Learning More from Microarrays: Insights from Modules and Networks

Abstract

Global gene expression patterns can provide comprehensive molecular portraits of biologic diversity and complex disease states, but understanding the physiologic meaning and genetic basis of the myriad gene expression changes have been a challenge. Several new analytic strategies have now been developed to improve the interpretation of microarray data. Because genes work together in groups to carry out specific functions, defining the unit of analysis by coherent changes in biologically meaningful sets of genes, termed modules, improves our understanding of the biological processes underlying the gene expression changes. The gene module approach has been used in exploratory discovery of defective oxidative phosphorylation in diabetes mellitus and also has allowed definitive hypothesis testing on a genomic scale for the relationship between wound healing and cancer and for the oncogenic mechanism of cyclin D. To understand the genetic basis of global gene expression patterns, computational modeling of regulatory networks can highlight key regulators of the gene expression changes, and many of these predictions can now be experimentally validated using global chromatin-immunoprecipitation analysis.

Systems-Based Analyses of Brain Regions Functionally Impacted in Parkinson's Disease Reveals Underlying Causal Mechanisms

“…Gene enrichment analysis performed here allowed for the detection of modest, but coordinate expression changes in functionally related genes. The importance and value of network modeling have been detailed by others [30]–[32] and have been used to identify underlying pathological processes in neurodegenerative and non-neurodegenerative diseases [33].…”

Gene and protein expression in the myometrium in pregnancy and labor

“…A statistical test performed for each module relative to all other genes on the microarray calculates whether the degree of coordinate regulation is more than one would expect by chance. Therefore, a module of genes involved in a physiological process may be significantly down-regulated whereas each gene in the module under study may be transcriptionally down regulated by say only 20%, and thus not clearly detected at the individual gene level (Tierney et al 2003, Wong & Chang 2005. In addition, beside classical ideas regarding trans-regulation of gene expression, a greater number of hypotheses generated from regulatory networks analysis or cis-regulatory DNA elements analysis can be validated today in a high throughput fashion using chromatin-immunoprecipitation followed by microarray analysis (ChIPchip).…”

High-Throughput Single-Cell Analysis for Wound Healing Applications

“…14,15 DNA microarray provides a valuable tool for studying wound repair and regeneration, particularly in small animals, for which it is generally feasible to extract small tissue samples. 16 It has been used for numerous applications, such as comparing differentially expressed genes in keloids and normal skin, 17,18 as well as studying burns in small and large animal models. 19,20 Microarray-based methods may be used to compare the changes in gene expression over time throughout the wound healing process, 21,22 as well as to study these differences in wounds from various stages of early fetal development.…”