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深度学习可以预测古代亚基因组的主导地位,但不能预测新/合成多倍体基因组的亚基因组主导地位
Zhongwei Guo1, Kang Zhang1, Chengcheng Cai1
1State Key Laboratory of Vegetable Biobreeding, Key Laboratory of Biology and Genetic Improvement of Horticultural Crops of the Ministry of Agriculture and Rural Affairs, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China.
The Plant journal : for cell and molecular biology
|August 12, 2024
概括
深度学习模型显示,促进子区域的DNA序列差异推动了植物亚基因组的主导地位. 这种表达式的主导性在多倍体化后的序列分歧之前并形成序列分歧.
科学领域:
- 基因组学就是基因组学.
- 进化生物学 进化生物学
- 生物信息学是一种生物信息学.
背景情况:
- 亚基因组主导性,即在全聚类的一个亚基因组中的基因的偏向表达或分化,是植物的一个关键的进化过程.
- 驱动子基因组优势的精确机制在很大程度上是未知的.
- 通过不同物种的杂交形成的全聚类,占植物多样性的很大一部分.
研究的目的:
- 通过深度学习来研究亚基因组优势的潜在机制.
- 确定DNA序列和甲基化在预测基因表达和亚基因组优势中的作用.
- 分析深度学习模型在各种植物多化系统中的适用性.
主要方法:
- 开发了两个卷积神经网络 (CNN) 模型:二进制表达模型 (BEM) 和同类学对比模型 (HCM).
- 利用发起体区域的DNA序列和甲基化数据.
- 应用CNN模型来分析Brassica,Gossypium和Cucurbitaceae中的古老和新/合成多倍体基因组.
主要成果:
- 在BEM准确地预测基因表达基于促进者DNA序列.
- HCM成功地预测了古老的同源基因对的亚基因组主导地位,但不是新的.
- 使用甲基化位点的模型产生了与基于DNA序列的模型相似的预测能力.
- 结果在三个研究的植物系统中一致,证明了模型的广泛适用性.
结论:
- 亚基因组主导性与同源促进体的长期序列分歧有关.
- 表达主导性似乎在多聚化后的亚基因组之间的序列分歧之前和驱动序列分歧.
- 深度学习为解剖复杂的进化机制提供了强大的工具,例如亚基因组优势.
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