Co-optimisation of axial root phenotypes for nitrogen and phosphorus acquisition in common bean

Harini Rangarajan, Johannes A. Postma & Jonathan P. Lynch

Background and Aims Root architecture is a primary determinant of soil resource acquisition. We hypothesized that root architectural phenes will display both positive and negative interactions with each other for soil resource capture because of competition for internal resources and functional tradeoffs in soil exploration.

Methods We employed the functional-structural plant model SimRoot to explore how interactions among architectural phenes in common bean determine the acquisition of phosphate and nitrate, two key soil resources contrasting in mobility. We evaluated the utility of basal root whorl number (BRWN) when basal root growth angle (BRGA), hypocotyl-borne roots (HBR), and lateral root branching density (LRBD) were varied, under varying availability of phosphate and nitrate.

Key Results Three basal root whorls were optimal in most phenotypes. This optimum shifted towards greater values when LRBD decreased and to smaller numbers when LRBD increased. The maximum biomass accumulated for a given BRWN phenotype in a given limiting nutrient scenario depended upon root growth angle. Under phosphorus stress, shallow phenotypes grew best, whereas under nitrate stress, fanned phenotypes grew best. The effect of increased HBR depended upon BRWN as well as the limiting nutrient. Greater production of axial roots due to BRWN or HBR reduced rooting depth, leading to reduced biomass under nitrate-limiting conditions. Increased BRWN as well as greater LRBD increased root carbon consumption, resulting in reduced shoot biomass.

Conclusions We conclude that the utility of a root architectural phenotype is determined by whether the constituent phenes are synergistic or antagonistic. Competition for internal resources and tradeoffs for external resources result in multiple phenotypes being optimal under a given nutrient regime. We also find that no single phenotype is optimal across contrasting environments. These results have implications for understanding plant evolution and also for the breeding of more stress-tolerant crop phenotypes.