title: Rewiring of the inferred protein interactome during blood development studied with the tool PPICompare.
abstract: Differential analysis of cellular conditions is a key approach towards understanding the consequences and driving causes behind biological processes such as developmental transitions or diseases. The progress of whole-genome expression profiling enabled to conveniently capture the state of a cell's transcriptome and to detect the characteristic features that distinguish cells in specific conditions. In contrast, mapping the physical protein interactome for many samples is experimentally infeasible at the moment. For the understanding of the whole system, however, it is equally important how the interactions of proteins are rewired between cellular states. To overcome this deficiency, we recently showed how condition-specific protein interaction networks that even consider alternative splicing can be inferred from transcript expression data. Here, we present the differential network analysis tool PPICompare that was specifically designed for isoform-sensitive protein interaction networks.
  
  
  
  Besides detecting significant rewiring events between the interactomes of grouped samples, PPICompare infers which alterations to the transcriptome caused each rewiring event and what is the minimal set of alterations necessary to explain all between-group changes. When applied to the development of blood cells, we verified that a reasonable amount of rewiring events were reported by the tool and found that differential gene expression was the major determinant of cellular adjustments to the interactome. Alternative splicing events were consistently necessary in each developmental step to explain all significant alterations and were especially important for rewiring in the context of transcriptional control.
  
  
  
  Applying PPICompare enabled us to investigate the dynamics of the human protein interactome during developmental transitions. A platform-independent implementation of the tool PPICompare is available at https://sourceforge.net/projects/ppicompare/ .
authors.affiliation: Center for Bioinformatics, Saarland University, Campus E2.1, Saarbrücken, 66123, Germany.|Graduate School of Computer Science, Saarland University, Campus E1.3, Saarbrücken, 66123, Germany.
authors.forename: Thorsten
authors.initials: T
authors.lastname: Will
authors.affiliation: Center for Bioinformatics, Saarland University, Campus E2.1, Saarbrücken, 66123, Germany. volkhard.helms@bioinformatik.uni-saarland.de.
authors.forename: Volkhard
authors.initials: V
authors.lastname: Helms
mesh_terms: D017398:Alternative Splicing; D001798:Blood Proteins / Q000378:metabolism*; D019295:Computational Biology / Q000379:methods*; D020869:Gene Expression Profiling; D006410:Hematopoiesis; D006801:Humans; D058977:Molecular Sequence Annotation; D060066:Protein Interaction Maps; D014158:Transcription, Genetic
chemical_list: D001798:Blood Proteins
keywords: Alternative splicing; Differential network analysis; Hematopoiesis; Protein-protein interaction networks