New Publication: Inferring the Brassica rapa interactome using protein–protein interaction data from Arabidopsis thaliana

Happy New Year to my blog readers and followers. We have had a good start to the year with a new publication! The lead author, Jianhua Yang, is employed on the EU MEIOSYS grant with which I am involved; our main input is through contributions from Mudassar.

Yang, J., Osman, K., Iqbal, M., Stekel, D.J., Luo, Z., Armstrong, S.J. and Franklin, F.C.H. 2013. Inferring the Brassica rapa interactome using protein–protein interaction data from Arabidopsis thaliana. Frontiers in Plant Science 3:297.


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.



BBSRC Lux Grant Launch

This weeks sees the launch of our BBSRC Lux grant.

We are delighted to have recruited two experienced and talented PostDocs to work on the project.

Neil Doherty will work with Phil Hill and Dave Scott on the experimental elements of the work. Neil has a BSc in Biochemistry from the University of Warwick and a PhD in molecular microbiology also from the University of Warwick. He has since been carrying out postdoctoral research at the University of Nottingham in a number of molecular microbiology research groups, where he has carried out a wide range of experimental work in Staphylococcus aureus, Helicobacter pylori, Streptococcus pneumoniae and Escherichia coli.

Mudassar Iqbal will work with me on the modelling and inference elements of the work. Mudassar has a MSc in physics from the University of the Punjab, an MRes in modelling and simulation of complex realities from the ICTP/SISSA, Trieste, and a PhD in bioinformatics at the University of Kent. He was since carrying out postdoctoral research at the Warwick Systems Biology Centre. Mudassar’s experience includes development of algorithms for analysis of codon usage bias, protein-protein interactions and inference in transcriptomics.

We welcome both Neil and Mudassar to Nottingham and look forward to several years of interdisciplinary research.