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单细胞谱分析鉴定出稳定的哺乳动物 tRNA-mRNA 界面,并提高神经元中的翻译效率。

Cell type-specific analysis by single-cell profiling identifies a stable mammalian tRNA-mRNA interface and increased translation efficiency in neurons.

机构信息

Department of Microbiology, Tumor, and Cell Biology, Karolinska Institute, Science for Life Laboratory, 171 77, Stockholm, Sweden.

出版信息

Genome Res. 2022 Jan;32(1):97-110. doi: 10.1101/gr.275944.121. Epub 2021 Dec 2.

DOI:10.1101/gr.275944.121
PMID:34857654
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8744671/
Abstract

The correlation between codon and anticodon pools influences the efficiency of translation, but whether differences exist in these pools across individual cells is unknown. We determined that codon usage and amino acid demand are highly stable across different cell types using available mouse and human single-cell RNA-sequencing atlases. After showing the robustness of ATAC-sequencing measurements for the analysis of tRNA gene usage, we quantified anticodon usage and amino acid supply in both mouse and human single-cell ATAC-seq atlases. We found that tRNA gene usage is overall coordinated across cell types, except in neurons, which clustered separately from other cell types. Integration of these data sets revealed a strong and statistically significant correlation between amino acid supply and demand across almost all cell types. Neurons have an enhanced translation efficiency over other cell types, driven by an increased supply of tRNA (AGC) anticodons. This results in faster decoding of the Ala-GCC codon, as determined by cell type-specific ribosome profiling, suggesting that the reduction of tRNA (AGC) anticodon pools may be implicated in neurological pathologies. This study, the first such examination of codon usage, anticodon usage, and translation efficiency resolved at the cell-type level with single-cell information, identifies a conserved landscape of translation elongation across mammalian cellular diversity and evolution.

摘要

密码子和反密码子库之间的相关性会影响翻译的效率,但个体细胞之间这些库是否存在差异尚不清楚。我们利用现有的小鼠和人类单细胞 RNA 测序图谱确定,密码子使用和氨基酸需求在不同细胞类型中高度稳定。在展示了 ATAC 测序测量用于分析 tRNA 基因使用的稳健性之后,我们在小鼠和人类单细胞 ATAC-seq 图谱中量化了反密码子使用和氨基酸供应。我们发现,除了神经元之外,tRNA 基因使用在整个细胞类型中总体上是协调的,神经元与其他细胞类型分开聚类。这些数据集的整合揭示了几乎所有细胞类型中氨基酸供应和需求之间的强烈且具有统计学意义的相关性。神经元比其他细胞类型具有更高的翻译效率,这是由 tRNA(AGC)反密码子供应增加驱动的。这导致 Ala-GCC 密码子的解码速度加快,这是通过细胞类型特异性核糖体分析确定的,这表明 tRNA(AGC)反密码子库的减少可能与神经病理学有关。这项研究首次在单细胞信息层面上,对密码子使用、反密码子使用和翻译效率进行了细胞类型水平的检查,确定了哺乳动物细胞多样性和进化过程中延伸翻译的保守景观。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc2b/8744671/4f4aef369210/97f02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc2b/8744671/1ff2793e9054/97f01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc2b/8744671/4f4aef369210/97f02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc2b/8744671/1ff2793e9054/97f01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc2b/8744671/4f4aef369210/97f02.jpg

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