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mRNA 测序预测蛋白质丰度的可行性。

Workability of mRNA Sequencing for Predicting Protein Abundance.

机构信息

Institute of Biomedical Chemistry, Moscow 119121, Russia.

Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia.

出版信息

Genes (Basel). 2023 Nov 11;14(11):2065. doi: 10.3390/genes14112065.

Abstract

Transcriptomics methods (RNA-Seq, PCR) today are more routine and reproducible than proteomics methods, i.e., both mass spectrometry and immunochemical analysis. For this reason, most scientific studies are limited to assessing the level of mRNA content. At the same time, protein content (and its post-translational status) largely determines the cell's state and behavior. Such a forced extrapolation of conclusions from the transcriptome to the proteome often seems unjustified. The ratios of "transcript-protein" pairs can vary by several orders of magnitude for different genes. As a rule, the correlation coefficient between transcriptome-proteome levels for different tissues does not exceed 0.3-0.5. Several characteristics determine the ratio between the content of mRNA and protein: among them, the rate of movement of the ribosome along the mRNA and the number of free ribosomes in the cell, the availability of tRNA, the secondary structure, and the localization of the transcript. The technical features of the experimental methods also significantly influence the levels of the transcript and protein of the corresponding gene on the outcome of the comparison. Given the above biological features and the performance of experimental and bioinformatic approaches, one may develop various models to predict proteomic profiles based on transcriptomic data. This review is devoted to the ability of RNA sequencing methods for protein abundance prediction.

摘要

转录组学方法(RNA-Seq、PCR)比蛋白质组学方法(即质谱和免疫化学分析)更常规、更具可重复性。出于这个原因,大多数科学研究都仅限于评估 mRNA 含量水平。与此同时,蛋白质含量(及其翻译后状态)在很大程度上决定了细胞的状态和行为。因此,从转录组学推断到蛋白质组学的结论往往是不合理的。不同基因的“转录-蛋白”对的比例可能相差几个数量级。通常情况下,不同组织之间转录组-蛋白质组水平的相关系数不超过 0.3-0.5。有几个特性决定了 mRNA 和蛋白质含量之间的比例:核糖体在 mRNA 上的移动速度、细胞中游离核糖体的数量、tRNA 的可用性、二级结构和转录本的定位。实验方法的技术特点也会显著影响相应基因的转录本和蛋白质的水平,从而影响比较结果。鉴于上述生物学特征以及实验和生物信息学方法的性能,人们可以开发各种模型,基于转录组数据预测蛋白质组图谱。这篇综述主要介绍了 RNA 测序方法在蛋白质丰度预测方面的能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bb7/10671741/308282e3bc26/genes-14-02065-g001.jpg

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