title: Mapping complex traits as a dynamic system.
abstract: Despite increasing emphasis on the genetic study of quantitative traits, we are still far from being able to chart a clear picture of their genetic architecture, given an inherent complexity involved in trait formation. A competing theory for studying such complex traits has emerged by viewing their phenotypic formation as a "system" in which a high-dimensional group of interconnected components act and interact across different levels of biological organization from molecules through cells to whole organisms. This system is initiated by a machinery of DNA sequences that regulate a cascade of biochemical pathways to synthesize endophenotypes and further assemble these endophenotypes toward the end-point phenotype in virtue of various developmental changes. This review focuses on a conceptual framework for genetic mapping of complex traits by which to delineate the underlying components, interactions and mechanisms that govern the system according to biological principles and understand how these components function synergistically under the control of quantitative trait loci (QTLs) to comprise a unified whole. This framework is built by a system of differential equations that quantifies how alterations of different components lead to the global change of trait development and function, and provides a quantitative and testable platform for assessing the multiscale interplay between QTLs and development. The method will enable geneticists to shed light on the genetic complexity of any biological system and predict, alter or engineer its physiological and pathological states.
authors.affiliation: National Engineering Research Center for Floriculture, College of Landscape Architecture, Beijing Forestry University, Beijing 100083, China; Center for Statistical Genetics, Departments of Public Health Sciences and Statistics, The Pennsylvania State University, Hershey, PA 17033, USA.
authors.forename: Lidan
authors.initials: L
authors.lastname: Sun
authors.affiliation: Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China; Center for Statistical Genetics, Departments of Public Health Sciences and Statistics, The Pennsylvania State University, Hershey, PA 17033, USA. Electronic address: rwu@bjfu.edu.cn.
authors.forename: Rongling
authors.initials: R
authors.lastname: Wu
mesh_terms: D000465:Algorithms; D002874:Chromosome Mapping; D019295:Computational Biology; D059647:Gene-Environment Interaction; D005838:Genotype; D006801:Humans; D008957:Models, Genetic; D010641:Phenotype; D010944:Plants / Q000235:genetics*; D040641:Quantitative Trait Loci; D049490:Systems Biology
keywords: Complex trait; Functional mapping; Genetic mapping; Network mapping; Quantitative trait loci; Systems mapping