Plasticity genes for improving nitrogen and water use efficiency in maize

Overview

This research program identifies maize genes that drive favorable phenotype plasticity, enabling higher and more stable yields across diverse environments. By analyzing transgene performance across multiple growing conditions, the program targets improvements in nitrogen use efficiency (NUE) and water use efficiency (WUE), two critical traits for sustainable maize production. The work addresses a key challenge in modern agriculture: developing varieties that maintain productivity under variable environmental stresses, including nutrient limitations and water availability. The approach combines large-scale phenotypic and environmental data analysis with field validation to discover genes that regulate yield stability as well as yield potential.

Technical specifications

Approach and methodology:

• Phenotype plasticity analysis applied to 1,400 transgenes evaluated across different environments to link genetic variation with yield and yield stability
• GEE biplot method (Genotype effect and genotype-by-environment interaction biplot) used to evaluate yield performance and stability of hybrid materials
• Field validation planned across major maize production areas of China, recording detailed yield traits over a one-year study period
• Transcriptome integration envisioned to explore transcriptional regulatory networks associated with identified plasticity genes

Initial validated candidates:

• Transgenic materials 00145, 03311, and 91022 demonstrated higher yield and better stability than wild type
• Associated genes identified include CAUB1177, CAUB1328, and CAUC0099

Data assets:

• Phenotype and environmental datasets for 1,400 transgenes across multiple environments, collected and analyzed by the research lab

Technology readiness level

The program is at an early-to-mid stage of gene discovery and validation. Initial screening using the GEE biplot method has already identified promising transgene materials and candidate genes with favorable yield and stability effects. The next phase involves systematic evaluation of all 1,400 genes, followed by multi-location field trials in China's principal maize-growing regions. The team is actively seeking industry partners to provide additional data, such as transcriptome datasets, and to contribute industry expertise that supports downstream validation and exploration of the transcriptional regulatory networks underlying the identified genes.