Exploiting maize genetic diversity: Metabolomic, enzyme activity profiling, and metabolic modelling to link leaf physiology to kernel yield ($)
The path from genome to phenome is difficult to predict. Cañas et al. tried to identify biochemical markers that are correlated with kernel yield that could be selected for in breeding. Specifically, they collected data from metabolomics, enzyme activity assays and metabolic modeling, taken during the vegetative phase and the grain filling state 15 days after silking (15 DAS), from 19 maize lines. Interestingly, in this sample pool representing broad genetic distance, they observed “only a slight relationship between the genetic distance of the 19 lines and their enzyme activities 15 DAS”. A strong correlation between grain yield and kernel C and N was observed, and higher levels of enzymes involved in C4 photosynthesis and nitrogen assimilation into amino acids during vegetative growth was also a positive indicator of yield. Plant Cell 10.1105/tpc.16.00613
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