Background: Understanding transcriptional regulation requires an in-depth analysis of promoter regions, which house vital cis-regulatory elements such as core promoters, enhancers, and silencers. Despite the significance of these regions, genome-wide characterization remains a challenge due to data complexity and computational constraints. Traditional bioinformatics tools like Clustal Omega face limitations in handling extensive datasets, impeding comprehensive analysis. To bridge this gap, we developed SEQSIM, a sequence comparison tool leveraging an optimized Needleman-Wunsch algorithm for high-speed comparisons. SEQSIM can analyze complete human promoter datasets in under an hour, overcoming prior computational barriers.
Results: Applying SEQSIM, we conducted a case study on CABS1, a gene associated with spermatogenesis and stress response but lacking well-defined functions. Our genome-wide promoter analysis revealed 41 distinct homology clusters, with CABS1 residing within a cluster that includes promoters of genes such as VWCE, SPOCK1, and TMX2. These associations suggest potential co-regulatory networks. Additionally, our findings unveiled conserved promoter motifs and long-range regulatory sequences, including LINE-1 transposable element fragments shared by CABS1 and nearby genes, implying evolutionary conservation and regulatory significance.
Conclusions: These results provide insight into potential gene regulation mechanisms, enhancing our understanding of transcriptional control and suggesting new pathways for functional exploration. Future studies incorporating SEQSIM could elucidate co-regulatory networks and chromatin interactions that impact gene expression.
Keywords: CABS1 gene regulation; Promoter sequence similarity; SEQSIM algorithm; chromatin architecture; transposable elements.
© 2025. The Author(s).