Genomic assisted selection for enhancing line breeding: merging genomic and phenotypic selection in winter wheat breeding programs with preliminary yield trials.
Early generation genomic selection is superior to conventional phenotypic selection in line breeding and can be strongly improved by including additional information from preliminary yield trials. The selection of lines that enter resource-demanding multi-environment trials is a crucial decision in every line breeding program as a large amount of resources are allocated for thoroughly testing these potential varietal candidates. We compared conventional phenotypic selection with various genomic selection approaches across multiple years as well as the merit of integrating phenotypic information from preliminary yield trials into the genomic selection framework. The prediction accuracy using only phenotypic data was rather low (r = 0.21) for grain yield but could be improved by modeling genetic relationships in unreplicated preliminary yield trials (r = 0.33). Genomic selection models were nevertheless found to be superior to conventional phenotypic selection for predicting grain yield performance of lines across years (r = 0.39). We subsequently simplified the problem of predicting untested lines in untested years to predicting tested lines in untested years by combining breeding values from preliminary yield trials and predictions from genomic selection models by a heritability index. This genomic assisted selection led to a 20% increase in prediction accuracy, which could be further enhanced by an appropriate marker selection for both grain yield (r = 0.48) and protein content (r = 0.63). The easy to implement and robust genomic assisted selection gave thus a higher prediction accuracy than either conventional phenotypic or genomic selection alone. The proposed method took the complex inheritance of both low and high heritable traits into account and appears capable to support breeders in their selection decisions to develop enhanced varieties more efficiently.
Department for Agrobiotechnology (IFA-Tulln), Institute for Biotechnology in Plant Production, University of Natural Resources and Life Sciences, Vienna (BOKU), Konrad-Lorenz-Str. 20, 3430, Tulln, Austria.
Sebastian
S
Michel
Saatzucht Donau GesmbH and CoKG, Saatzuchtstrasse 11, 2301, Probstdorf, Austria.
Christian
C
Ametz
ProGen Seed A.Ş, Büyükdalyan Mah. 2. Küme evler Sok., No: 49, 31001, Antakya, Hatay, Turkey.|Faculty of Agriculture and Natural Sciences, Department of Field Crops, University of Düzce, 81620, Düzce, Turkey.
Huseyin
H
Gungor
ProGen Seed A.Ş, Büyükdalyan Mah. 2. Küme evler Sok., No: 49, 31001, Antakya, Hatay, Turkey.
Batuhan
B
Akgöl
Probstdorfer Saatzucht Romania SRL, Str. Siriului Nr. 20, Sect. 1, Bucharest, Romania.
Doru
D
Epure
Plant Breeding Division, Department of Crop Science, University of Natural Resources and Life Sciences, Vienna (BOKU), Konrad-Lorenz-Str. 24, 3430, Tulln, Austria.
Heinrich
H
Grausgruber
Saatzucht Donau GesmbH and CoKG, Saatzuchtstrasse 11, 2301, Probstdorf, Austria.
Franziska
F
Löschenberger
Department for Agrobiotechnology (IFA-Tulln), Institute for Biotechnology in Plant Production, University of Natural Resources and Life Sciences, Vienna (BOKU), Konrad-Lorenz-Str. 20, 3430, Tulln, Austria. hermann.buerstmayr@boku.ac.at.
Hermann
H
Buerstmayr
D002523:Edible Grain / Q000254:growth & development; D023281:Genomics / Q000379:methods*; D010641:Phenotype; D000069600:Plant Breeding / Q000379:methods*; D012641:Selection, Genetic; D014908:Triticum / Q000235:genetics*