The Importance of Age and High Degree, in Protein-Protein Interaction Networks

Here we present an in-depth analysis of the protein age patterns found in the edge and triangle subgraphs of the yeast protein-protein interaction network (PIN). We assess their statistical significance both according to what would be expected by chance given the node frequencies found in the yeast PIN, and also, for the case of triangles, given the age frequencies observed in the currently available pairwise data. We find that pairwise interactions between Old proteins are over-represented even when controlling for high degree, and triangle interactions between Old proteins are over-represented even when controlling for pairwise interaction frequencies. There is evidence for negative selection of interactions between Middle-aged and Old proteins within triangles, despite pairwise Middle-Old interactions being common. Most triangles consist solely of vertices with high degree. Our findings point towards an architecture of the yeast PIN that is highly heterogeneous, having connected clumps which contain a large number of interacting Old proteins along with selective age-dependent interaction patterns. Supplementary Material is available online (www.liebertonline.com/cmb).

[1]  Z N Oltvai,et al.  Evolutionary conservation of motif constituents in the yeast protein interaction network , 2003, Nature Genetics.

[2]  Shmuel Sattath,et al.  How reliable are experimental protein-protein interaction data? , 2003, Journal of molecular biology.

[3]  Adam J. Smith,et al.  The Database of Interacting Proteins: 2004 update , 2004, Nucleic Acids Res..

[4]  Wan Kyu Kim,et al.  Age-Dependent Evolution of the Yeast Protein Interaction Network Suggests a Limited Role of Gene Duplication and Divergence , 2008, PLoS Comput. Biol..

[5]  Debra Goldberg,et al.  Improving evolutionary models of protein interaction networks , 2011, Bioinform..

[6]  Raya Khanin,et al.  How Scale-Free Are Biological Networks , 2006, J. Comput. Biol..

[7]  S. Tavaré,et al.  Ancestral Inference in Population Genetics , 1994 .

[8]  Peer Bork,et al.  Not Comparable, But Complementary , 2008, Science.

[9]  Stefan Bornholdt,et al.  Topology of biological networks and reliability of information processing , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[10]  K. Sneppen,et al.  Specificity and Stability in Topology of Protein Networks , 2002, Science.

[11]  Charlotte M Deane,et al.  Evolutionary analysis reveals low coverage as the major challenge for protein interaction network alignment. , 2010, Molecular bioSystems.

[12]  S. Shen-Orr,et al.  Network motifs: simple building blocks of complex networks. , 2002, Science.

[13]  Eugene V Koonin,et al.  The universal distribution of evolutionary rates of genes and distinct characteristics of eukaryotic genes of different apparent ages , 2009, Proceedings of the National Academy of Sciences.

[14]  Sarel J Fleishman,et al.  Comment on "Network Motifs: Simple Building Blocks of Complex Networks" and "Superfamilies of Evolved and Designed Networks" , 2004, Science.

[15]  Erik L. L. Sonnhammer,et al.  InParanoid 7: new algorithms and tools for eukaryotic orthology analysis , 2009, Nucleic Acids Res..

[16]  Gesine Reinert,et al.  How threshold behaviour affects the use of subgraphs for network comparison , 2010, Bioinform..

[17]  David R. Cox,et al.  PRINCIPLES OF STATISTICAL INFERENCE , 2017 .

[18]  Michael E. Cusick,et al.  Yeast Protein Interactome topology provides framework for coordinated-functionality , 2006 .

[19]  Wen-Hsiung Li,et al.  Evolution of the yeast protein interaction network , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[20]  Lin Hou,et al.  Evidence for the additions of clustered interacting nodes during the evolution of protein interaction networks from network motifs , 2011, BMC Evolutionary Biology.

[21]  Colin Cooper,et al.  The degree distribution of the generalized duplication model , 2006, Theor. Comput. Sci..

[22]  Alessandro Vespignani,et al.  Evolution thinks modular , 2003, Nature Genetics.

[23]  Nicolas Thierry-Mieg,et al.  New insights into protein-protein interaction data lead to increased estimates of the S. cerevisiae interactome size , 2010, BMC Bioinformatics.

[24]  P. Srere Protein interactions. , 1999, Methods.

[25]  Joel S. Bader,et al.  Precision and recall estimates for two-hybrid screens , 2008, Bioinform..

[26]  Süleyman Cenk Sahinalp,et al.  Not All Scale-Free Networks Are Born Equal: The Role of the Seed Graph in PPI Network Evolution , 2006, Systems Biology and Computational Proteomics.

[27]  Charlotte M. Deane,et al.  The function of communities in protein interaction networks at multiple scales , 2009, BMC Systems Biology.

[28]  Gesine Reinert,et al.  Predicting and Validating Protein Interactions Using Network Structure , 2008, PLoS Comput. Biol..

[29]  L. Bonetta Protein–protein interactions: Interactome under construction , 2010, Nature.

[30]  Charlotte M. Deane,et al.  How old is your fold? , 2005, ISMB.

[31]  S. Tavaré Part I: Ancestral Inference in Population Genetics , 2004 .

[32]  E. S. Lander,et al.  Calculating the secrets of life: Applications of the mathematical sciences in molecular biology , 1995 .

[33]  Ioannis Xenarios,et al.  DIP: The Database of Interacting Proteins: 2001 update , 2001, Nucleic Acids Res..