Pleiotropy, homeostasis, and functional networks based on assays of cardiovascular traits in genetically randomized populations

Description

A major problem in studying biological traits is understanding how genes work together to provide organismal structures and functions. Conventional reductionist paradigms attribute functions to particular proteins, motifs, and amino acids. An equally important but harder problem involves the synthesis of data at fundamental levels of biological systems to understand functionality at higher levels. We used subtle, naturally occurring, multigenic variation of cardiovascular (CV) properties in a panel of genetically randomized strains that are derived from the A/J and C57BL/6J strains of mice to perturb CV functions in nonpathologic ways. In this proof-of-concept study, computational analysis correctly identified the known relations among CV properties and revealed functionality at higher levels of the CV system. The network was then used to account for pleiotropies and homeostatic responses in single gene mutant mice and in mice treated with a pharmacologic agent (anesthesia). The CV network accounted for functional dependencies in complementary ways to the insights obtained from genetic networks and biochemical pathways. These networks are therefore an important approach for defining and characterizing functional relations in complex biological systems in health and disease.

Reference

Pleiotropy, homeostasis, and functional networks based on assays of cardiovascular traits in genetically randomized populations
Nadeau JH, Burrage LC, Restivo J, Pao YH, Churchill G, Hoit BD.
Genome Res. 2003 Sep;13(9):2082-91. PMCID: PMC403692. [ Full Text ]

Datasets


Click the following links to download the data file and Matlab scripts. Save them in the same directory and run the script. Note that matplot.m is a function called by the script.

data file
Script
matplot.m