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Related Concept Videos

Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).Mechanisms of Genetic VariationThe original sources of genetic variation are mutations,...
Complementation Tests00:49

Complementation Tests

A complementation test is a simple cross to identify whether the two mutations are located on the same gene or different genes. It was first performed by Edward Lewis in the 1940s while working on fruit flies. He developed the test to identify the location and arrangement of different mutations on chromosomes.
Organisms heterozygous for different mutations are crossed pairwise in all combinations. If present on different genes, the mutations can complement each other by providing the missing...
Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.In the early 20th century,...
Gene Conversion02:08

Gene Conversion

Other than maintaining genome stability via DNA repair, homologous recombination plays an important role in diversifying the genome. In fact, the recombination of sequences forms the molecular basis of genomic evolution. Random and non-random permutations of genomic sequences create a library of new amalgamated sequences. These newly formed genomes can determine the fitness and survival of cells. In bacteria, homologous and non-homologous types of recombination lead to the evolution of new...
Gene Conversion02:08

Gene Conversion

Other than maintaining genome stability via DNA repair, homologous recombination plays an important role in diversifying the genome. In fact, the recombination of sequences forms the molecular basis of genomic evolution. Random and non-random permutations of genomic sequences create a library of new amalgamated sequences. These newly formed genomes can determine the fitness and survival of cells. In bacteria, homologous and non-homologous types of recombination lead to the evolution of new...
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Spontaneous and Induced Mutations

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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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
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The mutation process in colored coalescent theory.

Jianjun Paul Tian1, Xiao-Song Lin

  • 1Mathematics Department, The College of William and Mary, Williamsburg, VA, 23187, USA. jptian@math.wm.edu

Bulletin of Mathematical Biology
|May 23, 2009
PubMed
Summary
This summary is machine-generated.

This study integrates mutation processes into colored coalescent theory, modeling mutations as a Poisson process on genealogical trees. The findings provide new insights into the expected time to reach a most recent common ancestor (MRCA) in colored populations.

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Area of Science:

  • Population Genetics
  • Mathematical Biology
  • Evolutionary Biology

Background:

  • The colored coalescent theory models population genetics with distinct genetic types.
  • Incorporating mutation processes is crucial for understanding evolutionary dynamics.

Purpose of the Study:

  • To introduce and analyze the effect of mutation processes within the colored coalescent framework.
  • To compute expected coalescent times and probabilities in the presence of mutations and color changes.

Main Methods:

  • Modeling mutations as an independent Poisson process on a colored genealogical random tree.
  • Analyzing the colored coalescent process with superimposed mutation dynamics.
  • Deriving explicit computations for expected coalescent times and probabilities.

Main Results:

  • The study quantifies how mutations affect the time to reach a most recent common ancestor (MRCA) in colored populations.
  • When x=1/2, the expected time to reach a black or white MRCA is (3 - 2/n) with 1/2 probability, irrespective of mutation rate (micro).
  • The overall expected time to reach any MRCA (black or white) is (2 - 2/n), matching the standard Kingman coalescent process.

Conclusions:

  • The colored coalescent theory, when extended with mutation processes, offers a robust framework for population genetics modeling.
  • Mutation dynamics influence specific color-based coalescent events but not the overall expected time to the first MRCA.
  • This research provides valuable analytical tools for studying the evolutionary history of populations with distinct genetic variations.