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Abstract Maize (Zea mays) production systems are heavily reliant on the provision of managed inputs such as fertilizers to maximize growth and yield. Hence, the effective use of nitrogen (N) fertilizer is crucial to minimize the associated financial and environmental costs, as well as maximize yield. However, how to effectively utilize N inputs for increased grain yields remains a substantial challenge for maize growers that requires a deeper understanding of the underlying physiological responses to N fertilizer application. We report a multiscale investigation of five field-grown maize hybrids under low or high N supplementation regimes that includes the quantification of phenolic and prenyl-lipid compounds, cellular ultrastructural features, and gene expression traits at three developmental stages of growth. Our results reveal that maize perceives the lack of supplemented N as a stress and, when provided with additional N, will prolong vegetative growth. However, the manifestation of the stress and responses to N supplementation are highly hybrid-specific. Eight genes were differentially expressed in leaves in response to N supplementation in all tested hybrids and at all developmental stages. These genes represent potential biomarkers of N status and include two isoforms of Thiamine Thiazole Synthase involved in vitamin B1 biosynthesis. Our results uncover a detailed view of the physiological responses of maize hybrids to N supplementation in field conditions that provides insight into the interactions between management practices and the genetic diversity within maize. 

Abstract Classical genetic studies have identified many cases of pleiotropy where mutations in individual genes alter many different phenotypes. Quantitative genetic studies of natural genetic variants frequently examine one or a few traits, limiting their potential to identify pleiotropic effects of natural genetic variants. Widely adopted community association panels have been employed by plant genetics communities to study the genetic basis of naturally occurring phenotypic variation in a wide range of traits. High-density genetic marker data—18M markers—from 2 partially overlapping maize association panels comprising 1,014 unique genotypes grown in field trials across at least 7 US states and scored for 162 distinct trait data sets enabled the identification of of 2,154 suggestive marker-trait associations and 697 confident associations in the maize genome using a resampling-based genome-wide association strategy. The precision of individual marker-trait associations was estimated to be 3 genes based on a reference set of genes with known phenotypes. Examples were observed of both genetic loci associated with variation in diverse traits (e.g., above-ground and below-ground traits), as well as individual loci associated with the same or similar traits across diverse environments. Many significant signals are located near genes whose functions were previously entirely unknown or estimated purely via functional data on homologs. This study demonstrates the potential of mining community association panel data using new higher-density genetic marker sets combined with resampling-based genome-wide association tests to develop testable hypotheses about gene functions, identify potential pleiotropic effects of natural genetic variants, and study genotype-by-environment interaction.