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Identification of traits and genetic markers to reduce the nitrogen requirement and improve the grain protein concentration of winter wheat

Lead Research Organisation: John Innes Centre
Department Name: UNLISTED

Abstract

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

Technical Summary

This project is a cooperation between BBSRC and INRA scientists and focuses on the biological question of what traits and genes are responsible for the ability of certain wheat lines to (1) produce more yield for each kg of fertiliser N applied and (2) demonstrate higher and more stable grain protein percentage than others. The programme will attempt to identify genetic markers in winter wheat backgrounds that breeders can use as selection criteria. For this purpose, altering the partitioning of N between plant organs (leaf lamina, leaf sheath, true stem and ear) could be easier and more useful than altering single metabolic processes such as photosynthesis. Physiologists, geneticists, modellers and breeders will collaborate to characterise and integrate NUE traits into elite wheat germplasm. Two suitable DH populations will be studied: (1) a UK Savannah x Rialto population representing available genetic variation in NUE and (2) a French half diallel population representing available genetic variation for extremes of positive or negative departures from the grain yield to protein percentage relationship. Specific objectives are to: (1) identify traits associated with lower fertiliser N requirement and increased grain protein percentage and (2) identify QTL associated with these traits; (3) identify lines in wheat mutant populations for NUE traits to investigate their inheritance and also characterise them at the molecular level for candidate genes to identify further allelic diversity. Finally, (4) predict the environmental stability of QTL by developing a QTL-based model to link genotype-specific parameters describing N distribution within the plant organs with genetic analysis.

Planned Impact

unavailable

Publications

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