Predicted protein-protein interactions in the moss Physcomitrella patens: a new bioinformatic resource.

Journal Article (Journal Article)

Background

Physcomitrella patens, a haploid dominant plant, is fast becoming a useful molecular genetics and bioinformatics tool due to its key phylogenetic position as a bryophyte in the post-genomic era. Genome sequences from select reference species were compared bioinformatically to Physcomitrella patens using reciprocal blasts with the InParanoid software package. A reference protein interaction database assembled using MySQL by compiling BioGrid, BIND, DIP, and Intact databases was queried for moss orthologs existing for both interacting partners. This method has been used to successfully predict interactions for a number of angiosperm plants.

Results

The first predicted protein-protein interactome for a bryophyte based on the interolog method contains 67,740 unique interactions from 5,695 different Physcomitrella patens proteins. Most conserved interactions among proteins were those associated with metabolic processes. Over-represented Gene Ontology categories are reported here.

Conclusion

Addition of moss, a plant representative 200 million years diverged from angiosperms to interactomic research greatly expands the possibility of conducting comparative analyses giving tremendous insight into network evolution of land plants. This work helps demonstrate the utility of "guilt-by-association" models for predicting protein interactions, providing provisional roadmaps that can be explored using experimental approaches. Included with this dataset is a method for characterizing subnetworks and investigating specific processes, such as the Calvin-Benson-Bassham cycle.

Full Text

Duke Authors

Cited Authors

  • Schuette, S; Piatkowski, B; Corley, A; Lang, D; Geisler, M

Published Date

  • March 16, 2015

Published In

Volume / Issue

  • 16 /

Start / End Page

  • 89 -

PubMed ID

  • 25885037

Pubmed Central ID

  • 25885037

Electronic International Standard Serial Number (EISSN)

  • 1471-2105

International Standard Serial Number (ISSN)

  • 1471-2105

Digital Object Identifier (DOI)

  • 10.1186/s12859-015-0524-1

Language

  • eng