评估广泛使用的基因表达进化基因表达遗传学模型的性能
Jose Rafael Dimayacyac1,2, Shanyun Wu1,3, Daohan Jiang4
1Department of Zoology, University of British Columbia, Vancouver, BC, Canada.
Genome biology and evolution
|November 24, 2023
概括
遗传学对基因表达的比较方法通常是不可靠的. 大多数模型不适合,经常是由于未解决的进化速率变化,突出了进化研究中常规模型评估的需要.
科学领域:
- 进化生物学是进化的生物学.
- 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:
- 遗传学比较方法 (PCM) 对于研究基因表达进化的研究至关重要.
- 开发用于定量特征的PCM对基因表达数据的适用性仍然不清楚.
- 模型匹配对于基因表达的基因基因比较研究中可靠的结论至关重要.
研究的目的:
- 通过基因表达数据,评估植物遗传模型分布假设的现实性.
- 评估各种遗传学模型在描述基因表达数据集中的表现.
- 为了确定影响模型性能的因素,在家族遗传学比较表达研究.
主要方法:
- 将特征演变的多个家族遗传模型配合到8个已发表的基因表达数据集中 (54,774个基因,145,927个基因-组织组合).
- 采用了经过验证的方法来评估最佳表现模型的绝对适用性.
- 分析模型性能,使用统计测试来识别与假设的偏差.
主要成果:
- 反映稳定选择的奥恩斯坦-乌伦贝克模型在66%的基因-组织组合中是首选的.
- 最适合的模型在61%的基因-组织组合中表现良好.
- 模型性能差通常与进化速率中未捕获的异质性有关.
结论:
- 遗传学模型,特别是奥恩斯坦-乌伦贝克,经常适合基因表达数据.
- 很大一部分基因表达数据集没有被当前最适合的模型充分描述.
- 评估模型性能对于强大的基因表达的基因基因比较分析和推动新模型开发至关重要.
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