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Viral nervous necrosis resistance in gilthead sea bream (Sparus aurata) at the larval stage: heritability and accuracy of genomic prediction with different training and testing settings.

Sara FaggionPaolo CarnierRafaella FranchMassimiliano BabbucciFrancesco PascoliGiulia Dalla RovereMassimo CaggianoHervé ChavanneAnna ToffanLuca Bargelloni
Published in: Genetics, selection, evolution : GSE (2023)
The estimate of the heritability for VNN symptomatology indicates that it is feasible to implement selective breeding programs for increased resistance to VNN of sea bream larvae/juveniles. Exploiting genomic information offers the opportunity of developing prediction tools for VNN resistance, and genomic models can be trained on EBV using all data or phenotypes, with minimal differences in classification performance of the trait phenotype. In a long-term view, the weakening of the genomic ties between animals in the training and test sets leads to decreased genomic prediction accuracies, thus periodical update of the reference population with new data is mandatory.
Keyphrases
  • copy number
  • machine learning
  • big data
  • electronic health record
  • deep learning
  • public health
  • dna methylation