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Volume 50 Issue 8
Aug.  2023
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Article Contents

High-throughput base editing KO screening of cellular factors for enhanced GBE

doi: 10.1016/j.jgg.2023.05.007
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This work was financially supported by the National Key Research and Development Program of China (2018YFA0901300), the National Natural Science Foundation of China (32171449, 81903776), a Tianjin Synthetic Biotechnology Innovation Capacity Improvement Project (TSBICIP-KJGG-001), Tianjin Natural Science Foundation (20JCYBJC00310), and Youth Innovation Promotion Association CAS (2022177).

  • Received Date: 2023-01-26
  • Publish Date: 2023-05-25
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  • Arbab, M., Shen, M.W., Mok, B., Wilson, C., Matuszek, Z., Cassa, C.A., Liu, D.R., 2020. Determinants of base editing outcomes from target library analysis and machine learning. Cell 182, 463-480.
    Gaudelli, N.M., Komor, A.C., Rees, H.A., Packer, M.S., Badran, A.H., Bryson, D.I., Liu, D.R., 2017. Programmable base editing of A T to G C in genomic DNA without DNA cleavage. Nature 551, 464-471.
    Jiang, G., Wang, J., Zhao, D., Chen, X., Pu, S., Zhang, C., Li, J., Li, Y., Yang, J., Li, S., et al., 2021. Molecular mechanism of the cytosine CRISPR base editing process and the roles of translesion DNA polymerases. ACS Synth. Biol. 10, 3353-3358.
    Kim, H.K., Min, S., Song, M., Jung, S., Choi, J.W., Kim, Y., Lee, S., Yoon, S., Kim, H.H., 2018. Deep learning improves prediction of CRISPR-Cpf1 guide RNA activity. Nat. Biotechnol. 36, 239-241.
    Koblan, L.W., Doman, J.L., Wilson, C., Levy, J.M., Tay, T., Newby, G.A., Maianti, J.P., Raguram, A., Liu, D.R., 2018. Improving cytidine and adenine base editors by expression optimization and ancestral reconstruction. Nat. Biotechnol. 36, 843-846.
    Komor, A.C., Kim, Y.B., Packer, M.S., Zuris, J.A., Liu, D.R., 2016. Programmable editing of a target base in genomic DNA without double-stranded DNA cleavage. Nature 533, 420-424.
    Li, B., Li, Y.Q., Zhao, D., Yang, J., Ma, Y.H., Bi, C.H., Zhang, X.L., 2022a. Sequence motifs and prediction model of GBE editing outcomes based on target library analysis and machine learning. J. Genet. Genomics 49, 254-257.
    Li, G., Li, X., Zhuang, S., Wang, L., Zhu, Y., Chen, Y., Sun, W., Wu, Z., Zhou, Z., Chen, J., et al., 2022b. Gene editing and its applications in biomedicine. Sci. China Life Sci. 65, 660-700.
    Maalouf, M., 2011. Logistic regression in data analysis:an overview. Int. J. Data Anal. Tech. Strat. 3, 281-299.
    Nishida, K., Arazoe, T., Yachie, N., Banno, S., Kakimoto, M., Tabata, M., Mochizuki, M., Miyabe, A., Araki, M., Hara, K.Y., et al., 2016. Targeted nucleotide editing using hybrid prokaryotic and vertebrate adaptive immune systems. Science 353, aaf8729.
    Sakamoto, A.N., Kaya, H., Endo, M., 2018. Deletion of TLS polymerases promotes homologous recombination in Arabidopsis. Plant Signal. Behav. 13, e1483673.
    Song, M., Kim, H.K., Lee, S., Kim, Y., Seo, S.Y., Park, J., Choi, J.W., Jang, H., Shin, J.H., Min, S., et al., 2020. Sequence-specific prediction of the efficiencies of adenine and cytosine base. Nat. Biotechnol. 38, 1037-1043.
    Uriarte-Arcia, A.V., Lopez-Yanez, I., Yanez-Marquez, C., 2014. One-hot vector hybrid associative classifier for medical data classification. PLoS ONE 9, e95715.
    Xu, P., Liu, Z., Liu, Y., Ma, H., Xu, Y., Bao, Y., Zhu, S., Cao, Z., Wu, Z., Zhou, Z., et al., 2021. Genome-wide interrogation of gene functions through base editor screens empowered by barcoded sgRNAs. Nat. Biotechnol. 39, 1403-1413.
    Zhao, D., Li, J., Li, S., Xin, X., Hu, M., Price, M.A., Rosser, S.J., Bi, C.H., Zhang, X., 2021. Glycosylase base editors enable C-to-A and C-to-G base changes. Nat. Biotechnol. 39, 35-40.
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