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Background <p>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.</p> Results <p>Applying SEQSIM, we conducted a case study on <i>CABS1</i>, a gene associated with spermatogenesis and stress response but lacking well-defined functions. Our genome-wide promoter analysis revealed 41 distinct homology clusters, with <i>CABS1</i> residing within a cluster that includes promoters of genes such as <i>VWCE, SPOCK1</i>, and <i>TMX2</i>. 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 <i>CABS1</i> and nearby genes, implying evolutionary conservation and regulatory significance.</p> Conclusions <p>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.</p>

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SEQSIM: A novel bioinformatics tool for comparisons of promoter regions—a case study of calcium binding protein spermatid associated 1 (CABS1)

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年6月9日

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  • Joy Ramielle L. Santos,
  • Weijie Sun,
  • A. Dean Befus,
  • Marcelo Marcet-Palacios

摘要

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.