title: Shadows of complexity: what biological networks reveal about epistasis and pleiotropy.
abstract: Pleiotropy, in which one mutation causes multiple phenotypes, has traditionally been seen as a deviation from the conventional observation in which one gene affects one phenotype. Epistasis, or gene-gene interaction, has also been treated as an exception to the Mendelian one gene-one phenotype paradigm. This simplified perspective belies the pervasive complexity of biology and hinders progress toward a deeper understanding of biological systems. We assert that epistasis and pleiotropy are not isolated occurrences, but ubiquitous and inherent properties of biomolecular networks. These phenomena should not be treated as exceptions, but rather as fundamental components of genetic analyses. A systems level understanding of epistasis and pleiotropy is, therefore, critical to furthering our understanding of human genetics and its contribution to common human disease. Finally, graph theory offers an intuitive and powerful set of tools with which to study the network bases of these important genetic phenomena.
authors.affiliation: Computational Genetics Laboratory, Department of Genetics, Dartmouth Medical School, Lebanon, NH 03756, USA.
authors.forename: Anna L
authors.initials: AL
authors.lastname: Tyler
authors.forename: Folkert W
authors.initials: FW
authors.lastname: Asselbergs
authors.forename: Scott M
authors.initials: SM
authors.lastname: Williams
authors.forename: Jason H
authors.initials: JH
authors.lastname: Moore
mesh_terms: D004843:Epistasis, Genetic; D053263:Gene Regulatory Networks; D006801:Humans; D010641:Phenotype