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A computationally efficient method for approximating reliabilities in large-scale single-step genomic prediction.

Hongding Gao1, Andrei A Kudinov2, Matti Taskinen2

  • 1Natural Resources Institute Finland (Luke), 31600, Jokioinen, Finland. hongding.gao@luke.fi.

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Summary
This summary is machine-generated.

Computationally efficient methods were developed to approximate the reliabilities of genomic estimated breeding values (GEBV) in single-step genomic prediction models. These approximations closely matched exact reliabilities, offering a feasible strategy for large-scale genomic evaluations.

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Area of Science:

  • Animal Breeding and Genetics
  • Quantitative Genetics
  • Genomic Prediction

Background:

  • Accurate estimation of reliabilities for genomic estimated breeding values (GEBV) is crucial for genetic selection.
  • Single-step genomic prediction models incorporating residual polygenic (RPG) effects present computational challenges.
  • Existing methods for calculating GEBV reliabilities require computationally intensive approaches.

Purpose of the Study:

  • To develop and evaluate computationally efficient methods for approximating GEBV reliabilities in single-step genomic prediction.
  • To compare different strategies for accounting for residual polygenic effects.
  • To assess the accuracy of approximated reliabilities against exact calculations.

Main Methods:

  • Two approaches were tested to account for residual polygenic (RPG) effects: a direct method including RPG effects and a blended method weighting genomic and pedigree-based BLUP (PBLUP) reliabilities.
  • A simplified weighted-PBLUP model was used for non-genotyped animals.
  • Five weighting schemes were compared using small and large datasets.

Main Results:

  • Approximated reliabilities using the blended method showed high correlations (0.980–0.996) and slopes close to 1.0 when compared to exact reliabilities across datasets and animal types.
  • The blended method demonstrated strong agreement with exact reliabilities for both genotyped and non-genotyped animals.
  • The best approximation approach achieved correlations of 0.992–0.994 across lactations.

Conclusions:

  • The proposed approximation methods provide accurate estimates of GEBV reliabilities, comparable to exact calculations.
  • The blended method is computationally more feasible than the direct method for including RPG effects, especially in large-scale datasets.
  • This approach offers an effective strategy for estimating GEBV reliabilities in large-scale single-step genomic prediction scenarios.