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Related Concept Videos

Nonsense-mediated mRNA Decay02:27

Nonsense-mediated mRNA Decay

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.
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Point mutations are genetic alterations involving the change of a single nucleotide base pair in DNA. Depending on how the alteration affects protein synthesis, they can lead to various consequences.Point mutations fall into the following types:Silent mutations occur when a nucleotide change does not alter the amino acid sequence due to the redundancy of the genetic code. For instance, changing ACC to ACA still encodes threonine, leaving the protein function unaffected. This occurs because...
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Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells
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corRna: a web server for predicting multiple-point deleterious mutations in structural RNAs.

Edmund Lam1, Alfred Kam, Jérôme Waldispühl

  • 1McGill Centre for Bioinformatics, McGill University, Montreal, QC, Canada.

Nucleic Acids Research
|May 21, 2011
PubMed
Summary
This summary is machine-generated.

Predicting multiple mutations in RNA structures is crucial for research. The corRna web server efficiently identifies multiple deleterious mutations in structural RNAs, aiding mutagenesis experiments and synthetic biology.

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Area of Science:

  • Molecular Biology
  • Bioinformatics

Background:

  • RNA molecules perform regulatory functions via sequence-determined structures.
  • Predicting mutations that alter RNA structure (deleterious mutations) is vital for experimental design and synthetic biology.
  • Current methods struggle with analyzing multiple mutations efficiently.

Purpose of the Study:

  • Introduce corRna, a web server for predicting multiple-point deleterious mutations in structural RNAs.
  • Provide a tool to efficiently explore the RNA mutational landscape.
  • Enable users to improve prediction quality using search heuristics.

Main Methods:

  • Utilize the RNAmutants framework for efficient exploration of RNA sequence space.
  • Implement search heuristics to refine predictions of deleterious mutations.
  • Validate predictions against experimental mutagenesis data and compare with existing methods.

Main Results:

  • corRna predictions show strong correlation with experimental mutagenesis data for the hepatitis C virus cis-acting replication element.
  • Achieve accuracy comparable to previous methods on a large test set but with significantly reduced execution time.
  • Successfully predict five-point deleterious mutations, a feat not possible with prior approaches.

Conclusions:

  • corRna offers an efficient and accurate solution for predicting multiple deleterious mutations in structural RNAs.
  • The tool facilitates advanced mutagenesis studies and synthetic biology applications by enabling the analysis of complex mutation combinations.
  • corRna expands the possibilities for investigating RNA structural dynamics and functional implications.