Genome-Wide Association Study Reveals Influence of Cell-specific Gene Networks on Soybean Root System Architecture

Abstract

AbstractRoot system architecture (RSA) describes the shape and arrangement of a plant’s roots in the soil including the angle, rate of growth, and type of individual roots, which facilitates the uptake of nutrients and water. In crop improvement efforts, RSA has been less well studied due to the technical challenges associated with phenotyping roots as well as a focus on above-ground traits such as yield. We developed a gel-based root phenotyping system calledRADICYL(Root Architecture 3D Cylinder), which is a non-invasive, high-throughput approach that enabled us to measure 15 RSA traits. We leveragedRADICYLto perform a comprehensive genome-wide association study (GWAS) with a panel of 371 diverse soybean elite lines, cultivars, landraces, and closely related species to identify gene networks underlying RSA. We identified 54 significant single nucleotide polymorphisms (SNPs) in our GWAS, some of which were shared across multiple RSA traits while others were specific to a given trait. We generated a single cell atlas of the soybean root using single nuclei RNA sequencing (snRNAseq) to explore the associated genes in the context of root tissues. Using gene co-expression network (GCN) analyses applied to RNA-seq of soybean root tissues, we identified network-level associations of genes predominantly expressed in endodermis with root width, and of those expressed in metaphloem with lateral root length. Our results suggest that pathways active in the endodermis and metaphloem cell-types influence soybean root system architecture.