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Area of Science:

  • Plant breeding
  • Genomics
  • Bioenergy crops

Background:

  • Genomic selection (GS) accelerates crop improvement by using genomic information for selection.
  • Perennial crops like switchgrass (Panicum virgatum L.) have long breeding cycles, making cost reduction in GS crucial.
  • DNA sequencing represents a significant cost in GS.

Purpose of the Study:

  • To evaluate strategies for reducing DNA sequencing costs in genomic selection for switchgrass.
  • To assess the impact of reduced sequencing on predictive ability and genetic gain.
  • To identify cost-effective GS approaches for perennial crop breeding.

Main Methods:

  • Simulations were performed for two traits (spring vigor, anthesis date) across three breeding populations.
  • Strategies included pooling DNA samples in training populations (TP) and candidate populations (CP), and sequencing TP phenotypic outliers.
  • Predictive ability was measured via cross-validation, and genetic gain was calculated for various sequencing budget scenarios.

Main Results:

  • Sequencing the outlier 50% of TP phenotypes incurred <5% loss in predictive ability.
  • TPs with as few as two phenotypically contrasting DNA samples retained >80% predictive ability.
  • Reduced TP sequencing and most CP pooling methods outperformed individual sequencing under restricted budgets.

Conclusions:

  • Reduced DNA sequencing strategies offer viable cost-saving routes for genomic selection in switchgrass.
  • These methods can maintain high predictive ability, especially under limited sequencing resources.
  • Optimizing sequencing strategies is key to maximizing genetic gain in perennial crop breeding programs.