Validating the prediction accuracies of marker-assisted and genomic selection of Fusarium head blight resistance in wheat using an independent sample
| Autor: | Odile Argillier, Albert W. Schulthess, Viktor Korzun, Martin W. Ganal, Jörg Plieske, Sonja Kollers, Bernd Rodemann, Jie Ling, Erhard Ebmeyer, Gunther Stiewe, Yong Jiang, Jochen C. Reif, Marion S. Röder |
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| Rok vydání: | 2016 |
| Předmět: |
0106 biological sciences
0301 basic medicine Genetic Markers Genotype Population Quantitative Trait Loci Context (language use) Quantitative trait locus Biology 01 natural sciences 03 medical and health sciences Fusarium Gene Frequency Statistics Genetics education Allele frequency Selection (genetic algorithm) Triticum Disease Resistance Plant Diseases education.field_of_study Models Genetic business.industry fungi Sampling (statistics) Contrast (statistics) Chromosome Mapping Reproducibility of Results General Medicine Genomics Biotechnology Plant Breeding 030104 developmental biology Phenotype business Agronomy and Crop Science 010606 plant biology & botany |
| Zdroj: | TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik. 130(3) |
| ISSN: | 1432-2242 |
| Popis: | Compared with independent validation, cross-validation simultaneously sampling genotypes and environments provided similar estimates of accuracy for genomic selection, but inflated estimates for marker-assisted selection. Estimates of prediction accuracy of marker-assisted (MAS) and genomic selection (GS) require validations. The main goal of our study was to compare the prediction accuracies of MAS and GS validated in an independent sample with results obtained from fivefold cross-validation using genomic and phenotypic data for Fusarium head blight resistance in wheat. In addition, the applicability of the reliability criterion, a concept originally developed in the context of classic animal breeding and GS, was explored for MAS. We observed that prediction accuracies of MAS were overestimated by 127% using cross-validation sampling genotype and environments in contrast to independent validation. In contrast, prediction accuracies of GS determined in independent samples are similar to those estimated with cross-validation sampling genotype and environments. This can be explained by small population differentiation between the training and validation sets in our study. For European wheat breeding, which is so far characterized by a slow temporal dynamic in allele frequencies, this assumption seems to be realistic. Thus, GS models used to improve European wheat populations are expected to possess a long-lasting validity. Since quantitative trait loci information can be exploited more precisely if the predicted genotype is more related to the training population, the reliability criterion is also a valuable tool to judge the level of prediction accuracy of individual genotypes in MAS. |
| Databáze: | OpenAIRE |
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