6/20/2001 8:00 AM
6/20/2001 2:30 PM
The NIGMS working group was charged with identifying research trends and opportunities related to large-scale patterns of genetic variation. The past few decades of research focusing largely on reductionism have yielded vast amounts of data. In addition, the various genome sequencing projects, as well as structural and functional genomics initiatives, are producing data far more rapidly than scientists can analyze them and understand their implications to biology and to health. Indeed, as the working group pointed out, as complex and overwhelming as the current data are, they are only the beginning. Every protein structure, every DNA sequence, every gene expression pattern has the potential of varying among individuals, among species, among populations within a species, and across environments. It will soon be possible to utilize information on thousands of variable genetic sites to investigate the relationships among genotypes, phenotypes, and environments. Studies of genetic variation are in their infancy, and it is vital to encourage research in this area.
There is no single way to characterize large-scale variation. One approach is to consider the combinatorial effects of many variable sites, whether the scale is within a gene or across a genome. Comparative genomics, where the goal is to identify patterns of variation among genomes, is also a productive way of identifying attributes of variation, such as which genomic regions are rapidly evolving. It is also important to study the context or environments in which genetic variation arises, is selected, and is maintained. Finally, variation occurs at every biological level of organization, from DNA sequence to protein structure to metabolic pathways to cell dynamics to individual phenotype to population characteristics.
Biological variation underlies differences in the expression of many human traits, including genetic disorders, responsiveness to drugs, susceptibility and resistance to infection, and response to trauma. Genetic and environmental variation may be related to the onset of a disease, its specific symptoms, and its severity, even if the disease-causing gene itself is not directly affected. The following areas of research may uncover important features of biological variation.
Studies of genetic architecture have historically focused on associations of genotype and phenotype (e.g., between DNA markers and a disease). In the future, it will also be important to focus on many levels of biological processes between DNA and a phenotype. A significant NIGMS effort focuses on the detailed analysis of the physical, biochemical, and genetic pathways that direct cellular development and metabolism. A next step will be studying how these complex systems diverge in different states (e.g., in a single individual, among healthy individuals, in the presence of disease, in different organisms) and to address how these complex systems evolve.
How genes are expressed depends on their cellular, developmental, physiological, and environmental context. The importance of context dependence is particularly important in medical research because study populations are rarely a random sample of the general population. For example, certain mutations in BRCA1 are predictive of breast cancer in 52 percent of the cases in which four or more family members have been affected. The same mutations are associated with only 1 percent of the sporadic cases of breast cancer. Clearly, BRCA1 operates in a larger context about which we know little. We need better tools and models for identifying important contextual features and determining how they interact.
Evolution of Genome Properties
An emerging area of research focuses on such issues as the evolution of haplotypes, selection for increased genetic interactions, and the evolution of recombination and methylation patterns. For example, rates of crossing-over vary within a genome; the Y chromosome rarely, if ever, recombines, but there are other "hotspots" of recombination. Recombination rates also vary dramatically among species; two closely related species of Drosophila, for example, differ 14-fold in their overall recombination rates. Such differences have important consequences for genome organization and evolution. The organization and evolution of haplotypes is an emerging area of research. For example, studies of the human Y chromosome and mitochondrial DNA have led to a good understanding of early human history and migration--a necessary prerequisite to studying the genetics of specific populations at risk for disease. We also know that specific haplotypes, while not causal, are associated with such diseases as multiple sclerosis, diabetes, arthritis, Parkinson's disease, and AIDS.
Extensions to Other Organisms
Many organisms have been studied for their value in agriculture or ecology. Thus there is considerable information about the population structure, natural history, and genetics of these systems. It will be valuable to take advantage of this wealth of information to study variation in the natural settings in which it evolved.
The study of biological variation depends heavily on rich data sets; researchers need the ability to access many kinds of information (e.g., DNA sequence, protein structure, development, natural history, and phenotype) in organisms from different habitats, from different populations, or from different species. In addition, whether one is looking at a clinical phenotype or at a gene expression array, it is important that experts agree on data standards so that data can be compared, combined, and shared. Organizing, maintaining, and making this information available should be included in any initiative.
Improved Dynamic Modeling and Statistical Methods
Mathematical approaches to studying biological variation have changed little in several decades. The working group pointed out that there is a need to develop new dynamic models to illuminate how systems interact. Just as important, it is critical to study the nature of biological and mathematical assumptions on models and statistics. For example, assumptions about cell biology or protein structure (e.g., that synonymous changes are not under selection or that mutation rates are the same throughout the genome) may seriously affect the validity of our analyses and predictions.
Studies of DNA sequences, protein structures, and basic cell processes have provided and will continue to provide rich data for studies of biological systems. The scientific scope of the proposed initiative would include:
The working group felt strongly that there should be opportunities both for individual research programs and for large, collaborative efforts. Based on the discussion at the meeting, NIGMS staff recommend a two-fold approach to addressing these research areas:
The working group also raised the issue of explicitly including both minority scientists and minority-serving institutions. The rationale is two-fold. First, to be credible, studies of human variation should be designed and conducted by a diverse and knowledgeable group of scientists. Second, in many areas of cutting-edge science, such as genomics and evolutionary biology, minority scientists are seriously underrepresented. It is important to establish programs to recruit and train those scientists now. The working group stressed that real partnerships among scientists and institutions are vital to addressing this goal. Collaborations that address training and infrastructure needs in minority-serving institutions are especially valuable.
Alan Templeton, ChairWashington UniversityOne Brookings DriveSt. Louis, MO 63130(314) 935-6868
Andrew ClarkPennsylvania State University326 Mueller LabUniversity Park, PA 16802(814) 863-3891
Anna DiRienzoDepartment of Human GeneticsUniversity of Chicago920 E. 58th StreetCLSC 507FChicago, IL 60637(773) 834-1037
Marc FeldmanStanford UniversityHERRIN 478AStanford, CA 94305-5020(650) 725-1867
Ira HerskowitzDepartment of Biochemistry and BiophysicsUniversity of California, San FranciscoBox 0448, HSE 901HSan Francisco, CA 94143(415) 476-4977
David KingsleyHHMI and Department of Developmental Biology Stanford University School of Medicine Beckman Center B300279 Campus DriveStanford, CA 94305-53295(650) 725-5954
Rick KittlesNational Human Genome Center Howard University2041 Georgia AvinueRoom 615Washington, DC 20060(202) 806-6979
Richard LewontinDepartment of Organismic and Evolutionary BiologyMuseum of Comparative Zoology Labs 317b26 Oxford StreetHarvard UniversityCambridge, MA 02138(617) 495-2419
Maria Fatima LimaSchool of Graduate Studies and ResearchMeharry Medical College1005 D.B. Todd BoulevardNashville, TN 37208-3599(615) 327-6533
Jean MacCluerDepartment of GeneticsSouthwest Foundation for Biomedical ResearchPO Box 760549San Antonio, TX 78245-0549(210) 258-9490
Andrew MurrayDepartment of Molecular & Cellular BiologyHarvard University16 Divinity Avenue, Room 3000Cambridge, MA 02138-2097(617) 496-1350
Andrej SaliRockefeller University1230 York AvenueNew York, NY 10021(212) 327-7550
Oliver SmithiesUniversity of North CarolinaChapel Hill, NC 27599(919) 966-6913
Roland SomogyiMolecular Mining Corp128 Ontario StreetKingston, OntarioK7L 2Y4(613) 547-9752
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