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Front. Plant Sci. | doi: 10.3389/fpls.2018.00159

Prospects and potential uses of genomic prediction of key performance traits in tetraploid potato

  • 1Institute for Quantitative Genetics and Genomics of Plants, Heinrich Heine Universität Düsseldorf, Germany
  • 2Cluster of Excellence on Plant Sciences, Germany

Genomic prediction is a routine tool in breeding programs of most major animal and
plant species. However, its usefulness for potato breeding has not yet been evaluated
in detail. The objectives of this study were to (i) examine the prospects of genomic
prediction of key performance traits in a diversity panel of tetraploid potato modeling
additive, dominance, and epistatic effects, (ii) investigate the effects of size and make
up of training set, number of test environments and molecular markers on prediction accuracy, and (iii) assess the effect of including markers from candidate genes
on the prediction accuracy. With genomic best linear unbiased prediction (GBLUP),
BayesA, BayesCpi, and Bayesian LASSO, four different prediction methods were used
for genomic prediction of relative area under disease progress curve after a Phytophthora infestans infection, plant maturity, maturity corrected resistance, tuber starch
content, tuber starch yield (TSY), and tuber yield (TY) of 184 tetraploid potato
clones or subsets thereof genotyped with the SolCAP 8.3k SNP array. The cross
validated prediction accuracies with GBLUP and the three Bayesian approaches for
the six evaluated traits ranged from about 0.5 to about 0.8. For traits with a high expected genetic complexity, such as TSY and TY, we observed an 8% higher prediction
accuracy using a model with additive and dominance effects compared with a model
with additive effects only. Our results suggest that for oligogenic traits in general and
when diagnostic markers are available in particular, the use of Bayesian methods for
genomic prediction is highly recommended and that the diagnostic markers should
be modeled as fixed effects. The evaluation of the relative performance of genomic
prediction vs. phenotypic selection indicated that the former is superior, assuming
cycle lengths and selection intensities that are possible to realize in commercial potato
breeding programs.

Keywords: Genomic prediction, Tetraploid potato, Phytophthora infestans, maturity, Tuber starch content, Tuber yield

Received: 20 Nov 2017; Accepted: 29 Jan 2018.

Edited by:

Rodomiro Ortiz, Swedish University of Agricultural Sciences, Sweden

Reviewed by:

Craig Yencho, North Carolina State University, United States
Paulino Pérez-Rodríguez, Inicio COLPOS, Mexico  

Copyright: © 2018 Stich and Van Inghelandt. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Mr. Benjamin Stich, Heinrich Heine Universität Düsseldorf, Institute for Quantitative Genetics and Genomics of Plants, Düsseldorf, 40225, Germany, benjamin.stich@hhu.de