P0847
Genetic Analysis of the Effect of Circadian Clock Genes on Yield Components in Wheat (T. aestivum)

Lukas M. Wittern , Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom
Keith A. Gardner , The John Bingham Laboratory, NIAB, Cambridge, United Kingdom
Matthew A. Hannah , Bayer CropScience NV., Gent, Belgium
Alex A.R. Webb , Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom
Andy Greenland , The John Bingham Laboratory, NIAB, Cambridge, United Kingdom
The circadian clock serves to coordinate physiology and behaviour in a wide range of organisms with its daily cycles derived from the rotation of the earth (McClung, 2013). In plants, circadian rhythms contribute to growth and yield and, hence to productivity (Dodd et al., 2005). We are investigating the effect of the wheat orthologues of A. thaliana core circadian clock genes on yield potential and contributing agronomic traits in wheat, providing an assessment of the viability of circadian tools for agronomic improvement.

To identify circadian clock homologues protein sequence databases were queried using an orthology prediction algorithm (Altenhoff et al., 2013). This analysis suggests that on an orthology basis the circadian clock is strongly conserved between monocots and dicots. Functional analysis suggests divergence in expression patterns.

We have previously reported the creation of the first high density linkage map in an eight parent winter wheat Multi-Parent-Advanced-Inter-Cross (MAGIC) population (Gardner et al., 2015). This genetic map was used to associate circadian clock genes with phenotypes in the NIAB (National Institute of Agricultural Botany) MAGIC population and identify several candidate genes.

Delayed chlorophyll fluorescence (DF) has been shown to oscillate with a circadian rhythm (Gould et al., 2009). We have optimized a high throughput assay for delayed chlorophyll fluorescence, which allows us to identify circadian phenotypes, such as circadian clock period, amplitude and phase in wheat. Together with high throughput qRT-PCR this has allowed us to characterise circadian oscillations in a highly diverse population.