Epistasis in a quantitative trait captured by a molecular model of transcription factor interactions

• Published in: Theoretical population biology Vol. 77; no. 1; pp. 1 - 5
• Main Authors: Gertz, Jason, Gerke, Justin P., Cohen, Barak A.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01-02-2010
• Subjects: Epistasis; Epistasis, Genetic; Gene regulation; Genetic Variation; Genotype; Humans; Models, Genetic; Nonlinear Dynamics; Phenotype; Polymorphism, Genetic; Quantitative Trait Loci - genetics; Quantitative traits; Saccharomyces cerevisiae - genetics; Saccharomyces cerevisiae - physiology; Spores, Fungal - genetics; Spores, Fungal - physiology; Thermodynamic models; Thermodynamics; Transcription Factors - physiology; Yeast; Thermodynamic models; Epistasis; Yeast; Quantitative traits; Gene regulation
• ISSN: 0040-5809; 1096-0325
• DOI: 10.1016/j.tpb.2009.10.002

With technological advances in genetic mapping studies more of the genes and polymorphisms that underlie Quantitative Trait Loci (QTL) are now being identified. As the identities of these genes become known there is a growing need for an analysis framework that incorporates the molecular interactions affected by natural polymorphisms. As a step towards such a framework we present a molecular model of genetic variation in sporulation efficiency between natural isolates of the yeast,
Saccharomyces cerevisiae. The model is based on the structure of the regulatory pathway that controls sporulation. The model captures the phenotypic variation between strains carrying different combinations of alleles at known QTL. Compared to a standard linear model the molecular model requires fewer free parameters, and has the advantage of generating quantitative hypotheses about the affinity of specific molecular interactions in different genetic backgrounds. Our analyses provide a concrete example of how the thermodynamic properties of protein–protein and protein–DNA interactions naturally give rise to epistasis, the non-linear relationship between genotype and phenotype. As more causative genes and polymorphisms underlying QTL are identified, thermodynamic analyses of quantitative traits may provide a useful framework for unraveling the complex relationship between genotype and phenotype.