Research Article | Open Access

Volume 2025 |Article ID 100008 | https://doi.org/10.1016/j.plaphe.2025.100008

Identification of phenotypic and transcriptomic signatures underpinning maize crown root systems

Jodi B. Callwood,¹ Craig L. Cowling,¹ Ella G. Townsend,¹ Shikha Malik,² Melissa A. Draves,³ Jasper Khor,⁴ Jackson P. Marshall,⁵ Heather Sweers,¹ Justin W. Walley,² and Dior R. Kelley ¹

¹Department of Genetics, Development, and Cell Biology, Iowa State University, Ames, IA, 50011, USA
²Department of Plant Pathology, Entomology, and Microbiology, Iowa State University, Ames, IA, 50011, USA
³Division of Plant Science and Technology, University of Missouri-Columbia, Columbia, MO, 65211, USA
⁴Department of Computer Science, Iowa State University, Ames, IA, 50011, USA
⁵Corteva Agriscience, Johnston, IA, 50131, USA

Abstract

Maize is pivotal in supporting global agriculture and addressing food security challenges. Crop root systems are critical for water uptake and nutrient acquisition, which impacts yield. Quantitative trait phenotyping is essential to understand better the genetic factors underpinning maize root growth and development. Root systems are challenging to phenotype given their below-ground, soil-bound nature. In addition, manual trait annotations of root images are tedious and can lead to inaccuracies and inconsistencies between individuals, resulting in data discrepancies. In this study, we explored juvenile root phenotyping in the presence and absence of auxin treatment, a key phytohormone in root development, using manual curation and gene expression analyses. In addition, we developed an automated phenotyping pipeline for field-grown maize crown roots by leveraging open-source software. By examining a test set of 11 diverse maize genotypes for juvenile-adult root trait correlations and gene expression patterns, an inconsistent correlation was observed, underscoring the developmental plasticity prevalent during maize root morphogenesis. Transcripts involved in hormone signaling and stress responses were among differentially expressed genes in roots from 20 diverse maize genotypes, suggesting many molecular processes may underlie the observed phenotypic variance. In particular, co-expressed gene expression networks associated with module-trait relationships included 1,3-β-glucan, which plays a crucial role in cell wall dynamics. This study furthers our understanding of genotype-phenotype relationships, which is relevant for informing agricultural strategies to improve maize root physiology.