Meeting Abstract
20.3 Thursday, Jan. 3 Scaling pleiotropic effects with organismal complexity WAGNER, GP; KENNEY-HUNT, JP; PAVLICEV, M*; PECK, JR; WAXMAN, D; CHEVERUD, JM; Yale University, New Haven; Washington University, St. Louis; Washington University, St. Louis; University Sussex, Brigton, UK; University Sussex, Brigton, UK; Washington University, St. Louis pavlicev@pcg.wustl.edu
Organismal complexity can be defined as the number of quasi-independent phenotypic characters. The effect of complexity on evolutionary change will be crucially dependent on the genetic architecture of complex phenotype. The degree of pleiotropy, i.e., the number of traits affected by a single mutation, is one of the proxies to measure genetic complexity of the organism. The way the effects of single mutation scale with degree of pleiotropy will influence the evolvability of the organism. At present, two main conflicting hypotheses are proposed. The most widely discussed proposal is that of a �cost of complexity�, predicting that the per trait effect of mutations will decrease with increasing degree of pleiotropy (complexity). The underlying statement of this prediction is that the total effect of pleiotropic mutation is fixed, hence the effect per trait will decrease as the number of traits increases. An opposite proposal is that the effect of mutation per trait is independent of the number of traits affected. Here we empirically explore the relationship between the degree of pleiotropy and the effect of mutation. We use an extensive dataset for the pleiotropic effects of 102 QTL (quantitative trait loci) on 70 skeletal characters in mice. Our analysis shows that the total genetic effect increases strongly with the number of characters affected. This effect is robust to corrections for directional selection, between-trait correlations and statistical detection limits of QTL effects. We conclude that the assumption that the total effect of a mutation is fixed is not supported by the QTL data presented. This implies that phenotype complexity does not necessarily reduce evolvability as suggested by the �cost of complexity� model.
