title: Prediction and identification of the effectors of heterotrimeric G proteins in rice (Oryza sativa L.).
abstract: Heterotrimeric G protein signaling cascades are one of the primary metazoan sensing mechanisms linking a cell to environment. However, the number of experimentally identified effectors of G protein in plant is limited. We have therefore studied which tools are best suited for predicting G protein effectors in rice. Here, we compared the predicting performance of four classifiers with eight different encoding schemes on the effectors of G proteins by using 10-fold cross-validation. Four methods were evaluated: random forest, naive Bayes, K-nearest neighbors and support vector machine. We applied these methods to experimentally identified effectors of G proteins and randomly selected non-effector proteins, and tested their sensitivity and speciﬁcity. The result showed that random forest classifier with composition of K-spaced amino acid pairs and composition of motif or domain (CKSAAP_PROSITE_200) combination method yielded the best performance, with accuracy and the Mathew's correlation coefficient reaching 74.62% and 0.49, respectively. We have developed G-Effector, an online predictor, which outperforms BLAST, PSI-BLAST and HMMER on predicting the effectors of G proteins. This provided valuable guidance for the researchers to select classifiers combined with different feature selection encoding schemes. We used G-Effector to screen the effectors of G protein in rice, and confirmed the candidate effectors by gene co-expression data. Interestingly, one of the top 15 candidates, which did not appear in the training data set, was validated in a previous research work. Therefore, the candidate effectors list in this article provides both a clue for researchers as to their function and a framework of validation for future experimental work. It is accessible at http://bioinformatics.fafu.edu.cn/geffector.
authors.affiliation: State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, P. R. China.
authors.forename: Kuan
authors.initials: K
authors.lastname: Li
authors.affiliation: College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
authors.forename: Chaoqun
authors.initials: C
authors.lastname: Xu
authors.affiliation: College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
authors.forename: Jian
authors.initials: J
authors.lastname: Huang
authors.affiliation: State Key Laboratory of Bioorganic and Natural Products Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai, China; State Key Laboratory of Microbial Metabolism, School of Life Science & Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, China; Huzhou Center of Bio-Synthetic Innovation, 1366 Hongfeng Road, Huzhou, China.
authors.forename: Wei
authors.initials: W
authors.lastname: Liu
authors.affiliation: Department of Biology, University of California at San Diego, La Jolla, California, USA.
authors.forename: Lina
authors.initials: L
authors.lastname: Zhang
authors.affiliation: College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
authors.forename: Weifeng
authors.initials: W
authors.lastname: Wan
authors.affiliation: College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
authors.forename: Huan
authors.initials: H
authors.lastname: Tao
authors.affiliation: Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute of Sichuan Agricultural University, Chengdu, Sichuan Province, China.
authors.forename: Ling
authors.initials: L
authors.lastname: Li
authors.affiliation: College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
authors.forename: Shoukai
authors.initials: S
authors.lastname: Lin
authors.affiliation: Department of Mathematical Sciences, University of Essex, Wivenhoe Park, Colchester, UK.
authors.forename: Andrew
authors.initials: A
authors.lastname: Harrison
authors.affiliation: College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China.
authors.forename: Huaqin
authors.initials: H
authors.lastname: He
mesh_terms: D001499:Bayes Theorem; D020962:Heterotrimeric GTP-Binding Proteins; D012275:Oryza; D010940:Plant Proteins; D060388:Support Vector Machine
chemical_list: D010940:Plant Proteins; D020962:Heterotrimeric GTP-Binding Proteins
keywords: effectors; heterotrimeric G proteins; predicting; rice (Oryza sativa L.)