Variance of gene expression identifies altered network constraints in neurological disease

Mar, Jessica C., Matigian, Nicholas A., Mackay-Sim, Alan, Mellick, George D., Sue, Carolyn M., Silburn, Peter A., McGrath, John J., Quackenbush, John and Wells, Christine A. (2011) Variance of gene expression identifies altered network constraints in neurological disease. PLoS Genetics, 7 8: . doi:10.1371/journal.pgen.1002207


 
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Author Mar, Jessica C.
Matigian, Nicholas A.
Mackay-Sim, Alan
Mellick, George D.
Sue, Carolyn M.
Silburn, Peter A.
McGrath, John J.
Quackenbush, John
Wells, Christine A.
Title Variance of gene expression identifies altered network constraints in neurological disease
Journal name PLoS Genetics   Check publisher's open access policy
ISSN 1553-7390
1553-7404
Publication date 2011-08-01
Year available 2011
Sub-type Article (original research)
DOI 10.1371/journal.pgen.1002207
Open Access Status DOI
Volume 7
Issue 8
Total pages 12
Place of publication San Francisco, CA, United States
Publisher Public Library of Science
Language eng
Subject 1105 Ecology, Evolution, Behavior and Systematics
1312 Molecular Biology
1311 Genetics
2716 Genetics (clinical)
1306 Cancer Research
Abstract Gene expression analysis has become a ubiquitous tool for studying a wide range of human diseases. In a typical analysis we compare distinct phenotypic groups and attempt to identify genes that are, on average, significantly different between them. Here we describe an innovative approach to the analysis of gene expression data, one that identifies differences in expression variance between groups as an informative metric of the group phenotype. We find that genes with different expression variance profiles are not randomly distributed across cell signaling networks. Genes with low-expression variance, or higher constraint, are significantly more connected to other network members and tend to function as core members of signal transduction pathways. Genes with higher expression variance have fewer network connections and also tend to sit on the periphery of the cell. Using neural stem cells derived from patients suffering from Schizophrenia (SZ), Parkinson's disease (PD), and a healthy control group, we find marked differences in expression variance in cell signaling pathways that shed new light on potential mechanisms associated with these diverse neurological disorders. In particular, we find that expression variance of core networks in the SZ patient group was considerably constrained, while in contrast the PD patient group demonstrated much greater variance than expected. One hypothesis is that diminished variance in SZ patients corresponds to an increased degree of constraint in these pathways and a corresponding reduction in robustness of the stem cell networks. These results underscore the role that variation plays in biological systems and suggest that analysis of expression variance is far more important in disease than previously recognized. Furthermore, modeling patterns of variability in gene expression could fundamentally alter the way in which we think about how cellular networks are affected by disease processes.
Keyword Genetics & Heredity
Genetics & Heredity
GENETICS & HEREDITY
Q-Index Code C1
Q-Index Status Confirmed Code
Grant ID P50-HG004233
R01-LM010129
LX0882502
481945
Institutional Status UQ
Additional Notes Article # e1002207

 
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