富含A/ t末端密码子的基因在哺乳动物中是共同调控和保守的。

IF 9 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Cell Systems Pub Date : 2023-04-19 DOI:10.1016/j.cels.2023.02.002
Hannah Benisty, Xavier Hernandez-Alias, Marc Weber, Miquel Anglada-Girotto, Federica Mantica, Leandro Radusky, Gökçe Senger, Ferriol Calvet, Donate Weghorn, Manuel Irimia, Martin H Schaefer, Luis Serrano
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引用次数: 3

摘要

密码子的使用对基因表达的影响取决于细胞环境。然而,密码子偏置在蛋白质编码基因的特定组同时更新中的重要性仍有待研究。本研究发现,与G/ c末端密码子富集的基因相比,A/ t末端密码子富集的基因在整个组织和发育过程中的表达更加协调。tRNA丰度测量表明,这种协调与读取A/ t端密码子的tRNA同工受体的表达变化有关。具有相似密码子组成的基因更有可能是相同蛋白质复合体的一部分,特别是对于具有A/ t结尾密码子的基因。A/ t端密码子基因的密码子偏好在哺乳动物和其他脊椎动物中是保守的。我们认为这种协调有助于组织特异性和个体特异性表达,例如,它可以促进及时的蛋白质复合物形成。
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Genes enriched in A/T-ending codons are co-regulated and conserved across mammals.

Codon usage influences gene expression distinctly depending on the cell context. Yet, the importance of codon bias in the simultaneous turnover of specific groups of protein-coding genes remains to be investigated. Here, we find that genes enriched in A/T-ending codons are expressed more coordinately in general and across tissues and development than those enriched in G/C-ending codons. tRNA abundance measurements indicate that this coordination is linked to the expression changes of tRNA isoacceptors reading A/T-ending codons. Genes with similar codon composition are more likely to be part of the same protein complex, especially for genes with A/T-ending codons. The codon preferences of genes with A/T-ending codons are conserved among mammals and other vertebrates. We suggest that this orchestration contributes to tissue-specific and ontogenetic-specific expression, which can facilitate, for instance, timely protein complex formation.

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来源期刊
Cell Systems
Cell Systems Medicine-Pathology and Forensic Medicine
CiteScore
16.50
自引率
1.10%
发文量
84
审稿时长
42 days
期刊介绍: In 2015, Cell Systems was founded as a platform within Cell Press to showcase innovative research in systems biology. Our primary goal is to investigate complex biological phenomena that cannot be simply explained by basic mathematical principles. While the physical sciences have long successfully tackled such challenges, we have discovered that our most impactful publications often employ quantitative, inference-based methodologies borrowed from the fields of physics, engineering, mathematics, and computer science. We are committed to providing a home for elegant research that addresses fundamental questions in systems biology.
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