在人类丸中,在细胞类型内和细胞类型之间推导转录后调节
Saad Khan1,2, Megan Elcheikhali1,2,3,4, Andrew Leduc1
1Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Proteomics Center, Northeastern University, Boston, MA 02115, USA.
bioRxiv : the preprint server for biology
|October 17, 2024
概括
单细胞地图集经常使用RNA来推断蛋白质水平. 这项研究开发了BayesPG,贝叶斯模型,通过分析人类丸细胞的RNA和蛋白质数据来量化转录后调节.
科学领域:
- 蛋白质基因组学是什么
- 单细胞生物学 单细胞生物学
- 生物统计学 生物统计学
背景情况:
- 单细胞地图集通常使用RNA丰度作为蛋白质丰度的代理.
- 蛋白质水平受到合成和降解速度的影响,这表明后转录调节.
- 在单细胞研究中,区分生物变异与技术噪音至关重要.
研究的目的:
- 估计转录后调节对蛋白质丰富性的贡献.
- 开发一个强大的计算模型,共同分析单细胞RNA和蛋白质数据.
- 研究人类丸中细胞类型特异性蛋白调节的研究.
主要方法:
- 使用SCoPE2,pSCoPE和plexDIA质谱学对5,883个单个人类丸细胞的量化蛋白质组.
- 开发了贝叶斯PG,贝叶斯模型,以整合转录组和蛋白组数据,同时考虑技术变化.
- 在多个数据集和方法中,从29,709个单细胞中联合建模的RNA和蛋白质数据.
主要成果:
- 贝叶斯PG估计了3,861个基因产品的共识mRNA和蛋白质水平,并量化了相对蛋白与mRNA比率 (rPTR).
- 大约28%的基因产品显示蛋白质和RNA水平之间存在显著差异,影响了约1500个基因本体学 (GO) 组.
- 与精子生成相关的功能和翻译后修饰的呈现出显著的细胞类型特异性调节.
结论:
- 转录后调节在特殊的细胞功能中起着重要作用,例如精子生成.
- 贝叶斯PG模型提供了一个可通用的框架,用于从单细胞蛋白质基因组数据推断蛋白质调节.
- 细胞类型对蛋白质丰度的特定调节,包括通过酸化,在人类丸中很明显.
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