To elucidate the structure, function, and evolution of large genetic networks is the ultimate goal of functional genomics. Progress towards this goal will not only lead to a deep understanding of all living things, but also to profound insights into the origins of human disease. Recently, the first genome-scale data on a large genetic network has become available, the network of all pairwise protein interactions in the yeast Saccharomyces cerevisiae. This data provides the foundation of the proposed work, a structural and functional characterization of this network, and an explanation of its structure in terms of its evolution via interaction turnover and gene duplication.
Aim 1 is a global characterization of the yeast protein interaction network (YPIN). A graph theoretical framework will be developed and used to address questions such as the following: Is the YPIN a connected network? If not, how many subnets does it have? Does it belong to any known category of graph? Do interacting proteins or proteins in the same subnet have similar spatiotemporal expression patterns? Are genes whose products have many protein interaction partners more or less likely to undergo gene duplication? Aim 2regards the evolution of the YPIN by gene duplications. The majority of genes in the YPIN are members of gene families. At what rate do duplicate genes change their interaction partners or become associated with different subnets after duplication? Preliminary results show that the YPIN is structurally similar to a random network, and that the rate of turnover in protein interactions is high. They also show that it is possible to estimate the rate at which new interactions evolve.
Aim 3 finally integrates all this information to provide a mathematical model for evolution of the YPIN. This model will explain all structural features of the YPIN as a function of the rate of interaction loss and interaction gain, the rate of gene duplications in the YPIN, and the rate of interaction turnover after gene duplication. The information required in the model can be estimated from genomic sequence, gene expression, and protein interaction data. Geneticists and evolutionary biologists have speculated for decades on the structure and evolution of large genetic networks. The proposed work will put this speculation to an end for a key genetic network, some of whose conserved components are also involved in the etiology of human disease.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM063882-02
Application #
6520577
Study Section
Genome Study Section (GNM)
Program Officer
Eckstrand, Irene A
Project Start
2001-07-01
Project End
2006-06-30
Budget Start
2002-07-01
Budget End
2003-06-30
Support Year
2
Fiscal Year
2002
Total Cost
$118,400
Indirect Cost
Name
University of New Mexico
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
829868723
City
Albuquerque
State
NM
Country
United States
Zip Code
87131
Felix, M-A; Wagner, A (2008) Robustness and evolution: concepts, insights and challenges from a developmental model system. Heredity 100:132-40
Martin, Olivier C; Wagner, Andreas (2008) Multifunctionality and robustness trade-offs in model genetic circuits. Biophys J 94:2927-37
Ciliberti, S; Martin, O C; Wagner, A (2007) Innovation and robustness in complex regulatory gene networks. Proc Natl Acad Sci U S A 104:13591-6
Wagner, Andreas; Wright, Jeremiah (2007) Alternative routes and mutational robustness in complex regulatory networks. Biosystems 88:163-72
Ciliberti, Stefano; Martin, Olivier C; Wagner, Andreas (2007) Robustness can evolve gradually in complex regulatory gene networks with varying topology. PLoS Comput Biol 3:e15
Gilchrist, Michael A; Coombs, Daniel (2006) Evolution of virulence: interdependence, constraints, and selection using nested models. Theor Popul Biol 69:145-53
Wagner, Andreas (2006) Periodic extinctions of transposable elements in bacterial lineages: evidence from intragenomic variation in multiple genomes. Mol Biol Evol 23:723-33
Gilchrist, Michael A; Wagner, Andreas (2006) A model of protein translation including codon bias, nonsense errors, and ribosome recycling. J Theor Biol 239:417-34
Gilchrist, Michael A; Sulsky, Deborah L; Pringle, Anne (2006) Identifying fitness and optimal life-history strategies for an asexual filamentous fungus. Evolution 60:970-9
Wagner, Andreas (2006) Cooperation is fleeting in the world of transposable elements. PLoS Comput Biol 2:e162

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