Is there a paradigm shift in genetics? Lessons from the study of human diseases.
The flood of genetic data made possible by recent technological advances has led to a number of important changes in our conceptual model, or working "paradigm," of genetics. Among these changes are recognition that (1) most mutations are unique; (2) there are many alleles at every locus, not just two; (3) these alleles have a hierarchical, or cladistic, history-dependent structure and geographic distribution; (3) the genotype-to-phenotype relationship is complex and quantitative, even for single-locus traits; (4) genotype-phenotype relationships often depend on the organization of the genome into linkage groups, gene families, and the like; and (5) genes affecting quantitative traits can be individually identified rather than solely being viewed as a polygenic aggregate, and these genes each have the same characteristics as genes for single-locus phenotypes. The latter provides a profound unifying impact on biology by reconciling long-standing conceptual differences on qualitative vis-a-vis quantitative phenotypes and their relative importance and evolution. Many of the data that have led to these advances have been generated in the study of genes associated with diseases in human populations. The conceptual changes affect all of biology, but are especially important in the human context, because the amount, complexity, and historical dependence of the variation in the human genome have serious societal implications regarding the epistemology of genetic causation and applications in public health. But whether these changes constitute a real "paradigm shift" in genetics, or are merely adjustments in the classical models developed early in this century, is unclear.
Weiss
K M
KM
Department of Anthropology, Pennsylvania State University, University Park 16802-3404, USA.
D000483:Alleles; D019143:Evolution, Molecular; D030342:Genetic Diseases, Inborn / Q000235:genetics*; D014644:Genetic Variation; D005826:Genetics, Medical; D005838:Genotype; D006801:Humans; D008957:Models, Genetic; D010641:Phenotype