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POSTER 72 - BUILDING HEARTS FROM COMPUTATIONAL ANALYSIS OF CARDIOVASCULAR TRAITS IN GENETICALLY RANDOMIZED POPULATIONS
J Nadeau
Genetics, CWRU
1) Burrage L,
2) Churchill G, 1) Hill A, 3) Restivo J,
4) Shao H, 4) Pao Y, 3) Hoit B
1) Genetics, CWRU,
2) Jackson Laboratory, 3) Medicine, CWRU, 4) Electrical Engineering
and Computer Science, CWRU
A major problem in studying biological traits is understanding how genes work together to provide organismal structures and functions. Conventional approaches usually involve a reductionist approach where specific functions are attributed to particular genes, motifs and amino acids. The equally important but harder problem involves the synthesis of information to understand functionality at higher levels. We have developed a computational method, called Phenotype Segregation Networks (PSNs), that uses assays of component traits to learn about higher level systems. We used subtle, naturally-occurring, multigenic variation of cardiovascular(CV) properties in the A/J and C57BL/6J strains and the AXB / BXA RI strains to perturb CV functions in non-pathologic ways. In this proof-of-concept study, computational analysis correctly identified the known functional relations among CV properties and revealed key aspects of heart functions. This PSN was then used to account for pleiotropies in single gene mutant mice and the effects of pharmacologic treatments. PSNs account for functional dependencies in ways that genetic networks and biochemical pathways do not and are therefore an important complementary approach for defining and characterizing functional relations in complex biological systems in health and disease.
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