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相关概念视频

Nonsense-mediated mRNA Decay02:27

Nonsense-mediated mRNA Decay

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The Upf proteins that carry out nonsense-mediated decay (NMD) are found in all eukaryotic organisms, including humans. Each protein has an individual role, but they need to work in collaboration. Upf1 is an ATP-dependent RNA helicase that unwinds the RNA helix. Because Upf1 can unwind any RNA, Upf2 and Upf3 are required to help Upf1 discriminate between nonsense and normal mRNAs.
Usually, Upf3 binds to an Exon Junction Complex (EJC) at mRNA splice sites. If a ribosome fully translates the mRNA,...
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Leaky Scanning02:28

Leaky Scanning

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During most eukaryotic translation processes, the small 40S ribosome subunit scans an mRNA from its 5' end until it encounters the first start AUG codon. The large 60S ribosomal subunit then joins the smaller one to initiate protein synthesis. The location of the translation initiation is largely determined by the nucleotides near the start codon as there may be multiple translation initiation sites present on the mRNA.  Marilyn Kozak discovered that the sequence RCCAUGG (where R...
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Improving Translational Accuracy02:07

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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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Nuclear Export of mRNA02:31

Nuclear Export of mRNA

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Before mRNAs are exported to the cytoplasm, it is crucial to check each mRNA for structural and functional integrity. Eukaryotic cells use several different mechanisms, collectively known as mRNA surveillance, to look for irregularities in mRNAs. Irregular or aberrant mRNA are rapidly degraded by various enzymes. If a defective mRNA escapes the surveillance, it would be translated into a protein which would either be non-functional or not function properly. One of the primary irregularities in...
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From DNA to Protein03:06

From DNA to Protein

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The flow of genetic information in cells from DNA to mRNA to protein is described by the central dogma, which states that genes specify the sequence of mRNAs, which in turn specify the sequence of amino acids making up all proteins. The decoding of one molecule to another is performed by specific proteins and RNAs. Because the information stored in DNA is so central to cellular function, it makes intuitive sense that the cell would make mRNA copies of this information for protein synthesis...
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Chromatin Structure Regulates pre-mRNA Processing02:41

Chromatin Structure Regulates pre-mRNA Processing

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In eukaryotic cells, nascent mRNA transcripts need to undergo many post-transcriptional modifications to reach the cell cytoplasm and translate into functional proteins. For a long time, transcription and pre-mRNA processing were considered two independent events that occur sequentially in the cell. However, it has now been well established that transcription and pre-mRNA processing are two simultaneous processes that are precisely regulated inside the cell.
The chromatin structure, especially...
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相关实验视频

Updated: Jun 30, 2025

De novo Identification of Actively Translated Open Reading Frames with Ribosome Profiling Data
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扩展的停止编码子上下文预测无意义的编码子读透效率在人类细胞.

Kotchaphorn Mangkalaphiban1,2, Lianwu Fu3, Ming Du3

  • 1Department of Microbiology and Physiological Systems, UMass Chan Medical School, 368 Plantation Street, Worcester, MA, 01655, USA.

Nature communications
|March 21, 2024
PubMed
概括
此摘要是机器生成的。

通过机器学习可以预测蛋白质合成期间的停止密码子读取. 这一发现有助于通过评估患者对药物的反应来开发治疗诸如囊性纤维化等遗传疾病的疗法.

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Measurement of Specific Mycobacterial Mistranslation Rates with Gain-of-function Reporter Systems
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De novo Identification of Actively Translated Open Reading Frames with Ribosome Profiling Data

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科学领域:

  • 分子生物学分子生物学
  • 遗传学 是一个遗传学.
  • 计算生物学 计算生物学

背景情况:

  • 蛋白质合成终结依赖于停止编码子,但近同类的tRNA可以导致读透.
  • 了解停止编码子的读透对于开发针对遗传疾病的疗法至关重要.

研究的目的:

  • 通过使用机器学习来研究停止密码子阅读的调控机制.
  • 评估跨物种的读透因子的保存情况,并预测治疗反应.

主要方法:

  • 机器学习分析人类 (HEK293T) 和酵母实验中的核糖体分析数据.
  • 基于序列背景和遗传因素的阅读效率的比较分析.
  • 模型验证使用药物治疗细胞和囊性纤维化无意义突变的数据.

主要成果:

  • 在读透调节中确定了保存因素,包括停止编码子的身份,上下文和3'-UTR长度.
  • 发现了证据表明P位点tRNA在读透调节中的作用,这种调节并未保存.
  • 开发了预测模型,准确地预测囊性纤维化中过早终止密码子的读透率.

结论:

  • 机器学习模型可以根据序列上下文预测停止编码子的阅读效率.
  • 预测模型显示了指导个性化无稽之谈抑制疗法的发展的潜力.
  • 这种方法可能有助于预测患者对基因疾病的阅读促进药物的反应.