Supplementary data for "Reconstruction and Validation of RefRec: A Global Model for the Yeast Molecular Interaction Network"

  • Tommi Aho (Creator)
  • Henrikki Almusa (Creator)
  • Jukka Matilainen (Creator)
  • Antti Jaakko Larjo (Creator)
  • Pekka Ruusuvuori (Creator)
  • Kaisa-Leena Aho (Creator)
  • Thomas Wilhelm (Creator)
  • Harri Juhani Lähdesmäki (Creator)
  • Andreas Beyer (Creator)
  • Manu Harju (Creator)
  • Sharif Mahmud Hasan Chowdhury (Creator)
  • Kalle Olavi Leinonen (Creator)
  • Christophe Roos (Creator)
  • Olli Yli-Harja (Creator)



    Molecular interaction networks establish all cell biological processes. The networks are under intensive research that is facilitated by new high-throughput measurement techniques for the detection, quantification, and characterization of molecules and their physical interactions. For the common model organism yeast Saccharomyces cerevisiae, public databases store a significant part of the accumulated information and, on the way to better understanding of the cellular processes, there is a need to integrate this information into a consistent reconstruction of the molecular interaction network. This work presents and validates RefRec, the most comprehensive molecular interaction network reconstruction currently available for yeast. The reconstruction integrates protein synthesis pathways, a metabolic network, and a protein-protein interaction network from major biological databases. The core of the reconstruction is based on a reference object approach in which genes, transcripts, and proteins are identified using their primary sequences. This enables their unambiguous identification and non-redundant integration. The obtained total number of different molecular species and their connecting interactions is ∼67,000. In order to demonstrate the capacity of RefRec for functional predictions, it was used for simulating the gene knockout damage propagation in the molecular interaction network in ∼590,000 experimentally validated mutant strains. Based on the simulation results, a statistical classifier was subsequently able to correctly predict the viability of most of the strains. The results also showed that the usage of different types of molecular species in the reconstruction is important for accurate phenotype prediction. In general, the findings demonstrate the benefits of global reconstructions of molecular interaction networks. With all the molecular species and their physical interactions explicitly modeled, our reconstruction is able to serve as a valuable resource in additional analyses involving objects from multiple molecular -omes. For that purpose, RefRec is freely available in the Systems Biology Markup Language format.
    Table S1: Unconditionally essential genes and their enrichments in GO Biological Processes.
    Koska saatavilla2017
    JulkaisijaTampere University of Technology

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