Combined Large-Scale Phenotyping and Transcriptomics in Maize Reveals a Robust Growth Regulatory Network

Area of Science:

• Plant Biology
• Genetics
• Molecular Biology

Background:

• Leaves are essential for plant biomass and seed production, directly impacting food security and renewable energy.
• Understanding the molecular mechanisms of leaf development is critical for enhancing crop productivity.

Purpose of the Study:

• To identify genes associated with diverse leaf traits in maize (Zea mays) using integrated genetic approaches.
• To uncover the molecular networks regulating leaf growth and development for potential biomass improvement.

Main Methods:

• Transcriptome profiling of maize leaf tissues from two diverse mapping populations.
• In-depth phenotyping of leaf traits across recombinant inbred lines.
• Integration of transcriptomic and phenotypic data with functional genomics data.

Main Results:

• Identified 226 genes robustly associated with various leaf traits by combining data from biparental and multiparent advanced generation intercross populations.
• The candidate gene set is enriched in transcriptional regulators, protein synthesis, and cell wall metabolism genes.
• Discovered a growth regulatory network of 185 genes by integrating with public functional genomics data.

Conclusions:

• Combining in-depth phenotyping with transcriptomics in mapping populations is a powerful strategy to dissect complex trait genetic control.
• The identified gene set and regulatory network provide valuable targets for maize biomass improvement and sustainable agriculture.