Laperche Anne, Brancourt-Hulmel Maryse, Heumez Emmanuel, Gardet Olivier, Hanocq Eric, Devienne-Barret Florence, Le Gouis Jacques
1281 SADV (Stress abiotiques et différenciation des végétaux cultivés), Chaussée de Brunehaut, UMR INRA/USTL, Estrées-Mons, BP50136, 80203 Péronne Cedex, France.
Theor Appl Genet. 2007 Aug;115(3):399-415. doi: 10.1007/s00122-007-0575-4. Epub 2007 Jun 14.
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 x 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 x N interactions and the impact of Rht-B1, Ppd-D1 and B1, are discussed.
当前,较低的市场价格和环境问题使小麦(Triticum aestivum L.)育种计划转向低投入农业生产方式,尤其是低氮(N)投入管理。此类计划需要了解植物对氮缺乏反应的遗传决定因素。我们的目标是表征氮利用效率的遗传基础以及基因型与氮的相互作用。对从一个耐氮胁迫品种和一个氮胁迫敏感品种杂交获得的222个双单倍体系(DH)的作图群体进行了产量、籽粒蛋白质产量及其组分的QTL检测。在七种不同环境下对该群体进行了试验,每种环境下均设置高氮(N(+))和低氮(N(-))供应。总共检测到233个QTL,涉及在每种环境和氮供应组合下测量的性状、“全局”相互作用变量(N(+)-N(-)和N(-)/N(+))、对氮胁迫的敏感性以及使用因子回归参数评估的氮限制条件下的表现。这233个QTL在整个基因组上被检测到,并聚类成82个基因组区域。矮秆基因(Rht-B1)、光周期敏感基因(Ppd-D1)和芒抑制基因(B1)与包含QTL数量最多的区域重合。在连锁群3D、4B、5A1和7B2上检测到非互作QTL。互作QTL通过互作或因子回归变量(2D2、3D、5A1、5D、6A、6B、7B2)或两者(1B、2A1、2A2、2D1、4B、5A2、5B)揭示。讨论了QTL元分析和因子回归在研究QTL与氮相互作用以及Rht-B1、Ppd-D1和B1影响方面的实用性。