Seqwin:微生物基因组中签名序列的超快速识别
Michael X Wang1,2, Bryce Kille1, Michael G Nute1
1Department of Computer Science, Rice University, Houston, 77005, USA.
bioRxiv : the preprint server for biology
|November 24, 2025
概括
Seqwin自动化微生物基因组签名发现,用于快速诊断. 这种开源工具有效地识别DNA签名,改善了在大型基因组集合中的病原体检测.
科学领域:
- 生物信息学是一种生物信息学.
- 基因组学就是基因组学.
- 微生物诊断 微生物诊断
背景情况:
- 聚合酶连锁反应 (PCR) 需要特定的微生物签名序列来进行准确的诊断.
- 现有的识别这些特征的方法受到越来越多可用的微生物基因组的限制.
研究的目的:
- 引入Seqwin,这是一个开源框架,用于自动化微生物基因组签名发现.
- 为了使敏感和准确的DNA签名识别能够进行强大的病原体检测.
主要方法:
- Seqwin构建了加权的泛基因组最小化图.
- 穿越算法识别了目标基因组中的频繁序列和非目标基因组中的罕见序列.
- 该框架可以适应序列变化和扩展到大型基因组集合.
主要成果:
- Seqwin发现了更多高质量的签名,而不是对*C. difficile*,*M.结核病*和*S. enterica*的替代方法.
- 对近15000个*S. enterica*基因组的分析,在不到10分钟的时间内产生了200多个候选签名.
- 与现有方法相比,Seqwin显示了较低的计算负担.
结论:
- Seqwin为微生物签名发现提供了一个可扩展的解决方案.
- 该框架有助于设计用于临床,环境和公共卫生应用的可靠诊断试验.
- 作为一个开源工具,Seqwin可用于学术用途.
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