Using genotype × nitrogen interaction variables to evaluate the QTL involved in wheat tolerance to nitrogen constraints

TL;DR: The aim was to characterize the genetic basis of N use efficiency and genotype ×-N interactions, and the usefulness of QTL meta-analysis and factorial regression to study QTL × N interactions.

Abstract: Lower market prices and environmental concerns now orientate wheat (Triticum aestivum L.) breeding programs towards low input agricultural practices, and more particularly low nitrogen (N) input management. Such programs require knowledge of the genetic determination of plant reaction to N deficiency. Our aim was to characterize the genetic basis of N use efficiency and genotype × N interactions. The detection of QTL for grain yield, grain protein yield and their components was performed on a mapping population of 222 doubled haploid lines (DH), obtained from the cross between an N stress tolerant variety and an N stress sensitive variety. Experiments on the population were carried out in seven different environments, and in each case under high (N+) and low (N−) N supplies. In total, 233 QTL were detected for traits measured in each combination of environment and N supply, for “global” interaction variables (N+–N− and N−/N+), for sensitivity to N stress and for performance under N-limited conditions which were assessed using factorial regression parameters. The 233 QTL were detected on the whole genome and clustered into 82 genome regions. The dwarfing gene (Rht-B1), the photoperiod sensitivity gene (Ppd-D1) and the awns inhibitor gene (B1) coincided with regions that contained the highest numbers of QTL. Non-interactive QTL were detected on linkage groups 3D, 4B, 5A1 and 7B2. Interactive QTL were revealed by interaction or factorial regression variables (2D2, 3D, 5A1, 5D, 6A, 6B, 7B2) or by both variables (1B, 2A1, 2A2, 2D1, 4B, 5A2, 5B). The usefulness of QTL meta-analysis and factorial regression to study QTL × N interactions and the impact of Rht-B1, Ppd-D1 and B1, are discussed.