Evidence map›Paper›PMID 41093849›Full record

ArticleNature communications2025

A motif preferred adenine base editor with minimal bystander and off-targets editing.

Mengyu Shang, Yinuo Li, Qiuyu Cao, Jingxuan Ren, Yuqiang Zeng, Jinxin Wang, Rachel V L Gonzalez, Xiaohui Zhang

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
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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

8 authors.

Mengyu Shang *State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou, China.
Yinuo Li *State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou, China.ORCID http://orcid.org/0009-0004-5718-1604
Qiuyu Cao *State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou, China.
Jingxuan Ren *State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou, China.
Yuqiang ZengState Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou, China.
Jinxin WangState Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou, China.
Rachel V L GonzalezDepartment of Physiology and Cellular Biophysics, Columbia University, Manhattan, NY, USA.
Xiaohui ZhangState Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou, China. zhangxiaohui3040@126.com.ORCID http://orcid.org/0000-0002-4095-5771

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

47% of hereditable diseases are caused by single C•G-to-T•A base conversions, which means efficient A-to-G base editing tools (ABEs) have great potential for the treatment of these diseases. However, the existing efficient ABEs, while catalyzing targeted A-to-G conversion, cause high A or C bystander editing and off-target events, which poses safety concerns for their clinical applications. To overcome this shortcoming, we have developed ABE8e-YA (ABE8e with TadA-8e A48E) for efficient and accurate editing of As in YA motifs with YAY > YAR (Y = T or C, R = A or G) hierarchy through structure-oriented rational design. Compared with ABE3.1, which is currently the only ABE version with a YAC motif preference, ABE8e-YA exhibits an average A-to-G editing efficiency improvement of an up to 3.1-fold increase in the indicated YA motif while maintaining reduced bystander C editing and minimized DNA or RNA off-targets. Additionally, we demonstrate that ABE8e-YA efficiently and precisely corrects pathogenic mutations in human cells, suggesting its high suitability for addressing 9.3% of pathogenic point mutations, higher than that of ABE8e and ABE9. Moreover, by using ABE8e-YA, we efficiently and precisely generate hypocholesterolemia and tail-loss mouse models mimicking human-associated disease, as well as performed in vivo mouse proprotein convertase subtilisin/kexin type 9 (Pcsk9) base editing for hypercholesterolemia gene therapy. Together these data indicate its great potential in broad applications for disease modeling and gene therapy.

Indexed as

AdenineGene EditingNucleotide MotifsAnimalsCRISPR-Cas SystemsHEK293 CellsHumansMiceAdenine

Identifiers

PMID41093849
PMCPMC12528748

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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.