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Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
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Small population sizes put a species at extreme risk of extinction due to a lack of variation, and a consequent decrease in adaptability. This weakens the chances of survival under pressures such as climate change, competition from other species, or new diseases. Large populations are more likely to survive pressures such as these, as such populations are more likely to harbor individuals that have genetic variants that are adaptive under new stresses. Small populations are much less...
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Improving Response in Genomic Selection with a Population-Based Selection Strategy: Optimal Population Value

Matthew Goiffon1, Aaron Kusmec2, Lizhi Wang3

  • 1Department of Industrial and Manufacturing Systems Engineering, Iowa State University, Ames, Iowa 50011.

Genetics
|May 21, 2017
PubMed
Summary
This summary is machine-generated.

Optimal Population Value (OPV) selection enhances genetic gain by evaluating breeding merit within subsets of a population. This new method, focusing on complementarity, outperforms existing genomic selection strategies.

Keywords:
GenPredgenetic gaingenomic selectionoptimal haploid valueoptimal population valuepopulation-based selectionshared data resource

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Area of Science:

  • Plant and Animal Breeding
  • Quantitative Genetics
  • Genomics

Background:

  • Genomic selection (GS) uses genomic estimated breeding values (GEBVs) for enhanced genetic gain in breeding programs.
  • Extensions like weighted genomic selection (WGS), optimal haploid value (OHV) selection, and genotype building (GB) selection aim to improve long-term response and doubled haploid development.

Purpose of the Study:

  • Introduce optimal population value (OPV) selection, a novel method evaluating the breeding merit of a set of individuals.
  • Compare OPV selection against GS, WGS, OHV, and GB selection in simulation studies.
  • Investigate the potential for improved selection methods based on individual complementarity.

Main Methods:

  • Genomic selection (GS) based on GEBVs.
  • Weighted genomic selection (WGS).
  • Optimal haploid value (OHV) selection.
  • Genotype building (GB) selection.
  • Optimal population value (OPV) selection, evaluating the maximum haploid value within a population subset.

Main Results:

  • OPV and GB selection demonstrated superior responses compared to GS, WGS, and OHV selection.
  • OPV selection consistently outperformed GB selection across most percentiles.
  • The study suggests that an individual's value can be enhanced by its complementarity with other individuals.

Conclusions:

  • Optimal population value (OPV) selection represents a significant advancement in breeding program strategies.
  • Selection methods considering individual complementarity offer a new paradigm for maximizing genetic gain.
  • OPV selection shows promise for more efficient and effective breeding programs.