Failure of cells to respond to DNA damage is a key mechanism of toxicity by environmental agents and a primary step in the onset of cancer. In this research program, we are using systematic approaches to map and model the genetic networks underlying the DNA damage response (DDR). Since DDR pathways are widely conserved, our studies bridge between Homo sapiens and the budding yeast Saccharomyces cerevisiae? impacting our knowledge of how genotoxic agents lead to pathogenesis in humans, coupled to a classic model organism for which new genetic technologies are readily developed and deployed. In the past five years of funding (NIH grant R01-ES14811), we made significant progress in identifying changes in yeast genetic, transcriptional, and signaling networks in response to DNA damage stress. We also developed innovative new technologies, including the experimental technique of ?differential? genetic interaction mapping and a computational approach to translate interaction networks into hierarchical, data-driven gene ontologies. In the next period of support, we will: (1) Significantly expand the yeast genetic interaction maps to include dynamic growth curves and specific DDR pathway readouts at high-throughput; (2) Develop and apply CRISPR technology to create parallel genetic network maps in human cell lines; and (3) Integrate all new and prior data to build comprehensive ontologies of DDR subsystems in yeast and human, which we will compare to systematically identify areas of conservation and divergence and validate specific DDR phenotypic predictions in mechanistic assays. This work moves us closer to a comprehensive structure/function model of the DDR. A growing set of DNA- damage-induced genetic networks and ontologies in model species and humans are important resources for understanding genetic polymorphisms that predispose an individual to environmental DNA damage and DDR- related diseases.

Public Health Relevance

We propose to develop comprehensive maps and models of signal transduction networks in response to DNA damage. These maps are a major biomedical resource which will be used to identify and target chemotherapeutic agents and their modulators.

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Research Project (R01)
Project #
5R01ES014811-12
Application #
9546715
Study Section
Genomics, Computational Biology and Technology Study Section (GCAT)
Program Officer
Balshaw, David M
Project Start
2005-09-26
Project End
2022-08-31
Budget Start
2018-09-01
Budget End
2019-08-31
Support Year
12
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of California, San Diego
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093
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Shen, John Paul; Ideker, Trey (2018) Synthetic Lethal Networks for Precision Oncology: Promises and Pitfalls. J Mol Biol 430:2900-2912
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Moder, Martin; Velimezi, Georgia; Owusu, Michel et al. (2017) Parallel genome-wide screens identify synthetic viable interactions between the BLM helicase complex and Fanconi anemia. Nat Commun 8:1238
Kramer, Michael H; Farré, Jean-Claude; Mitra, Koyel et al. (2017) Active Interaction Mapping Reveals the Hierarchical Organization of Autophagy. Mol Cell 65:761-774.e5
Srivas, Rohith; Shen, John Paul; Yang, Chih Cheng et al. (2016) A Network of Conserved Synthetic Lethal Interactions for Exploration of Precision Cancer Therapy. Mol Cell 63:514-25
Hofree, Matan; Carter, Hannah; Kreisberg, Jason F et al. (2016) Challenges in identifying cancer genes by analysis of exome sequencing data. Nat Commun 7:12096

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