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Haplotype-Based Genome-Wide Prediction Models Exploit Local Epistatic Interactions Among Markers.

Yong Jiang1, Renate H Schmidt1, Jochen C Reif2

  • 1Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466 Stadt Seeland, Germany.

G3 (Bethesda, Md.)
|March 18, 2018
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Summary

Haplotype-based genome-wide prediction models, like HGBLUP, outperform marker-based models by leveraging local epistatic effects. This computational efficiency makes them valuable for analyzing complex traits with dense SNP data, particularly in breeding applications.

Keywords:
GenPredGenomic SelectionShared Data Resourcesepistasisgenome-wide predictionhaplotypelocal epistatic effect

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Area of Science:

  • Quantitative genetics
  • Genomic prediction
  • Statistical genomics

Background:

  • Genome-wide prediction models are crucial for complex trait analysis.
  • Haplotype-based models may offer advantages over marker-based approaches.
  • Understanding the role of local epistasis in genomic prediction is key.

Purpose of the Study:

  • To compare marker-based and haplotype-based genome-wide prediction models.
  • To investigate if haplotype models account for local epistatic effects.
  • To determine conditions favoring haplotype-based model superiority.

Main Methods:

  • Theoretical derivation showing LEGBLUP's transformability to HGBLUP.
  • Simulation studies to validate theoretical findings.
  • Application of HGBLUP and marker-based models to mouse and crop datasets.

Main Results:

  • Haplotype-based models (HGBLUP) formally account for local epistatic effects.
  • HGBLUP demonstrated higher prediction accuracies in a mouse population.
  • Benefits of HGBLUP over marker-based models were trait-dependent in crop populations.

Conclusions:

  • Haplotype-based models are effective tools for genomic prediction, especially with ultra-high-density SNP data.
  • HGBLUP's ability to capture local epistasis is relevant for animal and plant breeding.
  • The inheritance of local epistatic effects mirrors additive effects, enhancing breeding value prediction.