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XB-LAB-413

Marcotte Lab

Protein organization & function and the link between genes and traits & diseases.

ICMB Univeristy of Texas at Austin

Institute for Cellular and Molecular Biology
The University of Texas at Austin
2500 Speedway, MBB 3.210
Austin, TX
78712, USA

www.marcottelab.org/index.php/Main_Page

General/Lab Phone: 512-232-3919
General/Lab Fax: 512-232-3472

People

Marcotte, Edward (Principal Investigator/Director)

Research Area

Our group studies the large-scale organization of proteins, essentially trying to reconstruct the 'wiring diagrams' of cells by learning how all of the proteins encoded by a genome are associated into functional pathways, systems, and networks. Such models let us better define the functions of genes, and to link genes to traits and diseases.

Additional Information

Bioinformatics of protein function and interactions: We've discovered a number of features of genomes that allow us to predict functions for proteins that have never been experimentally characterized. Using these techniques and information from over 30 fully sequenced genomes, we were able to calculate some of the first genome-wide predictions of protein function, finding very preliminary function for over half the 2,500 uncharacterized genes of yeast. Now, with hundreds of genomes in hand, we're extending these techniques, as well as asking fundamental questions about the evolution of protein interactions and the evolution of genomes. Rational identification of genes affecting traits and diseases: Using the gene networks and other computational tools, we've now gained some ability to rationally predict the consequences to an organism of mutating or interrupting a specific gene. This means that by using these tools, we can often select a small set of candidate genes to be implicated in a particular disease or trait. We've now experimentally validated >100 such candidate genes for diverse traits in a wide range of organisms, including yeast, worms, Arabidopsis, C. elegans, frogs, mice, and humans. For example, in yeast we've used network models to discover a large number of new ribosome biogenesis genes (collaborating with Arlen Johnson), as well as genes controlling such features as cell size. In animals, e.g. using our worm gene network models developed with collaborators Ben Lehner and Andy Fraser, we could successfully identify new genes controlling longevity, as well as genes capable of suppressing the loss of the Retinoblastoma tumor suppressor, thus 'curing' worms of model tumors. In Arabidopsis, with now ex-postdoc Insuk Lee and collaborator Sue Rhee, we could rationally identify new genes regulating root growth, drought resistance, and seedling pigmentation. In vertebrates, working with the Wallingford and Finnell labs, we've been able to use gene network models to help assign functions to a birth defect gene, as well as to identify entirely new birth defect genes, confirming their roles in vivo.

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Major funding for Xenbase is provided by the National Institute of Child Health and Human Development, grant P41 HD064556