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\begin{document}

\title{Using advanced imaging and analysis to find a gene that influences maize
Root System Architecture (RSA) and nitrogen relations}



\author[1]{Michelle Cho}%
\affil[1]{Affiliation not available}%


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  \date{May 24, 2024}


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\emph{\textbf{Michelle Cho\textsuperscript{1},} Zhengbin
Liu\textsuperscript{2}, Dhineshkumar Thirupatthi\textsuperscript{3}, Tim
Parker\textsuperscript{3}, Shayla Gunn\textsuperscript{4},}

\emph{Keith Duncan\textsuperscript{4}, Christopher
Topp\textsuperscript{4}}

\emph{\textsuperscript{1}Washington University in St. Louis, Saint
Louis, MO, USA}

\emph{\textsuperscript{2}Partek Inc, Saint Louis, MO, USA}

\emph{\textsuperscript{3} Bayer, Saint Louis, MO, USA}

\emph{\textsuperscript{4}Donald Danforth Plant Science Center, Saint
Louis, MO, USA}

\textbf{Keywords:} maize root phenomics, X-ray computed tomography,
Nitrogen metabolism, Root structure architecture, GWAS, CRISPR-Cas9
mutants

Understanding plant architecture can lead to identifying breeding
targets impacting crop yield, physiology, and efficiency. The genetics
controlling root system architecture (RSA), in particular, are not
well-understood due to the difficulty in accurately capturing and
measuring complex morphological traits. Here we use 2D and 3D imaging to
identify and verify a candidate gene underlying a maize Quantitative
Trait Locus (QTL) for altered root system architecture. The gene was
mapped in a population derived from the Illinois Long Term Protein
Selection Strains (ILTPS), which have diverged for nitrogen uptake
capacity. We extracted root traits via Digital Imaging of Root Traits
(DIRT) from hundreds of 2D images of root crowns of mature field-grown
ILTPS maize. We performed a Genome-Wide Association Study (GWAS) to
identify a QTL controlling multiple root crown traits. Only one gene was
within the local region of Linkage Disequilibrium (LD) of this QTL, and
subsequent nanopore sequencing and quantitative PCR revealed lesions in
the promoter which reduced gene expression, presumably driving the
divergent phenotypes. An analysis of 3D models generated from X-ray
Computed Tomography of root crowns verified that ILTPS lines containing
the high-versus-low expressing alleles had significantly different RSAs,
for example, in their Solidity, which suggests they explore the soil
differently. An ongoing field experiment aims to understand how these
different RSAs affect plant nitrogen uptake Additionally, we generated
CRISPR-Cas9 mutants in maize to investigate this gene's role in RSA and
nitrogen relations in maize.

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