View - ResearchGate

7Estimating Protein Function Using Protein–ProteinRelationshipsShailesh V. DateSummaryMany newly identified gene products from completely sequenced genomes are difficult to characterizein the absence of sequence homology to known proteins. In such a scenario, the context of theproteins’ functional associations can be used for annotation; overrepresented functional linkages witha certain class of proteins or members of a pathway allow putative function assignments based on the“guilt-by-association” principle. Two computational functional genomics methods, phylogenetic profilingand identification of Rosetta stone linkages, are described in this chapter, which allow assessmentof functional linkages between proteins, consequently facilitating annotation. Phylogeneticprofiling involves measuring similarity between profiles that describe the presence or absence of aprotein in a set of reference genomes, whereas Rosetta stone fusion sequences help link two or moreindependently transcribed and translated proteins. Both methods can be applied to investigate functionalassociations between individual proteins, and can also be extended to reconstruct the genomewidenetwork of functional linkages by querying the entire protein complement of an organism.Key Words: Interactome; protein-protein interactions; functional linkages; phylogeneticprofiles; matual information; Rosetta stone fusion sequences.1. IntroductionThe number of organisms with fully sequenced genomes is growing at arapid pace. However, many sequenced genomes are not fully annoted; analysisof this sequence data reveals that many genes and their products lack confidentfunctional assignments, primarily because of absence of any similaritywith sequences of known genes. Empirical observations suggest that thenumber of such uncharacterized genes is close to 30% for almost anysequenced genome, and can be as high as 60% for some, an example beingthe genome of the human malarial parasite Plasmodium falciparum (1).Absence of information about such a significant number of genes or theirFrom: Methods in Molecular Biology, vol. 408: Gene Function AnalysisEdited by: M. Ochs © Humana Press Inc., Totowa, NJ109