|ZHANG, NENGYI - Cornell University|
|GIBON, YVES - Max Planck Society|
|PINGHUA, LI - Boyce Thompson Institute|
|DEDOW, LAUREN - Boyce Thompson Institute|
|CHEN, CHARLES - Cornell University|
|SO, YOON-SUP - North Carolina State University|
|BRUTNELL, THOMAS - Boyce Thompson Institute|
|SITT, MARK - Max Planck Society|
|Buckler, Edward - Ed|
|WALLACE, JASON - Cornell University|
|KREMLING, KARL - Cornell University|
Submitted to: Plant Physiology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/25/2015
Publication Date: 4/27/2015
Citation: Zhang, N., Gibon, Y., Lepak, N.K., Pinghua, L., Dedow, L., Chen, C., So, Y., Brutnell, T., Sitt, M., Buckler Iv, E.S., Wallace, J.G., Kremling, K., Bradbury, P. 2015. Genome-wide association study of carbon and nitrogen metabolism in the maize nested association mapping population. Plant Physiology. doi: 10.1104/pp.15.0025.
Interpretive Summary: Carbon and nitrogen metabolism are critical to plant growth and development and are at the basis of yield and adaptation for all crops. This study is one of the largest ever to look at how corn genetics affects central metabolism. Through a combination of latest technologies to profile the genome and metabolites, we discovered several of key genes determining the balance of carbon and nitrogen in field grown corn plants. These key genes are likely important for adapting corn to numerous environments, and it provides a powerful model on how to relate genetics and central metabolism.
Technical Abstract: Carbon (C) and nitrogen (N) metabolism are critical to plant growth and development and at the basis of yield and adaptation. We have applied high throughput metabolite analyses to over 12,000 diverse field grown samples from the maize nested association mapping population. This allowed us to identify natural variation controlling the levels of twelve key C and N metabolites, often with single gene resolution. In addition to expected genes like invertases, critical natural variation was identified in key C4 metabolism genes like carbonic anhydrases and a malate transporter. Unlike prior maize studies, extensive pleiotropy was found for C and N metabolites. This integration of field-derived metabolite data with powerful mapping and genomics resources allows dissection of key metabolic pathways, providing avenues for future genetic improvement.