QTL mapping of nitrogen use efficiency and its components in rice

The excessive use of nitrogen (N) fertilizers has turned into a major environmental and economical concern today. Rice cultivation is particularly prone to N losses. The knowledge of the genetic determinism of agronomical nitrogen use efficiency (aNUE) and its two components - absorption (aNUE) and physiological (pNUE) nitrogen use efficiency - in rice is lacking and might be useful for breeding purposes towards the development of sustainable agriculture. In this study, the genetic determinism of NUE and related traits were investigated in rice through physiological and genetic approaches. The analysis of components of NUE and related traits in different rice cultivars in hydroponics demonstrated that agNUE depended more on aNUE than on pNUE. The sensitivity to the N supply depended on the rice cultivar. The genetic analysis was made on 174 F9-10 recombinant inbred lines (RILs) derived from the cross IR64/Azucena. Hydroponic experiments at the vegetative stage allowed the detection of 14 QTLs for NUE components and 63 for 12 agronomical and physiological traits. The aNUE was shown to be the most important component of agNUE in this RIL population. Six hotspots containing several QTLs for NUE or at least one for NUE and one for another trait were identified. Furthermore, 8 QTLs for aNUE or agNUE and 7 for other traits were found in several experiments repeatedly. Pot and field experiments allowed to identify 87 QTLs for NUE components and 371 for other traits in the same RIL population. Once again, aNUE was shown to be the most important component of agNUE. Fifty four hotspots were identified, and 9 QTLs for NUE components and 3 for other traits were found in several experiments repeatedly. In conclusion, the present study allowed to identify reliable regions involved in NUE components and related parameters in rice. These regions will be the target of further fine mapping and candidate gene studies towards the development of rice cultivars for sustainable agriculture.