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Point and Frameshift Mutations01:30

Point and Frameshift Mutations

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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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Principles of Pharmacogenetics: Types of Genetic Variants01:27

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The human genome is over 99.9% identical between individuals, yet genetic differences exist at millions of bases. The human genome contains approximately 3 million variant positions per individual, many of which are heterozygous, contributing to genetic diversity and individual traits. Genetic variations include single-nucleotide polymorphisms (SNPs), insertions, deletions, and copy number variations (CNVs).SNPs, the most common variation, involve single-base changes in DNA. These can be...
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Comparing Copy Number Variations and SNPs02:26

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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
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Single Nucleotide Polymorphisms-SNPs01:05

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A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
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Mutations01:35

Mutations

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Mutations are changes in the sequence of DNA. These changes can occur spontaneously or they can be induced by exposure to environmental factors. Mutations can be characterized in a number of different ways: whether and how they alter the amino acid sequence of the protein, whether they occur over a small or large area of DNA, and whether they occur in somatic cells or germline cells.
Chromosomal Alterations Are Large-Scale Mutations
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Mutations01:39

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A framework for exhaustively mapping functional missense variants.

Jochen Weile1,2,3,4, Song Sun1,2,3,4,5, Atina G Cote1,2,3

  • 1Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada.

Molecular Systems Biology
|December 23, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces a deep mutational scanning (DMS) framework to map functional impacts of human missense variants. This approach identifies disease-causing mutations and could be applied to most human disease genes.

Keywords:
complementationdeep mutational scanninggenotype–phenotypevariants of uncertain significance

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Area of Science:

  • Genomics and Bioinformatics
  • Molecular Biology
  • Human Genetics

Background:

  • Current human genome sequencing identifies only a fraction of functionally significant sequence variants.
  • Understanding the functional impact of genetic variants is crucial for diagnosing and treating diseases.

Purpose of the Study:

  • To develop a comprehensive framework for mapping functional missense variants in human genes.
  • To identify pathogenic variants and assess the potential of deep mutational scanning (DMS) for disease gene analysis.

Main Methods:

  • Developed a deep mutational scanning (DMS) framework combining random codon mutagenesis and multiplexed functional assays.
  • Utilized computational imputation and refinement to generate exhaustive variant maps.
  • Applied the framework to UBE2I, SUMO1, TPK1, and CALM1/2/3 genes.

Main Results:

  • Generated comprehensive functional maps for missense variants in the studied human genes.
  • The maps successfully recapitulated known protein features and identified pathogenic variations.
  • Demonstrated that DMS assays are potentially applicable to 57% of human disease genes.

Conclusions:

  • The developed DMS framework provides exhaustive maps of human missense variant function.
  • This approach reliably identifies pathogenic variations and has broad applicability to human disease genes.
  • DMS has the potential to map functional variation across all human disease genes.