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Emerging issues in genomic selection.

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Summary
This summary is machine-generated.

Genomic selection (GS) offers successful breeding across species, but long-term effects and prediction stability require further research. Addressing issues in genome-wide association studies (GWAS) and genomic parameter estimation is crucial for robust genomic predictions.

Keywords:
genomic evaluationgenomic selectiongenomwide association studieslarge datastability of genomic predictions

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Area of Science:

  • Animal breeding and genetics
  • Quantitative genetics
  • Genomic selection

Background:

  • Genomic selection (GS) is widely applied but faces challenges in long-term effects, parameter estimation, and prediction stability.
  • Current research often focuses on pairwise linkage disequilibrium, potentially overlooking higher-order effects like phantom dominance and epistasis.
  • The Bulmer effect can reduce additive variance, though increased recombination rates may release new genetic variance.

Purpose of the Study:

  • To summarize key findings and ongoing questions in genomic selection presented at the 2020 ASAS symposium.
  • To discuss challenges in estimating genomic parameters, robustness of genome-wide association studies (GWAS), and stability of genomic predictions.
  • To highlight areas needing further research in the field of genomic selection.

Main Methods:

  • Review and synthesis of presentations from the 2020 American Society of Animal Science (ASAS) symposium.
  • Discussion of computational strategies for estimating genetic parameters with dense genomic data, including sparse matrix algorithms and selective genotyping.
  • Analysis of different Genome-Wide Association Study (GWAS) models and their performance with varying dataset sizes, including single-step GBLUP.

Main Results:

  • Estimates of genetic parameters can be biased by genomic preselection, and computational costs increase with dense genomic data.
  • GWAS with small datasets often yield many associations, while large datasets yield few, potentially due to model artifacts.
  • Genomic predictions can fluctuate, impacting confidence, unlike traditional evaluations; basing decisions on groups of animals is a proposed solution.

Conclusions:

  • While significant progress has been made in genomic selection, critical questions regarding long-term impacts, parameter estimation accuracy, and prediction stability persist.
  • Robust GWAS require realistic models, consideration of population structure, and appropriate handling of genotyped and ungenotyped animals.
  • Further research is essential to address the complexities of genomic selection and ensure its reliable application in animal breeding.