Evidence map›Paper›PMID 37794072›Full record

ReviewNature protocols2023

Design and application of the transformer base editor in mammalian cells and mice.

Wenyan Han, Bao-Qing Gao, Junjie Zhu, Zongxing He, Jianfeng Li, Li Yang, Jia Chen

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature protocols, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.9field-weighted citation impact, top 24% 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

10 citing papers in PubMed, 6 citations in OpenAlex.

  1. Engineered Transformer Base Editor with Enhanced Editing Efficiency.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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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

7 authors at 3 institutions in 2 countries.

Wenyan Han *Gene Editing Center, School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
Bao-Qing Gao *Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
Junjie Zhu *Gene Editing Center, School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
Zongxing He *Gene Editing Center, School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
Jianfeng LiGene Editing Center, School of Life Science and Technology, ShanghaiTech University, Shanghai, China. lijf1@shanghaitech.edu.cn.
Li YangCenter for Molecular Medicine, Children's Hospital, Fudan University and Shanghai Key Laboratory of Medical Epigenetics, International Laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Fudan University, Shanghai, China. liyang_fudan@fudan.edu.cn.ORCID 0000-0001-8833-7473
Jia ChenGene Editing Center, School of Life Science and Technology, ShanghaiTech University, Shanghai, China. chenjia@shanghaitech.edu.cn.ORCID 0000-0002-4242-2899
ShanghaiTech University · CNFudan University · CNChinese Academy of Sciences · CN

Funding

Ministry of Agriculture and Rural Affairs of the People's Republic of China (MOA) NK2022010207Ministry of Science and Technology of the People's Republic of China (Chinese Ministry of Science and Technology) 2018YFA0801401Ministry of Science and Technology of the People's Republic of China (Chinese Ministry of Science and Technology) 2019YFA0802804Ministry of Science and Technology of the People's Republic of China (Chinese Ministry of Science and Technology) 20PJ1410200Ministry of Science and Technology of the People's Republic of China (Chinese Ministry of Science and Technology) 21JC1404600National Natural Science Foundation of China (National Science Foundation of China) 31925011National Natural Science Foundation of China (National Science Foundation of China) 81872305Science and Technology Commission of Shanghai Municipality (Shanghai Municipal Science and Technology Commission) 20PJ1410200Science and Technology Commission of Shanghai Municipality (Shanghai Municipal Science and Technology Commission) 21JC1404600
6 · The paper itself

Abstract

Fusing apolipoprotein B mRNA-editing enzyme, catalytic polypeptide-like cytidine deaminase with catalytically impaired Cas proteins (e.g., nCas9 or dCas9) provides a novel gene-editing technology, base editing, that grants targeted base substitutions with high efficiency. However, genome-wide and transcriptome-wide off-target mutations are observed in base editing, which raises safety concerns regarding therapeutic applications. Previously, we developed a new base editing system, the transformer base editor (tBE), to induce efficient editing with no observable genome-wide or transcriptome-wide off-target mutations both in mammalian cells and in mice. Here we describe a detailed protocol for the design and application of the tBE. Steps for designing single-guide RNA (sgRNA) and helper sgRNA pairs, making constructs, determining the genome-wide and transcriptome-wide off-target mutations, producing the tBE-containing adeno-associated viruses, delivering adeno-associated viruses into mice and examining the in vivo editing effects are included in this protocol. High-precision base editing by the tBE can be completed within 2-3 weeks (in mammalian cells) or within 6-8 weeks (in mice), with sgRNA-helper sgRNA pairs. The whole process can be collaboratively accomplished by researchers using standard techniques from molecular biology, bioinformatics and mouse husbandry.

Indexed as

CRISPR-Cas SystemsRNA, Guide, CRISPR-Cas SystemsAnimalsCRISPR-Associated Protein 9Gene EditingMammalsMiceMutationCRISPR-Associated Protein 9RNA, Guide, CRISPR-Cas Systems

Identifiers

PMID37794072
OpenAlexW4387332453

What OpenQuestion holds

Textmetadata
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.