Santos Joy Ramielle L, Sun Weijie, Befus A Dean, Marcet-Palacios Marcelo
Department of Medicine, University of Alberta, Edmonton, T6G 2R3, Canada.
Department of Computer Sciences, University of Alberta, Edmonton, T6G 2E1, Canada.
BMC Bioinformatics. 2025 Jun 9;26(1):156. doi: 10.1186/s12859-025-06160-x.
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.
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.
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.
理解转录调控需要对启动子区域进行深入分析，启动子区域包含核心启动子、增强子和沉默子等重要的顺式调控元件。尽管这些区域很重要，但由于数据复杂性和计算限制，全基因组表征仍然是一项挑战。像Clustal Omega这样的传统生物信息学工具在处理大量数据集时存在局限性，阻碍了全面分析。为了弥补这一差距，我们开发了SEQSIM，这是一种序列比较工具，利用优化的Needleman-Wunsch算法进行高速比较。SEQSIM可以在一小时内分析完整的人类启动子数据集，克服了先前的计算障碍。
应用SEQSIM，我们对CABS1进行了一项案例研究，CABS1是一个与精子发生和应激反应相关但功能尚未明确的基因。我们的全基因组启动子分析揭示了41个不同的同源簇，CABS1位于一个包含VWCE、SPOCK1和TMX2等基因启动子的簇中。这些关联表明了潜在的共调控网络。此外，我们的研究结果揭示了保守的启动子基序和长程调控序列，包括CABS1和附近基因共享的LINE-1转座子元件片段，这意味着进化保守性和调控意义。
这些结果为潜在的基因调控机制提供了见解，增强了我们对转录控制的理解，并为功能探索提出了新的途径。未来纳入SEQSIM的研究可以阐明影响基因表达的共调控网络和染色质相互作用。
