Phosphoregulators: Protein kinases and Protein phosphatases of mouse
Alistair RR Forrest1, Timothy Ravasi2, Darrin Taylor, Rohan Teasdale, RIKEN GER Group Members ,and Sean Grimmond
1a.forrest@imb.uq.edu.au, IMB; 2t.ravasi@imb.uq.edu.au, IMB
With the completion of the human and mouse genome sequences the task now turns to identifying their encoded transcripts and assigning gene function. In this paper we have undertaken a computational approach to identify and classify all the protein kinases and phosphatases present in the mouse gene complement. A non-redundant set of these sequences was produced by mining Ensembl gene predictions and publicly available cDNA sequences with a panel of InterPro domains. This approach identified 561 candidate protein kinases and 162 candidate protein phosphatases. This cohort was then analysed using TribeMCL protein sequence similarity clustering followed by CLUSTALV alignment and hierarchical tree generation. This approach allowed us to 1) distinguish between true members of the protein kinase and phosphatase families and enzymes of related biochemistry
2) determine the structure of the families and 3) suggest functions for previously uncharacterized members. The classifications obtained by this approach were in good agreement with previous schemes and allowed us to demonstrate domain associations with a number of clusters. Finally we comment on the complementary nature of cDNA and genome based gene detection and the impact of the FANTOM2 transcriptome project.