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相关概念视频

RNA Editing02:23

RNA Editing

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RNA editing is a post-transcriptional modification where a precursor mRNA (pre-mRNA) nucleotide sequence is changed by base insertion, deletion, or modification. The extent of RNA editing varies from a few hundred bases, in mitochondrial DNA of trypanosomes, to a just single base, in nuclear genes of mammals. Even a single base change in the pre-mRNA can convert a codon for one amino acid into the codon for another amino acid or a stop codon. This type of re-coding can significantly affect the...
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Proofreading01:43

Proofreading

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Overview
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Improving Translational Accuracy02:07

Improving Translational Accuracy

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Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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相关实验视频

Updated: May 12, 2025

A Nonsequencing Approach for the Rapid Detection of RNA Editing
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A Nonsequencing Approach for the Rapid Detection of RNA Editing

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通过深度学习预测不同细胞环境中的腺基编辑效率.

Lucas Kissling1, Amina Mollaysa2, Sharan Janjuha1

  • 1Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.

Genome biology
|May 9, 2025
PubMed
概括

腺基编辑器 (ABEs) 可以纠正致病突变. 这项研究验证了ABE in vivo,并引入了BEDICT2.0,这是一个深度学习模型,预测编辑效率以改善治疗开发.

关键词:
通过CRISPR-Cas9进行基因组编辑.基因组学就是基因组学.在生物体内,在生物体内.机器学习是机器学习.鼠标 鼠标是一个鼠标.

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Efficient PAM-Less Base Editing for Zebrafish Modeling of Human Genetic Disease with zSpRY-ABE8e
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Functional Assessment of BRCA1 variants using CRISPR-Mediated Base Editors
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Functional Assessment of BRCA1 variants using CRISPR-Mediated Base Editors

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相关实验视频

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科学领域:

  • 基因编辑技术 基因编辑技术
  • 分子生物学分子生物学
  • 生物信息学是一种生物信息学.

背景情况:

  • 腺基编辑器 (ABEs) 促进了A•T到G•C的转换.
  • 基准编辑效率的预测模型受到体外数据的限制.
  • 原始细胞的体内预测能力仍然不确定.

研究的目的:

  • 在体外和体内评估腺基编辑效率.
  • 为基础编辑结果开发一个预测计算模型.
  • 评估ABE在纠正病原性突变方面的潜力.

主要方法:

  • 使用SpRY-ABEmax和SpRY-ABE8e进行基础编辑屏幕.
  • 针对细胞系和小鼠肝脏模型中的2,195种致病突变.
  • 开发了BEDICT2.0,这是一个用于预测编辑效率的深度学习模型.

主要成果:

  • 观察到体外和体内基调编辑数据集之间的强烈相关性 (斯皮尔曼R = 0.83-0.92).
  • BEDICT2.0准确预测了细胞系 (R = 0.60-0.94) 和肝脏 (R = 0.62-0.81) 中的腺基编辑效率.
  • 展示了高目标编辑与最小的旁观者效应.

结论:

  • 腺基编辑显示了纠正众多病原性突变的巨大潜力.
  • BEDICT2.0是一个强大的计算工具,用于优化sgRNA-ABE组合.
  • 这些发现支持使用ABE用于体外和体内治疗应用.