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Related Experiment Video

Updated: Oct 19, 2025

Methods for Performing Crosses in Setaria viridis, a New Model System for the Grasses
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Improving Quantitative Traits in Self-Pollinated Crops Using Simulation-Based Selection With Minimal Crossing.

Daisuke Sekine1,2, Mai Tsuda2,3, Shiori Yabe2

  • 1Institute of Vegetable and Floriculture Science, National Agriculture and Food Research Organization, Tsu, Japan.

Frontiers in Plant Science
|September 20, 2021
PubMed
Summary

A new simulation-based genomic selection strategy improves quantitative traits in self-pollinated crops. This method efficiently identifies superior progeny with reduced crossing efforts, accelerating crop breeding.

Keywords:
genomic predictiongenomic selectionmarker-assisted recurrent selectionquantitative traitseed protein contentsegregation simulationsoybean

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Area of Science:

  • Plant breeding
  • Genomics
  • Quantitative genetics

Background:

  • Genomic selection (GS) and marker-assisted recurrent selection (MARS) are effective for cross-pollinated crops.
  • These methods are challenging in self-pollinated crops due to laborious crossing.

Purpose of the Study:

  • To develop a simulation-based genomic selection strategy for self-pollinated crops.
  • To predict progeny phenotypes for optimal cross combination selection.

Main Methods:

  • Developed a trait prediction model using genomic information.
  • Simulated selection strategy on biparental populations with varying heritability and QTL.
  • Applied the strategy to soybean for seed protein content using SNP markers.

Main Results:

  • The proposed strategy achieved genetic gains equal to or higher than conventional recurrent selection in early cycles.
  • Significantly reduced the number of cross combinations needed per cycle.
  • Successfully increased or decreased seed protein content in soybean progeny.

Conclusions:

  • The simulation-based strategy is effective for rapid improvement of quantitative traits in self-pollinated crops.
  • It minimizes crossing requirements while maximizing genetic gain.
  • Demonstrates potential for efficient crop breeding programs.