. Oliver, Trends Genet. 12, 241 (1996) [Medline].
4. V. Smith, D. Botstein, P. O. Brown, Proc. Natl. Acad. Sci. U.S.A. 92, 6479 (1995) [Medline]; D. D. Shoemaker et al., Nature Genet. 14, 450 (1996) [Medline].
5. S. Fodor, et al., Nature 364, 555 (1993) [Medline].
6. V. E. Velculescu, L. Zhang, B. Vogelstein, K. W. Kinzler, Science 270, 484 (1995) [Abstract].
7. M. Schena, D. Shalon, R. W. Davis, P. O. Brown, ibid., p. 467.
8. V. E. Velculescu et al., Cell 88, 243 (1997) [Medline].
9. J. L. DeRisi, V. R. Iyer, P. O. Brown, Science 278, 680 (1997) [Abstract/Full Text].
10. L. Zhang, et al., ibid. 276, 1268 (1997) [Abstract/Full Text].
11. S. Fields and O. Song, Nature 340, 245 (1989) [Medline].
12. J. Yates, J. Eng, A. McCormack, D. Schieltz, Anal. Chem. 67, 1426 (1995) [Medline].
13. M. Wilm, et al., Nature 379, 466 (1996) [Medline].
14. P. Goodfellow, Nature Genet. 16, 209 (1997) [Medline].
15. Symposium on "Genomics and Gene Therapy: Meaning for the Future of Science and Medicine," Harvard Institute of Human Genetics, Cambridge, MA, 26 March 1997.
16. http://www.ncbi.n1m.nih.gov/ncicgap/
17. G. Miklos, L. Gabor, G. M. Rubin, Cell 86, 521 (1996) [Medline].
18. S. Fields, Nature Genet. 5, 325 (1997) .
19. We thank J. Roskams, S. Fields, and D. Bassett for critical reading of the manuscript and helpful input.

Volume 278, Number 5338 Issue of 24 October 1997, pp. 601 - 602
©1997 by The American Association for the Advancement of Science.

Related Items

	The Evolution of Genomics Science 24 October 1997; 278 (5338):555 (in Genome Issue: Building Gene Families; Editorial) D. Duboule
	BIOMEDICAL POLICY: Whose DNA Is It, Anyway? Science 24 October 1997; 278 (5338):564 (in News & Comment) E. Marshall
	HUMAN GENETICS: NRC OKs Long-Delayed Survey of Human Genome Diversity Science 24 October 1997; 278 (5338):568 (in News & Comment) E. Pennisi
	HUMAN GENETICS: Environment Institute Lays Plans for Gene Hunt Science 24 October 1997; 278 (5338):569 (in News & Comment) J. Kaiser
	Predictive Genetic Testing: From Basic Research to Clinical Practice Science 24 October 1997; 278 (5338):602 (in Viewpoints) N. A. Holtzman, P. D. Murphy, M. S. Watson, P. A. Barr
	Sequencing the Human Genome Science 24 October 1997; 278 (5338):605 (in Viewpoints) L. Rowen, G. Mahairas, L. Hood
	Gene Families: The Taxonomy of Protein Paralogs and Chimeras Science 24 October 1997; 278 (5338):609 (in Genome Issue: Building Gene Families; Articles) S. Henikoff, E. A. Greene, S. Pietrokovski, P. Bork, T. K. Attwood, L. Hood
	GENOME MAPS 8: Building Gene Families Science 24 October 1997; 278 (5338):615 (in Genome Issue: Building Gene Families; Articles)
	A Genomic Perspective on Protein Families Science 24 October 1997; 278 (5338):631 (in Genome Issue: Building Gene Families; Articles) R. L. Tatusov, E. V. Koonin, D. J. Lipman
	Functional Coherence of the Human Y Chromosome Science 24 October 1997; 278 (5338):675 (in Reports) B. T. Lahn and D. C. Page
	Exploring the Metabolic and Genetic Control of Gene Expression on a Genomic Scale Science 24 October 1997; 278 (5338):680 (in Reports) J. L. DeRisi, V. R. Iyer, P. O. Brown