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基于序列的机器学习揭示了黑猩猩和黑猩猩之间的3D基因组差异
Colin M Brand1,2, Shuzhen Kuang3, Erin N Gilbertson1,4
1Bakar Computational Health Sciences Institute, University of California, San Francisco, CA.
bioRxiv : the preprint server for biology
|November 14, 2023
概括
黑猩猩和黑猩猩的基因组折叠差异导致了表型分歧. 机器学习揭示了人口层面的3D基因组变异,确定了影响基因调节和特征的关键区域和变异.
科学领域:
- 基因组学就是基因组学.
- 进化生物学 进化生物学
- 计算生物学 计算生物学
背景情况:
- 像黑猩猩和黑猩猩 (属*Pan*) 等密切相关物种之间的表型分歧受到基因调节变异的显著影响.
- 三维 (3D) 基因组结构在调解基因表达方面发挥着至关重要的作用,但Pan* 属内的折叠差异仍然不太了解.
研究的目的:
- 通过机器学习预测和分析来自红和黑猩猩的DNA序列的全基因组3D基因组接触图.
- 量化和表征3D基因组分歧在群体层面的 * Pan * 属内.
- 为了确定特定的基因组区域和变异,有助于3D基因组折叠差异和潜在的表型分歧.
主要方法:
- 应用机器学习从DNA序列预测56个个体的3D基因组接触地图,跨越所有五个现存的*Pan*血统.
- 采用双向方法,在4420个1Mb的基因组窗口中估计3D差异.
- 进行 *in silico* 突变发生,以识别不同基因组窗口中的 3D 修改变体,重点关注 CTCF 结合动机破坏.
主要成果:
- 在约17%的单个对对比中预测了相当大的3D基因组折叠差异.
- 确定了89个基因组窗口,其中存在大量的博黑猩猩接触地图分歧,包括与表型差异相关的基因区域.
- 在不同的窗口中发现了51个3D修改变异,其中66.67% (34个变异) 通过CTCF结合动机破坏影响基因组折叠.
结论:
- 揭示了 *Pan* 属内的 3D 基因组结构在人口水平上的显著变化.
- 确定了特定的基因组区域和变异,其中改变的3D折叠可能是黑猩猩和黑猩猩之间的表型差异的基础.
- 突出了CTCF结合动机破坏在驱动3D基因组折叠变化的作用,这有助于产生特定物种的特征.
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