PT  - JOURNAL ARTICLE
AU  - Jonathan S. Renk
AU  - Amanda M. Gilbert
AU  - Travis J. Hattery
AU  - Christine H. O’Connor
AU  - Patrick J. Monnahan
AU  - Nickolas Anderson
AU  - Amanda J. Waters
AU  - David P. Eickholt
AU  - Sherry A. Flint-Garcia
AU  - Marna D. Yandeau-Nelson
AU  - Candice N. Hirsch
TI  - Genetic Architecture of Kernel Compositional Variation in a Maize Diversity Panel
AID  - 10.1101/2021.03.29.436703
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.03.29.436703
4099  - http://biorxiv.org/content/early/2021/03/30/2021.03.29.436703.short
4100  - http://biorxiv.org/content/early/2021/03/30/2021.03.29.436703.full
AB  - Maize (Zea mays L.) is a multi-purpose row crop grown worldwide, which overtime has often been bred for increased yield at the detriment of lower composition grain quality. Some knowledge of the genetic factors that affect quality traits has been discovered through the study of classical maize mutants. However, much of the underlying genetic architecture controlling these traits and the interaction between these traits remains unknown. To better understand variation that exists for grain compositional traits in maize, we evaluated 501 diverse temperate maize inbred lines in five unique environments and predicted 16 compositional traits (e.g. carbohydrates, protein, starch) based on the output of near-infrared (NIR) spectroscopy. Phenotypic analysis found substantial variation for compositional traits and the majority of variation was explained by genetic and environmental factors. Correlations and trade-offs among traits in different maize types (e.g. dent, sweetcorn, popcorn) were explored and significant differences and correlations were detected. In total, 22.9-71.1% of the phenotypic variation across these traits could be explained using 2,386,666 single nucleotide polymorphism (SNP) markers generated from whole genome resequencing data. A genome-wide association study (GWAS) was conducted using these same markers and found 70 statistically significant loci for 12 compositional traits. This study provides valuable insights in the phenotypic variation and genetic architecture underlying compositional traits that can be used in breeding programs for improving maize grain quality.Core IdeasUnderstanding kernel compositional variation is important for food grade corn improvement.Genetic and environmental factors account for most of the variation in compositional traits.A broad range in trait heritabilities was observed across compositional traits.Compositional trade-offs will be important to consider when conducting multitrait breeding.Compositional traits are mostly controlled by a large number of small effect loci.Competing Interest StatementNA, AJW, and DE are employed by PepsiCo, Inc., a goods and beverage company that sources food grade corn. The views expressed in this manuscript are those of the authors and do not necessarily reflect the position or policy of PepsiCo, Inc.