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Related Concept Videos

Mutations01:35

Mutations

33.0K
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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Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

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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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Mismatch Repair01:36

Mismatch Repair

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Overview
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Multi-species Conserved Sequences02:51

Multi-species Conserved Sequences

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Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale  studies have provided new insights into the evolutionary relationship between organisms.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved...
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DNA as a Genetic Template02:05

DNA as a Genetic Template

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Two structural features of the DNA molecule provide a basis for the mechanisms of heredity: the four nucleotide bases and its double-stranded nature. The Watson-Crick model of double-helical DNA structure, proposed in 1952, drew heavily upon the X-ray crystallography work of researchers Rosalind Franklin and Maurice Wilkins. Watson, Crick, and Wilkins jointly received the Nobel Prize in Physiology or Medicine for their work in 1962. Franklin was, controversially, excluded from the prize for...
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Overview of Transposition and Recombination02:13

Overview of Transposition and Recombination

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Transposons make up a significant part of genomes of various organisms. Therefore, it is believed that transposition played a major evolutionary role in speciation by changing genome sizes and modifying gene expression patterns. For example, in bacteria, transposition can lead to conferring antibiotic resistance. Movement of transposable elements within the genetic pool of pathogenic bacteria can aid in transfer of antibiotic-resistant genetic elements. In eukaryotes, transposons can carry out...
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Related Experiment Video

Updated: May 27, 2025

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
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Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

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Hypermut 3: identifying specific mutational patterns in a defined nucleotide context that allows multistate

Zena Lapp1, Hyejin Yoon1, Brian Foley1

  • 1Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, NM 87545, United States.

Bioinformatics Advances
|February 21, 2025
PubMed
Summary
This summary is machine-generated.

Hypermut 3 software identifies virus hypermutation events, improving sequence analysis accuracy. This updated tool handles complex sequence data, including multistate characters and gaps, for more reliable viral evolution studies.

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Area of Science:

  • Virology
  • Bioinformatics
  • Evolutionary Biology

Background:

  • APOBEC3F and APOBEC3G enzymes induce mutations in viral sequences.
  • Hypermutated sequences can distort analyses of viral evolution.
  • Previous Hypermut versions lacked support for multistate characters and gaps.

Purpose of the Study:

  • To present an updated, user-friendly Hypermut version.
  • To enable detection of hypermutation events considering multistate characters and gaps.
  • To facilitate integration of hypermutation detection into sequence analysis pipelines.

Main Methods:

  • Development of Hypermut 3 in Python 3.
  • Implementation of functionality to handle multistate characters and gaps.
  • Provision of both web and command-line interfaces.

Main Results:

  • Hypermut 3 successfully detects hypermutation events, including G to A mutations.
  • The tool accommodates multistate characters and gaps in sequence alignments.
  • User-friendly web and command-line versions are now available.

Conclusions:

  • Hypermut 3 enhances the accuracy of viral sequence analysis.
  • The updated tool provides a robust method for identifying non-representative viral sequences.
  • This software aids in more reliable studies of viral evolution.