ISMARA: automated modeling of genomic signals as a democracy of regulatory motifs

Abstract

Accurate reconstruction of the regulatory networks that control gene expression is one of the key current challenges in molecular biology. Although gene expression and chromatin state dynamics are ultimately encoded by constellations of binding sites recognized by regulators such as transcriptions factors (TFs) and microRNAs (miRNAs), our understanding of this regulatory code and its context-dependent read-out remains very limited. Given that there are thousands of potential regulators in mammals, it is not practical to use direct experimentation to identify which of these play a key role for a particular system of interest. We developed a methodology that models gene expression or chromatin modifications in terms of genome-wide predictions of regulatory sites and completely automated it into a web-based tool called ISMARA (Integrated System for Motif Activity Response Analysis). Given only gene expression or chromatin state data across a set of samples as input, ISMARA identifies the key TFs and miRNAs driving expression/chromatin changes and makes detailed predictions regarding their regulatory roles. These include predicted activities of the regulators across the samples, their genome-wide targets, enriched gene categories among the targets, and direct interactions between the regulators. Applying ISMARA to data sets from well-studied systems, we show that it consistently identifies known key regulators ab initio. We also present a number of novel predictions including regulatory interactions in innate immunity, a master regulator of mucociliary differentiation, TFs consistently disregulated in cancer, and TFs that mediate specific chromatin modifications.

JQ1 affects BRD2-dependent and independent transcription regulation without disrupting H4-hyperacetylated chromatin states

“…We first performed motif activity response analysis (MARA) [32] using CAGE data and identified several candidate TFs that are responsible for up- or down-regulation of genes upon JQ1 treatment (Z-value ≥2.0) (Figure 6(A), Table S9). Among them are YY1 and E2F3, which show increased motif activity upon JQ1 treatment, and LEF1, FOSL1, and ZNF281, which show decreased motif activity (Figure 6(A)).…”

“…To identify key TFs, which might be involved in transcriptional regulation affected by JQ1 and the transcriptional activities of their target genes, we carried out MARA[32]. We submitted the bam files with mapped CAGE sequencing tags (hg19) to ISMARA online tool (The Integrated System for Motif Activity Response Analysis, http://ismara.unibas.ch/fcgi/mara).…”

Altered DNA methylation of glycolytic and lipogenic genes in liver of obese and type 2 diabetic patients

“…The Integrated System for Motif Activity Response Analysis (ISMARA) ISMARA was performed using the genome-wide mRNA expression data measured by Affymetrix array (see above) using methods for automated processing and modeling of the data as described earlier [3].…”

Integrative CAGE and DNA Methylation Profiling Identify Epigenetically Regulated Genes in NSCLC

“…4D). To identify key transcription factors responsible for observed expression changes, we used ISMARA online computational tool (35). ISMARA models gene expression by integrating predicted transcription factor-binding sites, and it identifies transcription factors most likely to drive the expression changes observed in given experiment.…”

“…The microarray CEL files were submitted to the ISMARA (The Integrated System for Motif Activity Response Analysis) online tool and selected MYC as the top transcription factor with highest activity significance (35). To find genes regulated by MYC, we obtained cMYC ChIP-seq peaks in A549 cells from ENCODE (36) and selected two nearest genes within 1 kb from the peak using GREAT 3.0.0 tool (37)…”