title: A computational interactome for prioritizing genes associated with complex agronomic traits in rice (Oryza sativa).
abstract: Rice (Oryza sativa) is one of the most important staple foods for more than half of the global population. Many rice traits are quantitative, complex and controlled by multiple interacting genes. Thus, a full understanding of genetic relationships will be critical to systematically identify genes controlling agronomic traits. We developed a genome-wide rice protein-protein interaction network (RicePPINet, http://netbio.sjtu.edu.cn/riceppinet) using machine learning with structural relationship and functional information. RicePPINet contained 708 819 predicted interactions for 16 895 non-transposable element related proteins. The power of the network for discovering novel protein interactions was demonstrated through comparison with other publicly available protein-protein interaction (PPI) prediction methods, and by experimentally determined PPI data sets. Furthermore, global analysis of domain-mediated interactions revealed RicePPINet accurately reflects PPIs at the domain level. Our studies showed the efficiency of the RicePPINet-based method in prioritizing candidate genes involved in complex agronomic traits, such as disease resistance and drought tolerance, was approximately 2-11 times better than random prediction. RicePPINet provides an expanded landscape of computational interactome for the genetic dissection of agronomically important traits in rice.
authors.affiliation: Department of Plant Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China.
authors.forename: Shiwei
authors.initials: S
authors.lastname: Liu
authors.affiliation: Department of Plant Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China.
authors.forename: Yihui
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Department of Plant Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China.
authors.forename: Jiawei
authors.initials: J
authors.lastname: Zhao
authors.affiliation: Department of Plant Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China.
authors.forename: Shitao
authors.initials: S
authors.lastname: Cai
authors.affiliation: Department of Plant Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China.
authors.forename: Hongmei
authors.initials: H
authors.lastname: Qian
authors.affiliation: Department of Plant Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China.
authors.forename: Kaijing
authors.initials: K
authors.lastname: Zuo
authors.affiliation: Department of Plant Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China.
authors.forename: Lingxia
authors.initials: L
authors.lastname: Zhao
authors.affiliation: Department of Plant Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China.|Key Laboratory of Urban Agriculture (South) Ministry of Agriculture, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China.
authors.forename: Lida
authors.initials: L
authors.lastname: Zhang
mesh_terms: D018745:Genome, Plant / Q000235:genetics; D012275:Oryza / Q000235:genetics*; D010641:Phenotype; D060066:Protein Interaction Maps; D040641:Quantitative Trait Loci / Q000235:genetics*
keywords: 
  Oryza sativa
  ; complex trait; interactome; protein-protein interaction network; rice