SEQSIM:一种用于比较启动子区域的新型生物信息学工具——以钙结合蛋白精细胞相关蛋白1 (CABS1)为例。

IF 3.3 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Joy Ramielle L Santos, Weijie Sun, A Dean Befus, Marcelo Marcet-Palacios
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引用次数: 0

摘要

背景:理解转录调控需要对启动子区域进行深入分析,启动子区域包含重要的顺式调控元件,如核心启动子、增强子和沉默子。尽管这些区域具有重要意义,但由于数据复杂性和计算限制,全基因组表征仍然是一个挑战。传统的生物信息学工具,如Clustal Omega,在处理大量数据集方面面临局限性,阻碍了全面分析。为了弥补这一差距,我们开发了SEQSIM,这是一种利用优化的Needleman-Wunsch算法进行高速比较的序列比较工具。SEQSIM可以在一个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。结果:应用SEQSIM,我们对CABS1进行了案例研究,CABS1是一个与精子发生和应激反应相关的基因,但缺乏明确的功能。我们的全基因组启动子分析揭示了41个不同的同源簇,CABS1位于一个包括VWCE、SPOCK1和TMX2等基因启动子的簇中。这些关联表明潜在的共同监管网络。此外,我们的研究结果揭示了保守的启动子基序和远程调控序列,包括CABS1和附近基因共享的LINE-1转座元件片段,这意味着进化保护和调控意义。结论:这些结果提供了潜在的基因调控机制,增强了我们对转录控制的理解,并为功能探索提供了新的途径。结合SEQSIM的未来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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SEQSIM: A novel bioinformatics tool for comparisons of promoter regions-a case study of calcium binding protein spermatid associated 1 (CABS1).

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.

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来源期刊
BMC Bioinformatics
BMC Bioinformatics 生物-生化研究方法
CiteScore
5.70
自引率
3.30%
发文量
506
审稿时长
4.3 months
期刊介绍: BMC Bioinformatics is an open access, peer-reviewed journal that considers articles on all aspects of the development, testing and novel application of computational and statistical methods for the modeling and analysis of all kinds of biological data, as well as other areas of computational biology. BMC Bioinformatics is part of the BMC series which publishes subject-specific journals focused on the needs of individual research communities across all areas of biology and medicine. We offer an efficient, fair and friendly peer review service, and are committed to publishing all sound science, provided that there is some advance in knowledge presented by the work.
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