Pleiotropy, Homeostasis, and Functional Networks Based on Assays of Cardiovascular Traits in Genetically Randomized Populations

Abstract

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.

The Collaborative Cross, a community resource for the genetic analysis of complex traits

“…genetic structure of the RI strains will enable us to establish networks of functionally important relationships within and among diverse sets of physiological and behavioral phenotypes 13,14 . Gene-environment interaction is a crucial problem in genetics, and a key contributor to most common diseases, which has been difficult to study in any mammalian population.…”

Heart failure: a complex clinical process interpreted by systems biology approach and network medicine

“…The design of this metabolic organization is robust, error-tolerant and represents a common pattern for the large-scale organization of interactions with which all living cells should comply (18). Nadeau et al (19) used a multigenic variation of cardiovascular properties in genetically randomized mice to perturb cardiovascular functions in the normal range of variation. In the described cardiovascular functions were included cardiac output, end-systolic left ventricular dimensions, septal wall thickness, and heartbeats per minute.…”

Functional network analysis of obese and lean Göttingen minipigs elucidates changes in oxidative and inflammatory networks in obese pigs

“…Correlation matrix of traits and statistical analysis A correlation matrix for all measured traits was calculated for both the lean and obese groups followed by permutation test or bootstrapping in order to identify the probability of having a true correlation at four different levels of significance (p<0.001, p<0.005, p<0.01 and p<0.05) using a customized Matlab script (Mathworks, Natick, MA, USA) based on a script kindly provided by G. A. Churchill [17]. A normality test was performed for each trait.…”

“…A comparable approach, but on a higher level of organisation, i.e. network analysis of functional physiological or phenotypical traits was described previously, showing promising results [17,23]. Multiple parameters or traits were measured ranging from anatomical and physical, cardiovascular, metabolic and inflammatory markers, which are all considered to reflect key processes in the aetiology of obesity and associated comorbidities.…”