552-2 Nature of Genotype-Environment Interaction as Revealed by Analysis of Quantitative Trait Loci in a Doubled Haploid Barley Population.

Monday, 6 October 2008
George R. Brown Convention Center, Exhibit Hall E
Rong-Cai Yang, University of Alberta, Edmonton, AB, CANADA and Bong Joo Ham, Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
The presence of genotype-environment interactions (GxE) would lead to an imperfect genetic correlation between measurements of the same quantitative traits over environments, suggesting that not all quantitative trait loci (QTL) are shared by all environments. However, zero correlation does not necessarily mean a total lack of QTL sharing but it could actually result from the canceling of cumulative positive and negative QTL effects. This presentation analyzes the yield and QTL data obtained from the North America Barley Genome Mapping Project (NABGMP, http://wheat.pw.usda.gov) to dissect the nature and cause of GxE based on the patterns of QTL sharing. In NABGMP, yield data of 150 doubled haploid lines derived from the cross between two malting barley cultivars, Steptoe and Morex, evaluated in 16 environments; a total of 223 RFLP makers were mapped on 7 chromosomes of barley. Phenotypic correlations between 120 (16x15/2) pairs of 16 environments were calculated. These pairs were clustered into four groups in the following two-way table, depending on whether or not there is significant correlation and whether or not there is QTL sharing. At least one QTL was common in 52 pairs of environments (i.e., QTL sharing) but 10 of those pairs did not lead to significant correlation. On the other hand, the remaining 68 pairs did not have any QTL sharing, but 31 of those showed significant correlation. Our joint analysis of across-environment correlations and QTL demonstrates that there is no clear one-to-one relationship between QTL sharing and correlation between environments. Thus, the information on both QTL sharing and correlation statuses is essential for plant breeders to design more efficient breeding and marker-assistant programs to deal with GxE.