Systems Mapping of Complex Traits Using Kinetic Models Jiguo Cao 1,2∗ , Zhongwen Huang 3 , Junyi Gai 4 , C. Eduardo Vallejos 5 and Rongling Wu 2,6∗ 1 Department of Statistics & Actuarial Science, Simon Fraser University, Burnaby, B.C. Canada V5A 1S6 2 Center for Computational Biology, Beijing Forestry University, Beijing 100083, China 3 Department of Agronomy, Henan Institute of Science and Technology, Xinxiang 453003, China 4 National Center for Soybean Improvement, National Key Laboratory for Crop Genetics and Germplasm Enhancement, Soybean Research Institute, Nanjing Agricultural University, Nanjing 210095, China 5 Department of Horticultural Sciences, University of Florida, Gainesville, FA 32611, USA 6 Center for Statistical Genetics, Pennsylvania State University, Hershey, PA 17033, USA ∗ Corresponding authors: jiguo cao@sfu.ca, rwu@hes.hmc.psu.edu SUMMARY: Every phenotypic trait can be viewed as a “system” in which a group of independent but interconnected components function together to comprise a unified whole. Once a system’s components and interactions have been delineated according to biological principles, therefore, we can change the phenotype of the system by altering those components and interactions that are functionally relevant to the system. Here, by incorporating a system of dif- ferential equations that quantifies how alterations of different components lead to the global change of trait development, we devise a computational model for genetic mapping of complex traits, equipped with a capacity to characterize genes and genetic interactions involved in the regulation of biological circuits. The model provides a quantitative and testable platform for assessing the in- 1