YeastNet v3: a public database of data-specific and integrated functional gene networks for Saccharomyces cerevisiae

Saccharomyces cerevisiae, i.e. baker’s yeast, is a widely studied model organism in eukaryote genetics because of its simple protocols for genetic manipulation and phenotype profiling. The high abundance of publicly available data that has been generated through diverse ‘omics’ approaches has led to the use of yeast for many systems biology studies, including large-scale gene network modeling to better understand the molecular basis of the cellular phenotype. We have previously developed a genome-scale gene network for yeast, YeastNet v2, which has been used for various genetics and systems biology studies. Here, we present an updated version, YeastNet v3 (available at http://www.inetbio.org/yeastnet/), that significantly improves the prediction of gene–phenotype associations. The extended genome in YeastNet v3 covers up to 5818 genes (∼99% of the coding genome) wired by 362 512 functional links. YeastNet v3 provides a new web interface to run the tools for network-guided hypothesis generations. YeastNet v3 also provides edge information for all data-specific networks (∼2 million functional links) as well as the integrated networks. Therefore, users can construct alternative versions of the integrated network by applying their own data integration algorithm to the same data-specific links.

[1]  Susumu Goto,et al.  KEGG for integration and interpretation of large-scale molecular data sets , 2011, Nucleic Acids Res..

[2]  Rob Jelier,et al.  Predicting phenotypic variation in yeast from individual genome sequences , 2011, Nature Genetics.

[3]  In suk Lee,et al.  Network approaches to the genetic dissection of phenotypes in animals and humans , 2013 .

[4]  Insuk Lee,et al.  JiffyNet: a web-based instant protein network modeler for newly sequenced species , 2013, Nucleic Acids Res..

[5]  A. Fraser,et al.  Predicting genetic modifier loci using functional gene networks. , 2010, Genome research.

[6]  Taro L. Saito,et al.  High-dimensional and large-scale phenotyping of yeast mutants. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[7]  Tao Xu,et al.  Role of Heme in the Antifungal Activity of the Azaoxoaporphine Alkaloid Sampangine , 2007, Eukaryotic Cell.

[8]  Robert P. St.Onge,et al.  The Chemical Genomic Portrait of Yeast: Uncovering a Phenotype for All Genes , 2008, Science.

[9]  G. Sumara,et al.  A Probabilistic Functional Network of Yeast Genes , 2004 .

[10]  Gary D. Bader,et al.  Cytoscape Web: an interactive web-based network browser , 2010, Bioinform..

[11]  T. Ideker,et al.  A gene ontology inferred from molecular networks , 2012, Nature Biotechnology.

[12]  Insuk Lee,et al.  Rational Extension of the Ribosome Biogenesis Pathway Using Network-Guided Genetics , 2009, PLoS biology.

[13]  Kriston L. McGary,et al.  Open Access Method , 2007 .

[14]  Andrew D. Ellington,et al.  Systematic Definition of Protein Constituents along the Major Polarization Axis Reveals an Adaptive Reuse of the Polarization Machinery in Pheromone-Treated Budding Yeast , 2008, Journal of proteome research.

[15]  E. Marcotte,et al.  An Improved, Bias-Reduced Probabilistic Functional Gene Network of Baker's Yeast, Saccharomyces cerevisiae , 2007, PloS one.