同适应性网络连接性确定了在开放的细菌泛基组中模糊的基本区域
Pan Zhang1,2,3, Biliang Zhang2,4, Yuan-Yuan Ji1,2
1State Key Laboratory of Plant Environmental Resilience, and College of Biological Sciences China Agricultural University Beijing China.
mLife
|July 1, 2024
概括
这项研究揭示了Sinorhizobium中的许多核心基因不是必不可少的,挑战了进化假设. 一个强大的隐藏马尔科夫模型 (HMM) 方法确定了必需的基因和辅助基因,突出了泛基组内的模糊必需区域.
科学领域:
- 微生物基因组学 微生物基因组学
- 进化生物学是进化的生物学.
- 系统生物学 系统生物学
背景情况:
- 泛基因组研究通常假定核心基因是必不可少的,辅助基因是不可或缺的.
- 这种假设在泛基因组背景下缺乏广泛的遗传验证.
- 了解基因关键性对于 prokaryotic pangenome 分析至关重要.
研究的目的:
- 通过使用泛基因Tn-seq.进行基因测试,以测试Sinorhizobium中核心和辅助基因的基本性.
- 评估和建立最强大的方法来分配健身类别.
- 探索基因基本性,辅助/核心状态和功能类别之间的关系.
主要方法:
- 泛基 Tn-seq 分析是在营养丰富的介质中对 Sinorhizobium 菌株进行的.
- 使用隐藏马尔科夫模型 (HMM),贝叶斯式和蒙特卡洛方法分析了每个菌株的三个独立突变库.
- 基于HMM的方法之所以被选中,是因为它在分类健身基因 (必需基因,优势基因,缺点基因,非必需基因) 方面的稳定性.
主要成果:
- 基本 (ES) 和优势 (GA) 基因在核心基因中被丰富,而非基本 (NE) 基因在辅助基因中被过度代表.
- 与核心ES/GA基因相比,辅助ES/GA基因表现出较低的健康效应.
- 在3284个核心基因中,1599个基因表现出跨菌株的差异性实质性,表明了一个模糊的基本区域.
结论:
- 这项研究挑战了核心基因作为普遍必不可少的传统观点.
- HMM方法为分析Tn-seq数据和对基因适应性进行分类提供了强大的方法.
- 协同适应性网络分析对于理解复杂的 prokaryotic pangenomes 的遗传基础是强大的.
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