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Related Concept Videos

Mismatch Repair01:20

Mismatch Repair

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Organisms are capable of detecting and fixing nucleotide mismatches that occur during DNA replication. This sophisticated process requires identifying the new strand and replacing the erroneous bases with correct nucleotides. Mismatch repair is coordinated by many proteins in both prokaryotes and eukaryotes.
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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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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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Related Experiment Video

Updated: Dec 25, 2025

Efficient Generation of hiPSC Neural Lineage Specific Knockin Reporters Using the CRISPR/Cas9 and Cas9 Double Nickase System
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sgRNA-PSM: Predict sgRNAs On-Target Activity Based on Position-Specific Mismatch.

Bin Liu1, Zhihua Luo2, Juan He3

  • 1School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China; Advanced Research Institute of Multidisciplinary Science, Beijing Institute of Technology, Beijing, China.

Molecular Therapy. Nucleic Acids
|March 22, 2020
PubMed
Summary

Predicting single-guide RNA (sgRNA) on-target activity is crucial for CRISPR-Cas9 applications. New methods, sgRNA-PSM and sgRNA-ExPSM, improve prediction accuracy by analyzing sequence and evolutionary data.

Keywords:
XGBoostposition-specific mismatchsgRNAs on-target activity

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Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Genomics

Background:

  • Single-guide RNA (sgRNA) on-target activity is essential for CRISPR-Cas9 technology.
  • Accurate prediction of sgRNA activity is vital for genome editing and synthetic biology.
  • Existing computational predictors have limitations in capturing comprehensive sequence and evolutionary information.

Purpose of the Study:

  • To develop novel computational methods for predicting sgRNA on-target activity.
  • To address limitations of current predictors by incorporating long-range sequence and evolutionary information.
  • To provide an accessible tool for researchers to predict sgRNA efficacy.

Main Methods:

  • Proposed two new prediction methods: sgRNA-PSM and sgRNA-ExPSM.
  • Utilized long-range sequence information and evolutionary data.
  • Employed a novel feature vector dimension reduction technique to prevent overfitting.
  • Conducted rigorous leave-one-gene-out cross-validation on benchmark and independent datasets.

Main Results:

  • sgRNA-PSM and sgRNA-ExPSM demonstrated superior performance compared to existing methods.
  • The new methods effectively captured crucial sequence and evolutionary features for activity prediction.
  • Validation on human and mouse gene datasets confirmed the enhanced predictive power.
  • A web server for sgRNA-PSM was developed for user accessibility.

Conclusions:

  • The proposed sgRNA-PSM and sgRNA-ExPSM methods represent a significant advancement in predicting sgRNA on-target activity.
  • These methods offer improved accuracy and robustness for CRISPR-Cas9 applications.
  • The user-friendly web server facilitates the practical application of these predictive tools in research and development.