title: Prediction of hybrid performance in maize with a ridge regression model employed to DNA markers and mRNA transcription profiles.
abstract: BACKGROUND
  Ridge regression models can be used for predicting heterosis and hybrid performance. Their application to mRNA transcription profiles has not yet been investigated. Our objective was to compare the prediction accuracy of models employing mRNA transcription profiles with that of models employing genome-wide markers using a data set of 98 maize hybrids from a breeding program.
  
  
  RESULTS
  We predicted hybrid performance and mid-parent heterosis for grain yield and grain dry matter content and employed cross validation to assess the prediction accuracy. Prediction with a ridge regression model using random effects for mRNA transcription profiles resulted in similar prediction accuracies than employing the model to DNA markers. For hybrids, of which none of the parental inbred lines was part of the training set, the ridge regression model did not reach the prediction accuracy that was obtained with a model using transcriptome-based distances.
  
  
  CONCLUSIONS
  We conclude that mRNA transcription profiles are a promising alternative to DNA markers for hybrid prediction, but further studies with larger data sets are required to investigate the superiority of alternative prediction models.
authors.affiliation: Institute of Agronomy and Plant Breeding II, Justus Liebig University, Giessen, 35392, Germany.
authors.forename: Carola
authors.initials: C
authors.lastname: Zenke-Philippi
authors.affiliation: Biocenter Klein Flottbek, Developmental Biology and Biotechnology, University of Hamburg, Hamburg, 22609, Germany.
authors.forename: Alexander
authors.initials: A
authors.lastname: Thiemann
authors.affiliation: Biocenter Klein Flottbek, Developmental Biology and Biotechnology, University of Hamburg, Hamburg, 22609, Germany.
authors.forename: Felix
authors.initials: F
authors.lastname: Seifert
authors.affiliation: Institute of Plant Breeding, Seed Science, and Population Genetics, University of Hohenheim, Stuttgart, 70593, Germany.
authors.forename: Tobias
authors.initials: T
authors.lastname: Schrag
authors.affiliation: Institute of Plant Breeding, Seed Science, and Population Genetics, University of Hohenheim, Stuttgart, 70593, Germany.
authors.forename: Albrecht E
authors.initials: AE
authors.lastname: Melchinger
authors.affiliation: Biocenter Klein Flottbek, Developmental Biology and Biotechnology, University of Hamburg, Hamburg, 22609, Germany.|Institute of Plant Breeding, Seed Science, and Population Genetics, University of Hohenheim, Stuttgart, 70593, Germany.
authors.forename: Stefan
authors.initials: S
authors.lastname: Scholten
authors.affiliation: Institute of Agronomy and Plant Breeding II, Justus Liebig University, Giessen, 35392, Germany. matthias.frisch@uni-giessen.de.
authors.forename: Matthias
authors.initials: M
authors.lastname: Frisch
mesh_terms: D054458:Amplified Fragment Length Polymorphism Analysis; D005819:Genetic Markers; D006823:Hybrid Vigor; D008957:Models, Genetic; D000069600:Plant Breeding; D012333:RNA, Messenger / Q000235:genetics; D012044:Regression Analysis; D059467:Transcriptome; D003313:Zea mays / Q000235:genetics*
chemical_list: D005819:Genetic Markers; D012333:RNA, Messenger