叶绿体结构,编码子使用偏差和基于机器学习的分子识别,使用Sophorae Tonkinensis Radix et Rhizoma (Shan Dou Gen) 和其类似物的DNA条形码
Mengdi Zheng1, Yang Zhao1, Mingchen Gao1
1Xi'an Medical University, Xi'an, Shaanxi 710021, China.
Fitoterapia
|November 26, 2025
概括
这项研究对山道基因和相关物种的叶绿体基因组进行了测序,揭示了它们的进化和编码体使用的洞察力. 结合DNA条形码和机器学习,有效地识别了物种,确保了药物安全.
科学领域:
- 植物基因组学和分子进化
- 生物信息学和计算生物学
- 药物鉴定和传统医学
背景情况:
- 香杜健 (Sophorae Tonkinensis Radix et Rhizoma) 是一种有价值的药用草本.
- 由于物种很容易混,准确的识别至关重要.
- 了解遗传多样性有助于保护和质量控制.
研究的目的:
- 测序和分析山道基因和六种相关物种的叶绿体基因组.
- 为了研究子使用偏差和进化模式.
- 评估用于物种识别的DNA条形码和机器学习.
主要方法:
- 整个叶绿体基因组测序和比较分析.
- 使用CodonW和CUSP进行Codon使用偏差分析.
- 用于物种识别的DNA条形码 (ITS2,matK,psbA-trnH,rbcL) 和机器学习 (BLOG,WEKA).
主要成果:
- 叶绿体基因组表现出A/T丰富的单核酸SSRs.
- 自然选择是编码子使用偏差的主要驱动因素.
- 所有四个DNA条形码都有效地区分了七种物种.
- 博客算法实现了>85%的识别准确度.
结论:
- 叶绿体DNA分析提供了一种强大的物种识别方法.
- 机器学习,特别是BLOG,提高了识别的准确性.
- 这项研究支持安全使用,保护和利用Shan Dou Gen.
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