Identification of gene co-regulatory modules and associated cis-elements involved in degenerative heart disease

Abstract

BackgroundCardiomyopathies, degenerative diseases of cardiac muscle, are among the leading causes of death in the developed world. Microarray studies of cardiomyopathies have identified up to several hundred genes that significantly alter their expression patterns as the disease progresses. However, the regulatory mechanisms driving these changes, in particular the networks of transcription factors involved, remain poorly understood. Our goals are (A) to identify modules of co-regulated genes that undergo similar changes in expression in various types of cardiomyopathies, and (B) to reveal the specific pattern of transcription factor binding sites, cis-elements, in the proximal promoter region of genes comprising such modules.MethodsWe analyzed 149 microarray samples from human hypertrophic and dilated cardiomyopathies of various etiologies. Hierarchical clustering and Gene Ontology annotations were applied to identify modules enriched in genes with highly correlated expression and a similar physiological function. To discover motifs that may underly changes in expression, we used the promoter regions for genes in three of the most interesting modules as input to motif discovery algorithms. The resulting motifs were used to construct a probabilistic model predictive of changes in expression across different cardiomyopathies.ResultsWe found that three modules with the highest degree of functional enrichment contain genes involved in myocardial contraction (n = 9), energy generation (n = 20), or protein translation (n = 20). Using motif discovery tools revealed that genes in the contractile module were found to contain a TATA-box followed by a CACC-box, and are depleted in other GC-rich motifs; whereas genes in the translation module contain a pyrimidine-rich initiator, Elk-1, SP-1, and a novel motif with a GCGC core. Using a naïve Bayes classifier revealed that patterns of motifs are statistically predictive of expression patterns, with odds ratios of 2.7 (contractile), 1.9 (energy generation), and 5.5 (protein translation).ConclusionWe identified patterns comprised of putative cis-regulatory motifs enriched in the upstream promoter sequence of genes that undergo similar changes in expression secondary to cardiomyopathies of various etiologies. Our analysis is a first step towards understanding transcription factor networks that are active in regulating gene expression during degenerative heart disease.

Depicting the Core Transcriptome Modulating Multiple Abiotic Stresses Responses in Sesame (Sesamum indicum L.)

“…To further pinpoint the master players among the large number of detected TFs, we identified in the promoter of genes within each module, the enriched putative cis -regulatory motifs. Previous works in yeast and human have demonstrated that genes with similar expression patterns are regulated by the same set of TFs, and therefore are likely to have similar cis -regulatory motifs in their upstream promoter regions [91,92]. Our study corroborated well these conclusions and unraveled for each module the master TFs that may regulate the gene expression under specific abiotic stress (Figure 4).…”

A Rapid, Extensive, and Transient Transcriptional Response to Estrogen Signaling in Breast Cancer Cells

“…Computations were performed in R, using the same pipeline we described previously (Danko and Pertsov, 2009). …”

“…Raw CEL files from existing microarray datasets collected using the Affymetrix U133 platform were analyzed together using a previously described pipeline (Danko and Pertsov, 2009). Normalized microarray data were compared to read counts mapping to the +1 to +13 kb window of genes regulated by E2 during at least one point in the GRO-seq time course.…”

Dynamic reorganization of the AC16 cardiomyocyte transcriptome in response to TNFα signaling revealed by integrated genomic analyses

“…Other motifs are consistent with previous literature as well. For example, Sp1 has consistently been found in searches for cardiac transcription factors and is associated with the regulation of many cardiac genes [ 37 - 39 ], KLF4 is a critical transcriptional regulator of stress responses in cardiomyocytes [ 25 - 27 ], Smad3 is a key mediator of cardiac inflammation and fibrosis [ 40 ], and ZNF143 is critical for heart development in zebrafish [ 41 ].…”