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Related Concept Videos

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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Mutations01:35

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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
While point mutations are changes in a single nucleotide in...
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To learn more about the function of a gene, researchers can observe what happens when the gene is inactivated or “knocked out,” by creating genetically engineered knockout animals. Knockout mice have been particularly useful as models for human diseases such as cancer, Parkinson’s disease, and diabetes.
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Mutations are heritable changes in an organism’s genome involving alterations in the base sequence of DNA or RNA. These changes can influence cellular processes and phenotypic traits, potentially transforming the unaltered wild type into a mutant form. Such changes, termed forward mutations, are pivotal in shaping the genetic diversity of organisms.RNA viruses exhibit the highest mutation rates due to the absence of robust proofreading mechanisms during genome replication. In contrast,...
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Spontaneous mutations arise infrequently during DNA replication due to errors in the process. A key factor behind these errors is tautomeric shifts in nitrogenous bases, where bases transition from keto to enol forms or amino to imino forms. This shift can alter base-pairing rules, leading to mutations. Additionally, reactive oxygen species (ROS) arising from aerobic metabolism can damage DNA, resulting in depurination (loss of a purine base) or depyrimidination (loss of a pyrimidine base).
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Visualizing Genetic Variants, Short Targets, and Point Mutations in the Morphological Tissue Context with an RNA In Situ Hybridization Assay
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Vermont: a multi-perspective visual interactive platform for mutational analysis.

Alexandre V Fassio1,2, Pedro M Martins3,4, Samuel da S Guimarães5

  • 1Department of Computer Science, Universidade Federal de Minas Gerais, 6627, Antônio Carlos avenue, Pampulha, Belo Horizonte, 31270-901, Brazil. alexandrefassio@dcc.ufmg.br.

BMC Bioinformatics
|September 21, 2017
PubMed
Summary

VERMONT 2.0 is a new visual analytics platform that helps researchers understand the impact of protein point mutations. It combines sequence and structural data with interactive visualizations to identify damaging mutations and their effects.

Keywords:
Complex networkIntramolecular networkMutational analysisPoint mutationVisual analytics platform

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Vast genomic and sequence variation data necessitates computational tools for mutation impact assessment.
  • Experimental characterization of all mutations is infeasible due to scale.
  • Understanding mutation effects on protein structure and function is critical for disease association.

Purpose of the Study:

  • To introduce VERMONT 2.0, a visual interactive platform for analyzing protein point mutations.
  • To provide a novel visual analytics approach for gaining insights into mutation impacts.
  • To enhance the understanding of how mutations affect protein structure and function.

Main Methods:

  • VERMONT 2.0 integrates sequence and structural parameters.
  • The platform utilizes interactive visualizations for data exploration.
  • A set of experimentally characterized mutations was visually examined using VERMONT.

Main Results:

  • VERMONT 2.0 facilitates the identification of damaging mutations.
  • The platform helps elucidate the reasons behind a mutation's damaging potential.
  • Visual analysis revealed position-specific structural and physicochemical properties influencing mutation impact.

Conclusions:

  • VERMONT enables understanding mutations through position-specific properties.
  • The platform aids in interpreting the structural and physicochemical basis of mutation effects.
  • Specific mutation positions with significant impact on protein function/structure were identified.