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Quantifying the impact of genetic mutations on enhancer dynamics [RNAseq]

ABSTRACT: Transcriptional regulation is mediated by enhancers, yet how genetic perturbations alter enhancer activity and gene expression remains unclear. We developed UDI-UMI-STARR-seq, integrating dual indexes and unique molecular identifiers, and combined it with RNA-seq to profile perturbation-induced changes in enhancer activity and target gene expression. We applied this approach to 253,632 fragments representing 46,142 cell type-specific candidate enhancer regions and assessed the impact of CRISPR/Cas9-mediated deletion of six transcription factors (ATF2, CTCF, FOXA1, LEF1, TCF7L2, and SCRT1). We identified fragments that were repressed or induced, often through p53 family motifs. Enhancer-gene mapping revealed TF-specific programs, including repression of Wnt/p53 targets after ATF2 or LEF1 loss. A deep learning model trained on enhancer sequences recapitulated enhancer grammar, including cooperative motif syntax and flanking sequence context. Applying this framework to 16p12.1 deletion identified responsive fragments linked to genes involved in neuronal function, providing a scalable readout of enhancer dynamics generalizable to genetic mutations.

ORGANISM(S): Homo sapiens

PROVIDER: GSE345629 | GEO | 2026/09/04

REPOSITORIES: GEO

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Quantifying the impact of genetic mutations on enhancer dynamics [STARRseq_PRJNA879724]

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