文献类型： 外文期刊

作者： Yuan, Tanglong ¹ ; Wu, Leilei ² ; Li, Shiyan ³ ; Zheng, Jitan ¹ ; Li, Nana ¹ ; Xiao, Xiao ¹ ; Zhang, Haihang ¹ ; Fei, Tianyi ² ; Xie, Long ¹ ; Zuo, Zhenrui ¹ ; Li, Di ¹ ; Huang, Pinzheng ⁷ ; Feng, Hu ¹ ; Cao, Yaqi ¹ ; Yan, Nana ¹ ; Wei, Xinming ⁷ ; Shi, Lei ¹ ; Sun, Yongsen ¹ ; Wei, Wu ³ ; Sun, Yidi ² ; Zuo, Erwei ¹ ;

作者机构： 1.Chinese Acad Agr Sci, Agr Genom Inst Shenzhen, Shenzhen Branch,Minist Agr & Rural Affairs, Guangdong Lab Lingnan Modern Agr,Key Lab Synthet B, Shenzhen, Guangdong, Peoples R China

2.Chinese Acad Sci, Inst Neurosci, CAS Ctr Excellence Brain Sci & Intelligence Techno, Shanghai, Peoples R China

3.Univ Chinese Acad Sci, Chinese Acad Sci, Shanghai Inst Nutr & Hlth, Biomed Big Data Ctr,Key Lab Computat Biol, Shanghai, Peoples R China

4.Guangxi Univ, State Key Lab Conservat & Utilizat Subtrop Agrobio, Nanning, Guangxi, Peoples R China

5.Huazhong Agr Univ, Key Lab Agr Anim Genet Breeding & Reprod Minist Ed, Wuhan, Hubei, Peoples R China

6.Huazhong Agr Univ, Key Lab Swine Genet Breeding Minist Agr & Rural Af, Wuhan, Hubei, Peoples R China

7.Epigen Therapeut Inc, Shanghai 201315, Peoples R China

8.Lingang Lab, Shanghai, Peoples R China

期刊名称：CELL DISCOVERY （ 影响因子：33.5； 五年影响因子：21.9 ）

ISSN：

年卷期： 2024 年 10 卷 1 期

页码：

收录情况： SCI

摘要： Adenine base editors (ABEs) and cytosine base editors (CBEs) enable the single nucleotide editing of targeted DNA sites avoiding generation of double strand breaks, however, the genomic features that influence the outcomes of base editing in vivo still remain to be characterized. High-throughput datasets from lentiviral integrated libraries were used to investigate the sequence features affecting base editing outcomes, but the effects of endogenous factors beyond the DNA sequences are still largely unknown. Here the base editing outcomes of ABE and CBE were evaluated in mammalian cells for 5012 endogenous genomic sites and 11,868 genome-integrated target sequences, with 4654 genomic sites sharing the same target sequences. The comparative analyses revealed that the editing outcomes of ABE and CBE at endogenous sites were substantially different from those obtained using genome-integrated sequences. We found that the base editing efficiency at endogenous target sites of both ABE and CBE was influenced by endogenous factors, including epigenetic modifications and transcriptional activity. A deep-learning algorithm referred as BE_Endo, was developed based on the endogenous factors and sequence information from our genomic datasets, and it yielded unprecedented accuracy in predicting the base editing outcomes. These findings along with the developed computational algorithms may facilitate future application of BEs for scientific research and clinical gene therapy.