Genome-Wide Association of Carbon and Nitrogen Metabolism in the Maize Nested Association Mapping Population

• Published in: Plant physiology (Bethesda) 2015-06, Vol.168 (2), p.575-583
• Main Authors: Zhang, Nengyi, Gibon, Yves, Wallace, Jason G., Lepak, Nicholas, Li, Pinghua, Dedow, Lauren, Chen, Charles, So, Yoon-Sup, Kremling, Karl, Bradbury, Peter J., Brutnell, Thomas, Stitt, Mark, Buckler, Edward S.
• Format: Article
• Language: English
• Subjects: Calcium metabolism; Carbon - metabolism; Carbonic Anhydrases - metabolism; Cellular metabolism; Chloroplasts; Chromosome Mapping - methods; Cluster Analysis; Crops, Agricultural - growth & development; Families; Gene Expression Regulation, Plant; GENES, DEVELOPMENT, AND EVOLUTION; Genetic Linkage; Genome-Wide Association Study; Life Sciences; Metabolome - genetics; Nitrogen - metabolism; Oxygen metabolism; Polymorphism, Single Nucleotide - genetics; Principal Component Analysis; Protein precursors; Proteins; Quantitative Trait Loci - genetics; Steroid metabolism; Symbolic learning; Transcription factors; Vegetal Biology; Zea mays - enzymology; Zea mays - genetics; Zea mays - metabolism
• ISSN: 0032-0889; 1532-2548
• DOI: 10.1104/pp.15.00025

Carbon (C) and nitrogen (N) metabolismare critical to plant growth and development and are at the basis of crop yield and adaptation. We performed high-throughput metabolite analyses on over 12,000 samples from the nested association mapping population to identify genetic variation in C and N metabolism in maize (Zea maysssp.mays). All samples were grown in the same field and used to identify natural variation controlling the levels of 12 key C and N metabolites, namely chlorophylla, chlorophyllb, fructose, fumarate, glucose, glutamate, malate, nitrate, starch, sucrose, total amino acids, and total protein, along with the first two principal components derived from them. Our genome-wide association results frequently identified hits with single-gene resolution. In addition to expected genes such as invertases, natural variation was identified in key C₄ metabolism genes, including carbonic anhydrases and a malate transporter. Unlike several 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 for the dissection of key metabolic pathways, providing avenues for future genetic improvement.