Inferring the Brassica rapa interactome using protein-protein interaction data from Arabidopsis thaliana

被引:17
|
作者
Yang, Jianhua [1 ]
Osman, Kim [1 ]
Iqbal, Mudassar [2 ]
Stekel, Dov J. [2 ]
Luo, Zewei [1 ]
Armstrong, Susan J. [1 ]
Franklin, F. Chris H. [1 ]
机构
[1] Univ Birmingham, Birmingham B15 2TT, W Midlands, England
[2] Univ Nottingham, Nottingham NG7 2RD, England
来源
基金
英国生物技术与生命科学研究理事会;
关键词
Brassica rapa; Arabidopsis thaliana; interactome; protein-protein interaction; domain-domain interaction; meiosis; DOMAIN-DOMAIN INTERACTIONS; INTERACTION NETWORKS; PLANT INTERACTOMES; DATA INTEGRATION; MISMATCH REPAIR; GENE; GENOME; RECOMBINATION; MEIOSIS; IDENTIFICATION;
D O I
10.3389/fpls.2012.00297
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
Following successful completion of the Brassica rapa sequencing project, the next step is to investigate functions of individual genes/proteins. For Arabidopsis thaliana, large amounts of protein-protein interaction (PPI) data are available from the major PPI databases (DBs). It is known that Brassica crop species are closely related to A. thaliana. This provides an opportunity to infer the B. rapa interactome using PPI data available from A. thaliana. In this paper, we present an inferred B. rapa interactome that is based on the A. thaliana PPI data from two resources: (i) A. thaliana PPI data from three major DBs, BioGRID, IntAct, and TAIR. (ii) ortholog-based A. thaliana PPI predictions. Linking between B. rapa and A. thaliana was accomplished in three complementary ways: (i) ortholog predictions, (ii) identification of gene duplication based on synteny and collinearity, and (iii) BLAST sequence similarity search. A complementary approach was also applied, which used known/predicted domain-domain interaction data. Specifically, since the two species are closely related, we used PPI data from A. thaliana to predict interacting domains that might be conserved between the two species. The predicted interactome was investigated for the component that contains known A. thaliana meiotic proteins to demonstrate its usability.
引用
收藏
页数:15
相关论文
共 50 条
  • [31] Inferring plant microRNA functional similarity using a weighted protein-protein interaction network
    Meng, Jun
    Liu, Dong
    Luan, Yushi
    BMC BIOINFORMATICS, 2015, 16
  • [32] SPRINT: ultrafast protein-protein interaction prediction of the entire human interactome
    Li, Yiwei
    Ilie, Lucian
    BMC BIOINFORMATICS, 2017, 18
  • [33] An Integrated Approach (CLuster Analysis Integration Method) to Combine Expression Data and Protein-Protein Interaction Networks in Agrigenomics: Application on Arabidopsis thaliana
    Santoni, Daniele
    Swiercz, Aleksandra
    Zmienko, Agnieszka
    Kasprzak, Marta
    Blazewicz, Marek
    Bertolazzi, Paola
    Felici, Giovanni
    OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY, 2014, 18 (02) : 155 - 165
  • [34] Global protein interactome exploration through mining genome-scale data in Arabidopsis thaliana
    Feng Xu
    Guang Li
    Chen Zhao
    Yuhua Li
    Peng Li
    Jian Cui
    Youping Deng
    Tieliu Shi
    BMC Genomics, 11
  • [35] Global protein interactome exploration through mining genome-scale data in Arabidopsis thaliana
    Xu, Feng
    Li, Guang
    Zhao, Chen
    Li, Yuhua
    Li, Peng
    Cui, Jian
    Deng, Youping
    Shi, Tieliu
    BMC GENOMICS, 2010, 11
  • [36] Inferring protein function by domain context similarities in protein-protein interaction networks
    Zhang, Song
    Chen, Hu
    Liu, Ke
    Sun, Zhirong
    BMC BIOINFORMATICS, 2009, 10
  • [37] Using logistic regression method to predict protein function from protein-protein interaction data
    Ni, Qingshan
    Wang, Zhengzhi
    Han, Qingjuan
    Li, Gangguo
    Wang, Xiaomin
    Wang, Guangyun
    2009 3RD INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICAL ENGINEERING, VOLS 1-11, 2009, : 704 - +
  • [38] Inferring protein function by domain context similarities in protein-protein interaction networks
    Song Zhang
    Hu Chen
    Ke Liu
    Zhirong Sun
    BMC Bioinformatics, 10
  • [39] Structural domain-domain interactions: Assessment and comparison with protein-protein interaction data to improve the interactome
    Prieto, C.
    De Las Rivas, J.
    PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2010, 78 (01) : 109 - 117
  • [40] Mining protein-protein interaction data
    Haasl, Ryan J.
    Fang, Jianwen
    CURRENT BIOINFORMATICS, 2006, 1 (02) : 197 - 205