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Law of Segregation01:49

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When crossing pea plants, Mendel noticed that one of the parental traits would sometimes disappear in the first generation of offspring, called the F1 generation, and could reappear in the next generation (F2). He concluded that one of the traits must be dominant over the other, thereby causing masking of one trait in the F1 generation. When he crossed the F1 plants, he found that 75% of the offspring in the F2 generation had the dominant phenotype, while 25% had the recessive phenotype.
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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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The principle of natural selection posits that organisms better adapted to their environment are more likely to survive and reproduce. This principle is closely intertwined with mating preferences, a key aspect of sexual selection, which evolutionary psychologists believe is driven by instincts to propagate one's genes. Such instincts significantly influence mating behaviors and preferences between genders.
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Law of Independent Assortment02:03

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While Mendel’s Law of Segregation states that the two alleles for one gene are separated into different gametes, a different question of how different genes are inherited remains. For example, is the gene for tall plants inherited with the gene for green peas? Mendel asked this question by experimenting with a dihybrid cross; a cross in which both parents are homozygous for two distinct traits resulting in an F1 generation that are heterozygous for both traits.
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In 1866, Gregor Mendel published the results of his pea plant breeding experiments, providing evidence for predictable patterns in the inheritance of physical characteristics. The significance of his findings was not immediately recognized. In fact, the existence of genes was unknown at the time. Mendel referred to hereditary units as “factors.”
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Assessing Differences in Sperm Competitive Ability in Drosophila
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Selection theory for selfed progenies.

N M Cowen1

  • 1Department of Agronomy, University of Missouri, 65211, Columbia, MO, USA.

TAG. Theoretical and Applied Genetics. Theoretische Und Angewandte Genetik
|November 19, 2013
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Summary
This summary is machine-generated.

This study generalizes a model for predicting selection response in selfed progeny by incorporating multiple alleles per locus. The new model simplifies calculations and provides a framework for estimating key genetic parameters for improved breeding strategies.

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Area of Science:

  • Quantitative Genetics
  • Plant Breeding

Background:

  • Predicting selection response is crucial for crop and livestock improvement.
  • Existing models often simplify genetic complexity, limiting their applicability.

Purpose of the Study:

  • To extend existing models for predicting selection response in selfed progeny.
  • To develop a generalized model accommodating multiple alleles and frequencies at each locus.

Main Methods:

  • Simplified derivation and calculation of condensed coefficients of identity.
  • Expressed genetic variances within and among selfed progenies as a linear function of population parameters.
  • Developed selection response equations for selfed progenies based on population parameters.
  • Identified progeny sets for estimating population parameters.

Main Results:

  • The study presents a generalized model for predicting selection response in selfed progeny.
  • Introduced a framework using five population parameters: additive variance, dominance variance, covariance of additive and homozygous dominance deviations, variance of homozygous dominance deviations, and inbreeding depression.

Conclusions:

  • The generalized model enhances the prediction of selection response in selfed progenies.
  • The five population parameters provide a comprehensive basis for estimating genetic gains in breeding programs.