In Silico CRISPR Restoration of F7 Promoter Activity in Hereditary Factor VII Deficiency

Hereditary Factor VII (FVII) deficiency is associated with reduced F7 gene expression and impaired coagulation, and regulatory mechanisms controlling F7 transcription remain incompletely characterized. This study aimed to computationally explore whether restoration of predicted HNF4α binding at the F7 promoter, through transcription factor modulation, promoter motif correction, or CRISPR activation (CRISPRa)-mediated epigenetic regulation, could theoretically enhance predicted F7 transcription in hereditary FVII deficiency. An entirely in silico pipeline was developed to characterize the F7 promoter regulatory landscape by identifying conserved transcription factor binding motifs using JASPAR, FIMO, and UCSC Genome Browser datasets. Liver expression correlations were evaluated using GTEx transcriptomic data, while chromatin accessibility and regulatory context were assessed using ENCODE ChIP-seq, ATAC-seq, and ChromHMM/Segway annotations. A hepatic regulatory network was constructed in CellDesigner to simulate the predicted effects of HNF4α loss on F7 transcription over a 24-h period. Six high-confidence HNF4α binding motifs were identified within the proximal F7 promoter, including three regions overlapping known disease-associated variants. Liver expression analyses demonstrated positive correlations between F7 and HNF4A (r = 0.68) and HNF1A (r = 0.61). Computational modeling predicted that CRISPRa targeting of HNF4α-associated regulatory regions could increase simulated F7 transcription toward approximately 87% of wild-type levels under the modeled conditions, with predicted target specificity. Overall, this purely computational study presents an integrated multi-omic framework for prioritizing promoter-targeted regulatory strategies in hereditary FVII deficiency. By combining transcription factor motif analysis, chromatin annotation, transcriptomic correlation, regulatory network modeling, and CRISPR guide prioritization within a unified pipeline, the study generates experimentally testable hypotheses while providing a systematic approach that extends beyond previous single-variant or isolated experimental analyses.