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Predicting Cis-Element Responses to Cell Signaling in Red Blood Cell Precursors [ER RNA-seq]

GSE314034 Homo sapiens Expression profiling by high throughput sequencing 6 samples Submitted 2026/05/27 Platform GPL18573
Summary
Chromatin signatures at cis-regulatory elements can predict how they regulate transcription. However, accurate cell type-specific prediction of functional cis-elements remains a significant computational challenge due to the lack of context regarding the role of environmental stimuli that may alter activity. Most existing datasets use static molecular and sequence features which do not evaluate cis-element responses to extracellular cues. To investigate chromatin changes mediated by Kit/SCF, we performed ATAC-seq and RNA-seq in acutely SCF stimulated HUDEP-2 cells and mapped enhancer-promoter interactions using existing datasets. The top Kit-predictive features included Inflammatory Response (JUN, JUND, ATF2, ATF3, EGR1), blood cell maintenance (RUNX1) and chromatin remodelers/transcription factors (THAP1, MXI1, PKNOX1, CTCF). EGR1 - a transcription factor which regulates proliferation and differentiation - was 37-fold upregulated after SCF treatment. Combined with ATAC-seq footprinting data, this suggested Kit transcriptional targets may be EGR1 dependent. To distinguish EGR1-sensitive from EGR1-insensitive KREs, we compared feature occupancy and selected evolutionarily conserved regions in each category. Understanding KREs' roles at a systems-level can also provide insights regarding how chromatin occupancy and transcription reorganizes signal responses. Dysfunctional KREs may contribute to chromatin misregulation in hematologic malignancies, or chemoresistance. any of our predicted KRE target genes have poorly described or unknown functions, which provide numerous in-roads to discover genetic, molecular, and cellular regulators of erythropoiesis.
Published in
Predictive modeling of signal-responsive cis-elements in human red blood cell precursors
Dogiparthi VR, Chee L, Roy P et al. · Nucleic acids research 2026 · PMID 42165135 · doi:10.1093/nar/gkag505
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Also filed as BioProject PRJNA1389635 and SRA study SRP655788. Searching any of these in the dataset finder brings you back here.

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