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Cold stress tolerance of soybeans during flowering: QTL mapping and efficient selection strategies under controlled conditions
Author(s) -
Jähne Felix,
Balko Christiane,
Hahn Volker,
Würschum Tobias,
Leiser Willmar L.
Publication year - 2019
Publication title -
plant breeding
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.583
H-Index - 71
eISSN - 1439-0523
pISSN - 0179-9541
DOI - 10.1111/pbr.12734
Subject(s) - biology , quantitative trait locus , point of delivery , cultivar , selection (genetic algorithm) , population , trait , marker assisted selection , genetics , agronomy , gene , demography , artificial intelligence , sociology , computer science , programming language
Abstract Breeding soybeans for higher latitudes requires cultivars with an increased chilling stress tolerance, especially when flowering occurs. Phenotyping in climate chambers to select for this trait is labour‐intensive and requires an optimal allocation of resources due to limited space. We screened a diversity panel of 35 early maturity cultivars and a biparental population of 103 RILs for their cold stress tolerance at flowering stage. Pod number under control and stress conditions is highly heritable and showed only a weak correlation between the two treatments. Based on different testing scenarios, we could show that testing more genotypes with less replicates yields much higher responses to selection and hence should be pursued in such climate‐controlled experiments. We identified quantitative trait loci (QTL) for pod number under both conditions (chromosomes 7 and 13) and a cold tolerance‐specific QTL (chromosome 11). Furthermore, we performed genomic predictions using different test set scenarios and prediction models, showing that genomic prediction is a promising tool to select for cold stress tolerance, particularly if known QTL can be used as fixed effects in the model.