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pSBVB: A Versatile Simulation Tool To Evaluate Genomic Selection in Polyploid Species.

María L Zingaretti1, Amparo Monfort2,3, Miguel Pérez-Enciso1,4

  • 1Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB Consortium, 08193 Bellaterra, Barcelona, Spain laura.zingaretti@cragenomica.es miguel.perez@uab.es.

G3 (Bethesda, Md.)
|December 22, 2018
PubMed
Summary

Genomic selection (GS) is effective in polyploid crops, but requires tailored tools. A new simulation software, pSBVB, aids in evaluating GS strategies for these complex species.

Keywords:
GenPredGenomic PredictionGenomic selectionPolyploidsShared Data ResourcesSimulationpSBVB

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Area of Science:

  • Plant Breeding
  • Genetics
  • Bioinformatics

Background:

  • Genomic selection (GS) is widely used in diploid breeding but underutilized in polyploid crops.
  • Polyploid species present unique genetic challenges for breeding programs.

Purpose of the Study:

  • To develop a versatile simulation tool, polyploid Sequence Based Virtual Breeding (pSBVB), for evaluating GS strategies in polyploids.
  • To assess the potential of GS in polyploid breeding and optimize experimental designs.

Main Methods:

  • Developed pSBVB, a gene dropping software simulating complex phenotypes in polyploids.
  • Input includes genotype data (SNP to sequence), causal variants, heritabilities, and pedigree.
  • Simulates both allo- and autopolyploid species by specifying recombination rates.

Main Results:

  • pSBVB can model various phenotypes and genetic architectures in polyploids.
  • Demonstrated pSBVB's utility with tetraploid potato and octoploid strawberry data.
  • Genomic selection shows promise in polyploids, with effectiveness dependent on genetic architecture.

Conclusions:

  • pSBVB is a valuable tool for exploring GS in polyploid species.
  • GS can be a powerful breeding strategy for polyploids, contingent on genetic factors.
  • Further research using pSBVB can optimize breeding designs and strategies for polyploid crops.