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量化测序深度和参考基因组选择对四种牛RNA病毒的超转录组检测的影响
Barbara Brito1, Melinda Frost2, John Webster2
1Australian Institute for Microbiology & Infection, University of Technology Sydney, Ultimo, NSW 2007, Australia; Elizabeth Macarthur Agricultural Institute, New South Wales Department of Primary Industries and Regional Development, Menangle, NSW 2568, Australia.
Research in veterinary science
|March 7, 2026
概括
超转录组测序可以检测牛呼吸道病毒,但高基因组覆盖率需要深度测序和适当的参考基因组. 诊断效用取决于测序深度和参考序列的准确性,特别是对于不同的菌株.
科学领域:
- 兽医病毒学 兽医病毒学
- 下一代测序的测序方法
- 分子诊断学 分子诊断学
背景情况:
- 超转录组测序在各种环境中提供非向的RNA病毒检测.
- 评估其诊断潜力需要与已建立的方法比较,如qRT-PCR.
- 了解检测极限和基因组覆盖范围的局限性至关重要.
研究的目的:
- 评估四种牛呼吸道RNA病毒 (BCoV,BNV,IDV,BVDV-1) 的元转录组测序性能.
- 量化测序深度和参考基因组选择对病毒读取恢复和基因组覆盖的影响.
- 为使用元转录组学进行兽医诊断提供方法指南.
主要方法:
- 从鼻子抽样中获取的元转录基因数据的基于参考的映射.
- 测序深度的系统变化 (1,10,200万次阅读).
- NCBI RefSeq和研究组装的参考基因组的比较.
主要成果:
- 转录组学检测到BNV和BCoV在≥10M读取高的qRT-PCRCt值 (高达40),但要求完整性Ct<30.
- 检测IDV的敏感度较低,一些qRT-PCR阳性样本显示没有映射读数.
- BVDV-1的恢复高度依赖于参考;研究组装的基因组比NCBI RefSeq提高了检测能力,特别是对于分歧菌株.
结论:
- 测序深度和参考基因组选择显著影响转基因组病毒检测和兽医诊断中的覆盖范围.
- 检测具有高Ct值的病毒需要高的测序深度,但完整的基因组需要较低的Ct值.
- 仔细选择参考序列至关重要,以避免错误分类,并确保准确检测各种病毒菌株.
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