Genetic mapping of dynamic control of leaf angle across multiple canopy levels in maize

Authors: DZIEVIT, MATTHEW - Iowa State University; Li, Xianran; YU, JIANMING - Iowa State University

Submitted to: The Plant Genome
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/17/2023
Publication Date: 12/20/2023
Citation: Dzievit, M., Li, X., Yu, J. 2023. Genetic mapping of dynamic control of leaf angle across multiple canopy levels in maize. The Plant Genome. 17(1). Article e20423. https://doi.org/10.1002/tpg2.20423.
DOI: https://doi.org/10.1002/tpg2.20423

Interpretive Summary: This research studied plants to understand the angle difference of leaves in different parts of the plant. They found specific genomic regions control leaf angle dynamics and can help breeders develop plants that can grow more efficiently and produce more yield, especially when planted at higher densities. This research could help improve the production of maize crops and ultimately benefit farmers and consumers.

Technical Abstract: Optimizing leaf angle and other canopy architecture traits has helped modern maize (Zea mays L.) become adapted to higher planting densities over the last 60 years. Traditional investigations into leaf angle’s genetic control have focused on one leaf or the average of multiple leaves; as a result, our understanding of leaf angle’s genetic control across multiple canopy levels is still limited. To address this, genetic mapping across four canopy levels was conducted in the present study to investigate the genetic control of leaf angle across the canopy. We developed two populations of doubled haploid lines derived from three inbreds with distinct leaf angle phenotypes. These populations were genotyped with genotyping-by-sequencing and phenotyped for leaf angle in four different canopy levels over multiple years. To understand how leaf angle changes across the canopy, the four measurements were used to derive three additional measurements to capture the pattern across the canopy. Composite interval mapping was conducted with the leaf-specific measurements and the derived traits. A set of 59 quantitative trait loci (QTL) were uncovered across all seven traits, and two genomic regions were consistently detected across multiple canopy levels. Additionally, seven genomic regions were found to contain consistent QTL with either relatively stable or dynamic effects at different positions within the canopy. Prioritizing selection of QTL with dynamic effects across the canopy will aid breeders in selecting maize varieties with the ideal canopy architecture that continues maximizing yield on a per area basis under increasing planting densities.