WhoGEM: an admixture-based prediction machine accurately predicts quantitative functional traits in plants.

Journal: Genome biology
PMID:

Abstract

The explosive growth of genomic data provides an opportunity to make increased use of sequence variations for phenotype prediction. We have developed a prediction machine for quantitative phenotypes (WhoGEM) that overcomes some of the bottlenecks limiting the current methods. We demonstrated its performance by predicting quantitative disease resistance and quantitative functional traits in the wild model plant species, Medicago truncatula, using geographical locations as covariates for admixture analysis. The method's prediction reliability equals or outperforms all existing algorithms for quantitative phenotype prediction. WhoGEM analysis produces evidence that variation in genome admixture proportions explains most of the phenotypic variation for quantitative phenotypes.

Authors

  • Laurent Gentzbittel
    EcoLab, Université de Toulouse, CNRS, Avenue de l'Agrobiopole BP 32607, Auzeville-Tolosane, F-31326, Castanet-Tolosan, France. gentz@ensat.fr.
  • Cécile Ben
    EcoLab, Université de Toulouse, CNRS, Avenue de l'Agrobiopole BP 32607, Auzeville-Tolosane, F-31326, Castanet-Tolosan, France.
  • Mélanie Mazurier
    EcoLab, Université de Toulouse, CNRS, Avenue de l'Agrobiopole BP 32607, Auzeville-Tolosane, F-31326, Castanet-Tolosan, France.
  • Min-Gyoung Shin
    University of Southern California, 1050 Childs Way (USC), Los Angeles, CA, 90089-0371, USA.
  • Todd Lorenz
    University of La Verne, 1950 3rd Street, La Verne, CA, 91750, USA.
  • Martina Rickauer
    EcoLab, Université de Toulouse, CNRS, Avenue de l'Agrobiopole BP 32607, Auzeville-Tolosane, F-31326, Castanet-Tolosan, France.
  • Paul Marjoram
    University of Southern California, 1050 Childs Way (USC), Los Angeles, CA, 90089-0371, USA.
  • Sergey V Nuzhdin
    University of Southern California, 1050 Childs Way (USC), Los Angeles, CA, 90089-0371, USA.
  • Tatiana V Tatarinova
    University of La Verne, 1950 3rd Street, La Verne, CA, 91750, USA.