ISRR 2018

Genetic Architecture of Shoot-Borne Roots Development in Maize

Lixing Yuan
Department of Plant Nutrition, China Agricultural University, China

Given the important function of roots for anchorage and resource acquisition from soils, the root system architecture is fundamental for crop growth and productivity. In most of cereal crops, the post-embryonic shoot-borne roots dominate the whole root system that is consist of crown roots (CR) from belowground nodes and brace roots (BR) from aboveground nodes, representing the major components for water and nutrient uptake. However, the gene regulatory networks and substantial natural variations controlling these type of roots traits are largely unknown. Here, we used cereal model species maize (Zea may L.) to determine the genetic architecture of shoot-borne roots development under field condition through genome-wide association analyses (GWAS). Field trials growing maize association population (513 lines) were performed across eight environments, and a modified Shovelomics method was used to determine fourteen shoot-borne roots traits (i.e. number, angle, diameter, etc.) at later developmental stage. The tropical/subtropical lines showed steeper and thicker CR than the temperate lines, suggesting their preferential distribution of roots in deep soil. By GWAS a total of 389 genetic loci was identified to be associated with investigated root traits, and explanined about 32-65% of total phenotypic variation. Within the genetic loci a set of priori candidate genes for shoot-borne root traits was predicated and mostly involved in the transport and metabolism of various phytohormones, in particular a gene network pathway for auxin TIR1/ABF2–AUX/IAA-ARF–LBD. Taken together, this work indicated the existence of large natural variation in maize shoot-borne roots which were controlled by numerous small-effects genetic loci. The identifed SNPs and associated priori genes underlying shoot-borne roots development further provide a rich resource for breeding maize cultivars with the optimal root system architecture for sustainable agricultural production.









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