Literature DB >> 34197039

Genetic control of kernel compositional variation in a maize diversity panel.

Jonathan S Renk1, Amanda M Gilbert1, Travis J Hattery2, Christine H O'Connor1,3, Patrick J Monnahan1,3, Nickolas Anderson4, Amanda J Waters4, David P Eickholt4, Sherry A Flint-Garcia5, Marna D Yandeau-Nelson2, Candice N Hirsch1.   

Abstract

Maize (Zea mays L.) is a multi-purpose row crop grown worldwide, which, over time, 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 control of 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, and 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, and popcorn) were explored, and significant differences and meaningful correlations were detected. In total, 22.9-71.0% 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 72 statistically significant SNPs for 11 compositional traits. This study provides valuable insights in the phenotypic variation and genetic control underlying compositional traits that can be used in breeding programs for improving maize grain quality.
© 2021 The Authors. The Plant Genome published by Wiley Periodicals LLC on behalf of Crop Science Society of America.

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Year:  2021        PMID: 34197039     DOI: 10.1002/tpg2.20115

Source DB:  PubMed          Journal:  Plant Genome        ISSN: 1940-3372            Impact factor:   4.089


  1 in total

1.  Association mapping across a multitude of traits collected in diverse environments in maize.

Authors:  Ravi V Mural; Guangchao Sun; Marcin Grzybowski; Michael C Tross; Hongyu Jin; Christine Smith; Linsey Newton; Carson M Andorf; Margaret R Woodhouse; Addie M Thompson; Brandi Sigmon; James C Schnable
Journal:  Gigascience       Date:  2022-08-23       Impact factor: 7.658

  1 in total

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