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Related Concept Videos

Frequency-dependent Selection01:21

Frequency-dependent Selection

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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.
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Types of Selection01:46

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Natural selection influences the frequencies of particular alleles and phenotypes within populations in several different ways. Primarily, natural selection can be directional, stabilizing, or disruptive. Directional selection favors one extreme trait and shifts the population towards that phenotype while selecting against individuals displaying alternate traits. Stabilizing selection favors an intermediate trait with a narrow range of variation. Deviation from the optimal phenotype towards an...
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Expected Frequencies in Goodness-of-Fit Tests01:19

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A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n)  to the number of categories (k).
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Hardy-Weinberg Principle01:49

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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.
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Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual...
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Behavior genetics explores how genetic inheritance influences human behavior. It focuses on how genes, passed from parents to offspring, contribute to the development of behavioral traits and tendencies. This branch of genetics seeks to understand the complex interplay between inherited genetic factors and environmental influences in shaping our behaviors.
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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
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Characterizing selection on complex traits through conditional frequency spectra.

Roshni A Patel1,2, Clemens L Weiß3, Huisheng Zhu4

  • 1Department of Genetics, Stanford University, Stanford, CA 94305, USA.

Genetics
|December 18, 2024
PubMed
Summary
This summary is machine-generated.

Genome-wide association studies (GWAS) face ascertainment bias. This study introduces conditional frequency spectra to reveal selection acting on complex traits, offering insights into genetic variant behavior.

Keywords:
GWASallele frequency spectracomplex traitspolygenic scoresselection

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Area of Science:

  • Population Genetics
  • Genomics
  • Evolutionary Biology

Background:

  • Genome-wide association studies (GWAS) are powerful tools for identifying genetic variants associated with complex traits.
  • However, the ascertainment process in GWAS introduces biases, complicating the study of natural selection acting on these traits.
  • The frequency and effect size of a variant are interdependent under selection, influencing its detectability in GWAS.

Purpose of the Study:

  • To address ascertainment biases in GWAS by proposing a novel approach using conditional frequency spectra.
  • To investigate the impact of natural selection and demographic history on allele frequency dynamics.
  • To analyze empirical data for complex traits to detect evidence of selection.

Main Methods:

  • Characterized allele frequency dynamics under selection and non-equilibrium demography.
  • Developed and analyzed conditional frequency spectra based on GWAS cohort frequencies.
  • Investigated empirical conditional frequency spectra for variants associated with 106 complex traits.

Main Results:

  • Demonstrated that conditional frequency spectra can reveal selection biases inherent in GWAS.
  • Found compelling evidence for stabilizing or purifying selection acting on variants associated with complex traits.
  • Showcased the utility of conditional frequency spectra for understanding polygenic score portability.

Conclusions:

  • Conditional frequency spectra offer a robust method to study natural selection on complex traits, overcoming GWAS ascertainment limitations.
  • The findings provide crucial insights into the evolutionary forces shaping complex traits and the properties of GWAS-ascertained variants.
  • This approach enhances our understanding of genetic architecture and its implications for predictive genetic modeling.