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Strongly regulated “super-target” transcription factors exert an outsized influence in microRNA-regulated networks

GSE289003 Homo sapiens Expression profiling by high throughput sequencing 14 samples 2026/01/12 GPL18573
Summary
To elucidate the role of microRNAs (miRNAs), it is essential to identify their direct post-transcriptional targets. However, identifying the most functionally significant targets is challenging due to factors such as the inherent limitations of predictive algorithms, the abundance of RNA interactions detected in co-precipitation studies, and the prevalence of non-productive targeting caused by weak interactions or unfavorable stoichiometries. We introduce the concept of 'super-targets'—genes whose regulation disproportionately drives miRNA functionality by virtue of both strong targeting and the critical role of the gene itself, such as a transcription factor whose disruption has broad downstream effects. A prime example is the reciprocal regulation between the miR-200 family and ZEB transcription factors, which governs the epithelial-mesenchymal status of cells. To assess the impact of such 'super-targeting,' we developed a system that isolates ZEB regulation from all other miR-200 activities. This approach reveals a complex network of transcriptional and post-transcriptional regulation, where miR-200’s ability to maintain an epithelial phenotype and suppress cell migration is fully dependent on the repression of ZEB1 and ZEB2, though other effects are ZEB-independent. Our findings suggest that a significant portion of miRNA regulatory impact may result from the potent targeting of a few key genes, highlighting that indirect transcriptional effects are a fundamental mechanism of miRNA function and likely more impactful than numerous modestly-regulated direct targets that otherwise dominate the publication landscape.
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NCBI GEO page ↗ Paper (PMID 41455985) ↗ {# Names what the click gives you. "Open in finder" meant nothing to a visitor who arrived from a search engine and has never seen the tool. #} Find more human RNA-seq datasets →
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