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Published on: July 16, 2019
Genetic dissection of grain yield in bread wheat. II. QTL-by-environment interaction
H Kuchel1, K Williams, P Langridge
1Australian Grain Technologies Pty Ltd, University of Adelaide, Roseworthy Campus, Roseworthy, SA, 5371, Australia. haydn.kuchel@ausgraintech.com
Abstract:
The grain yield of wheat is influenced by genotype, environment and genotype-by-environment interaction. A mapping population consisting of 182 doubled haploid progeny derived from a cross between the southern Australian varieties 'Trident' and 'Molineux', was used to characterise the interaction of previously mapped grain yield quantitative trait locus (QTL) with specific environmental covariables. Environments (17) used for grain yield assessment were characterised for latitude, rainfall, various temperature-based variables and stripe rust infection severity. The number of days in the growing season in which the maximum temperature exceeded 30 degrees C was identified as the variable with the largest effect on site mean grain yield. However, the greatest QTL-by-environmental covariable interactions were observed with the severity of stripe rust infection. The rust resistance allele at the Lr37/Sr38/Yr17 locus had the greatest positive effect on grain yield when an environment experienced a combination of high-stripe rust infection and cool days. The grain yield QTL, QGyld.agt-4D, showed a very similar QTL-by-environment covariable interaction pattern to the Lr37/Sr38/Yr17 locus, suggesting a possible role in rust resistance or tolerance. Another putative grain yield per se QTL, QGyld.agt-1B, displayed interactions with the quantity of winter and spring rainfall, the number of days in which the maximum temperature exceeded 30 degrees C, and the number of days with a minimum temperature below 10 degrees C. However, no cross-over interaction effect was observed for this locus, and the 'Molineux' allele remained associated with higher grain yield in response to all environmental covariables. The results presented here confirm that QGyld.agt-1B may be a prime candidate for marker-assisted selection for improved grain yield and wide adaptation in wheat. The benefit of analysing the interaction of QTL and environmental covariables, such as employed here, is discussed.
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