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Spontaneous and Induced Mutations01:30

Spontaneous and Induced Mutations

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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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Homologous Recombination02:31

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The basic reaction of homologous recombination (HR) involves two chromatids that contain DNA sequences sharing a significant stretch of identity. One of these sequences uses a strand from another as a template to synthesize DNA in an enzyme-catalyzed reaction. The final product is a novel amalgamation of the two substrates. To ensure an accurate recombination of sequences, HR is restricted to the S and G2 phases of the cell cycle. At these stages, the DNA has been replicated already and the...
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A mutation is a change in the sequence of bases of DNA or RNA in a genome. Some mutations occur during replication of the genome due to errors made by the polymerase enzymes that replicate DNA or RNA. Unlike DNA polymerase, RNA polymerase is prone to errors because it is not capable of “proofreading” its work. Viruses with RNA-based genomes, like HIV, therefore accrue mutations faster than viruses with DNA-based genomes. Because mutation and recombination provide the raw material...
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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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Because the DNA segments are cut and reorganized in a direction-specific manner, site-specific recombination has emerged as an efficient genetic engineering technique. Flippase and Cyclization recombinases or Flp and Cre, respectively, are two members of the tyrosine recombinase family derived from bacteriophages, that are used to mediate site-specific DNA insertions, deletions, and targeted expression of proteins in mammalian cell lines.
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Translesion (TLS) polymerases rescue stalled DNA polymerases at sites of damaged bases by replacing the replicative polymerase and installing a nucleotide across the damaged site. Doing so, TLS allows additional time for the cell to repair the damage before resuming regular DNA replication.
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Detection of Homologous Recombination Intermediates via Proximity Ligation and Quantitative PCR in Saccharomyces cerevisiae
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The coalescent with replication-independent mutations.

Stephen M Krone1, Beth M Tuschhoff1

  • 1Department of Mathematics and Statistical Science, University of Idaho, Moscow, Idaho, United States.

Peerj
|February 21, 2022
PubMed
Summary
This summary is machine-generated.

We developed a mathematical model for bacterial genetic diversity, explaining how growth rates and mutations impact diversity. This model provides an unbiased estimator for mutation rates in fluctuating bacterial populations.

Keywords:
CoalescentMicrobial diversityReplication rateReplication-independent mutations

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Area of Science:

  • Population genetics
  • Microbial evolution
  • Mathematical modeling

Background:

  • Bacterial cultures exhibit varying genetic diversity influenced by growth rates.
  • Understanding mutation processes (replication-dependent and independent) is crucial for microbial evolution studies.
  • Existing models may not fully capture the impact of fluctuating growth rates on genetic diversity.

Purpose of the Study:

  • To develop a mathematical framework for the neutral coalescent model incorporating both replication-dependent and replication-independent mutations.
  • To explain and quantify observed differences in genetic diversity in bacterial cultures with varying growth rates.
  • To derive an unbiased estimator for replication-independent mutation rates.

Main Methods:

  • Mathematical modeling of the neutral coalescent.
  • Incorporation of replication-dependent and replication-independent mutation types.
  • Derivation of an estimator using single nucleotide polymorphism counts from cultures with different growth rates.

Main Results:

  • The developed coalescent model successfully explains and quantifies empirical data on genetic diversity differences related to bacterial growth rates.
  • An unbiased and consistent estimator for replication-independent mutation rates was derived.
  • The model quantifies the impact of fluctuating growth rates, relevant to natural bacterial populations.

Conclusions:

  • The neutral coalescent model with both mutation types provides a robust framework for studying bacterial genetic diversity.
  • The derived estimator offers a novel method for quantifying mutation rates in microbial populations.
  • This work enhances our understanding of microbial evolution under varying environmental conditions, including fluctuating growth rates.