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Related Concept Videos

Frequency-dependent Selection01:21

Frequency-dependent Selection

When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.Positive Frequency-Dependent SelectionIn positive...
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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)
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Detecting strong positive selection in the genome.

Wolfgang Stephan1

  • 1Section of Evolutionary Biology, Department of Biology, Ludwig-Maximilians University Munich, Munich, Germany.

Molecular Ecology Resources
|May 14, 2011
PubMed
Summary
This summary is machine-generated.

New statistical tests detect positive selection in genomes by analyzing single-nucleotide polymorphism data. These methods help distinguish selection from demographic events, aiding evolutionary studies in various species.

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Area of Science:

  • Population Genetics
  • Evolutionary Biology
  • Genomics

Background:

  • Genome-wide data, including single-nucleotide polymorphism (SNP) and polymorphism data, are increasingly available for diverse species.
  • Distinguishing the effects of positive selection from demographic history is crucial for understanding evolutionary processes.
  • Existing statistical tests for selection were primarily developed for idealized, randomly mating (panmictic) populations.

Purpose of the Study:

  • To review and highlight recent advancements in statistical methods for detecting positive selection from genome-wide data.
  • To emphasize the utility of these methods in differentiating selection from demographic events, especially when considering linkage disequilibrium.
  • To identify the need for extending these powerful analytical tools to more complex, spatially structured populations.

Main Methods:

  • Utilizing newly developed statistical tests that analyze genome-wide single-nucleotide polymorphism data.
  • Incorporating linkage disequilibrium patterns to improve the accuracy of distinguishing selection from demographic history.
  • Applying established methods to available sequence and polymorphism data from model organisms like Drosophila melanogaster, humans, and plants.

Main Results:

  • Recent statistical tests effectively infer evidence of recent strong positive selection.
  • These methods successfully localize targets of selection within the genome.
  • Demographic events can be reliably distinguished from selection, particularly when linkage disequilibrium is considered.

Conclusions:

  • Advanced statistical approaches provide powerful tools for evolutionary inference using genomic data.
  • These methods have been validated across diverse species, demonstrating broad applicability.
  • Future research should focus on adapting these tests for spatially structured populations to maximize their utility.