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转录组软件的结果显示,不同的商业管道之间存在显著的差异.
Cung Nawl Thawng1, Geoffrey Battle Smith2
1Biology Department and Molecular Biology Program, New Mexico State University, Las Cruces, NM, USA.
BMC genomics
|November 3, 2023
概括
选择合适的转录组分析软件对于准确的结果至关重要. DNAstar-D (Deseq2) 提供了一种更保守的方法来分析基因表达,特别是对于对低水平辐射的微妙生物反应.
科学领域:
- 环境科学 环境科学
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
背景情况:
- 研究对低水平和背景辐射的生物反应.
- 之前的一项研究确定了DNAstar-D作为E. coli和C. elegans中差异基因表达分析的保守工具.
研究的目的:
- 使用不同的软件包比较转录组对不同辐射剂量率的反应.
- 评估DNAstar-D与其他软件 (CLC,DNAstar-E,Azenta) 在分析RNA-Seq数据中的性能.
主要方法:
- 利用了来自三种模型生物的RNA-Seq数据:大肠杆菌,C. elegans和埃及甲虫.
- 分析了对不同剂量速率的自然辐射源的转录组反应.
- 在多个软件管道 (DNAstar-D,CLC,DNAstar-E,Azenta) 中比较差异性基因表达结果.
主要成果:
- 与CLC,DNAstar-E和Azenta.E相比,DNAstar-D始终产生了较为保守的差异表达基因 (DEG) 数量和较低的折叠变化.
- 在CLC管道中,在DEG数量和跨研究的折叠变化方面,CLC管道显示了显著夸张的基因表达反应.
- 应用30阅读的最低切断标准减少了在大多数软件包中观察到的夸张反应.
结论:
- 转录组分析软件的选择对基因表达数据的解释产生重大影响.
- DNAstar-D (Deseq2) 提供了更加保守和现实的转录组表达模式,适合研究微妙的生物反应.
- 来自CLC等软件的过度基因表达发现可能需要仔细考虑和验证,特别是在低剂量辐射研究中.
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