Evidence map›Paper›PMID 35952936›Full record

ArticleGenomics, proteomics & bioinformatics2023

Dynamic Landscapes of tRNA Transcriptomes and Translatomes in Diverse Mouse Tissues.

Peng Yu, Siting Zhou, Yan Gao, Yu Liang, Wenbing Guo, Dan Ohtan Wang, Shuaiwen Ding, Shuibin Lin, Jinkai Wang, Yixian Cun

Open access · goldAbstract read
In one paragraph

Article in Genomics, proteomics & bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.3field-weighted citation impact, top 20% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
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  3. The regulation, function and disease relevance of cytoplasmic tRNAs.Nature reviews. Molecular cell biology · 2026
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 2 countries.

Peng YuCenter for Translational Medicine, Precision Medicine Institute, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, China; Department of Radiation Oncology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou 510080, China.
Siting ZhouDepartment of Medical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Center for Stem Cell Biology and Tissue Engineering, MOE Key Laboratory for Stem Cells and Tissue Engineering, Sun Yat-sen University, Guangzhou 510080, China.
Yan GaoDepartment of Medical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Center for Stem Cell Biology and Tissue Engineering, MOE Key Laboratory for Stem Cells and Tissue Engineering, Sun Yat-sen University, Guangzhou 510080, China.
Yu LiangCenter for Translational Medicine, Precision Medicine Institute, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, China.
Wenbing GuoDepartment of Medical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Center for Stem Cell Biology and Tissue Engineering, MOE Key Laboratory for Stem Cells and Tissue Engineering, Sun Yat-sen University, Guangzhou 510080, China.
Dan Ohtan WangRIKEN Center for Biosystems Dynamics Research, Kobe 650-0047, Japan; Graduate School of Biostudies, Kyoto University, Kyoto 606-8501, Japan; Wuya College of Innovation, Shenyang Pharmaceutical University, Shenyang 110016, China.
Shuaiwen DingDepartment of Medical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China.
Shuibin LinCenter for Translational Medicine, Precision Medicine Institute, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, China. Electronic address: linshb6@mail.sysu.edu.cn.
Jinkai WangDepartment of Medical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Center for Stem Cell Biology and Tissue Engineering, MOE Key Laboratory for Stem Cells and Tissue Engineering, Sun Yat-sen University, Guangzhou 510080, China; RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510080, China. Electronic address: wangjk@mail.sysu.edu.cn.
Yixian CunDepartment of Medical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Center for Stem Cell Biology and Tissue Engineering, MOE Key Laboratory for Stem Cells and Tissue Engineering, Sun Yat-sen University, Guangzhou 510080, China. Electronic address: cunyx3@mail.sysu.edu.cn.
Sun Yat-sen University · CNShenyang Pharmaceutical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although the function of tRNAs in the translational process is well established, it remains controversial whether tRNA abundance is tightly associated with translational efficiency (TE) in mammals. Moreover, how critically the expression of tRNAs contributes to the establishment of tissue-specific proteomes in mammals has not been well addressed. Here, we measured both tRNA expression using demethylase-tRNA sequencing (DM-tRNA-seq) and TE of mRNAs using ribosome-tagging sequencing (RiboTag-seq) in the brain, heart, and testis of mice. Remarkable variation in the expression of tRNA isodecoders was observed among different tissues. When the statistical effect of isodecoder-grouping on reducing variations is considered through permutating the anticodons, we observed an expected reduction in the variation of anticodon expression across all samples, an unexpected smaller variation of anticodon usage bias, and an unexpected larger variation of tRNA isotype expression at amino acid level. Regardless of whether or not they share the same anticodons, the isodecoders encoding the same amino acids are co-expressed across different tissues. Based on the expression of tRNAs and the TE of mRNAs, we find that the tRNA adaptation index (tAI) and TE are significantly correlated in the same tissues but not between tissues; and tRNA expression and the amino acid composition of translating peptides are positively correlated in the same tissues but not between tissues. We therefore hypothesize that the tissue-specific expression of tRNAs might be due to post-transcriptional mechanisms. This study provides a resource for tRNA and translation studies, as well as novel insights into the dynamics of tRNAs and their roles in translational regulation.

Indexed as

AnticodonTranscriptomeAmino AcidsAnimalsMammalsMiceProtein BiosynthesisRNA, TransferAmino AcidsAnticodonRNA, TransferAmino acid compositionCodon usage biasTissue-specificTranslational efficiencytRNA expression

Identifiers

PMID35952936
PMCPMC10787195
OpenAlexW4300582127

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.