Broad environmental adaptation is associated with root anatomical phenotypes in maize landraces: an in silico study

Root phenotypes contribute to environmental adaptation. We hypothesized that root phenotypes of maize (Zea mays L. ssp. mays) landraces reflect their adaptation to edaphic limitations in their native soil environments, and that some root phenotypes may confer broad edaphic adaptation.

We phenotyped the roots of maize landraces and used the functional-structural plant/soil model OpenSimRoot_v2 to simulate landraces and their native environments to analyse how root phene states interact with each other and with environment variables to regulate edaphic adaptation.

Landraces from low phosphorus regions have root phenotypes with shallow growth angles and greater nodal root numbers, allowing them to adapt to their native environments by improved topsoil foraging. We used machine learning algorithms to detect the most important phenotypes responsible for adaptation to multiple environments. The most important phene states responsible for stability across environments are large cortical cell size and reduced diameter of roots in nodes 5 and 6. When we dissected the components of root diameter, we observed that large cortical cell size improved growth by 28, 23 and 114 %, while reduced cortical cell file number alone improved shoot growth by 137, 66 and 216 %, under drought, nitrogen and phosphorus stress, respectively. Functional-structural analysis of 96 maize landraces from the Americas, previously phenotyped in mesocosms in the glasshouse, suggested that parsimonious anatomical phenotypes, which reduce the metabolic cost of soil exploration, were the main phenotypes associated with adaptation to multiple environments, while root architectural phenotypes were related to adaptation to specific environments.

These results indicate that integrated root phenotypes with anatomical phene states that reduce the metabolic cost of soil exploration increase tolerance to edaphic stress across multiple environments and therefore would improve yield stability, regardless of their root architecture.