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Genomic prediction of synthetic hexaploid wheat upon tetraploid durum and diploid Aegilops parental pools.

Susanne DreisigackerJohannes W R MartiniJaime CuevasPaulino Pérez-RodríguezNerida Lozano-RamírezJulio HuertaPawan Kumar SinghLeonardo Crespo-HerreraAlison R BentleyJosé Crosa
Published in: The plant genome (2024)
Bread wheat (Triticum aestivum L.) is a globally important food crop, which was domesticated about 8-10,000 years ago. Bread wheat is an allopolyploid, and it evolved from two hybridization events of three species. To widen the genetic base in breeding, bread wheat has been re-synthesized by crossing durum wheat (Triticum turgidum ssp. durum) and goat grass (Aegilops tauschii Coss), leading to so-called synthetic hexaploid wheat (SHW). We applied the quantitative genetics tools of "hybrid prediction"-originally developed for the prediction of wheat hybrids generated from different heterotic groups - to a situation of allopolyploidization. Our use-case predicts the phenotypes of SHW for three quantitatively inherited global wheat diseases, namely tan spot (TS), septoria nodorum blotch (SNB), and spot blotch (SB). Our results revealed prediction abilities comparable to studies in 'traditional' elite or hybrid wheat. Prediction abilities were highest using a marker model and performing random cross-validation, predicting the performance of untested SHW (0.483 for SB to 0.730 for TS). When testing parents not necessarily used in SHW, combination prediction abilities were slightly lower (0.378 for SB to 0.718 for TS), yet still promising. Despite the limited phenotypic data, our results provide a general example for predictive models targeting an allopolyploidization event and a method that can guide the use of genetic resources available in gene banks.
Keyphrases
  • copy number
  • genome wide
  • dna methylation
  • machine learning
  • electronic health record
  • mass spectrometry
  • single cell
  • risk assessment
  • climate change
  • big data
  • neural network