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Key genes for corn architecture revealed, identifying future breeding targets

The physical structure of corn plants—including the angle of leaves bending from the stem and the number of pollen-laden tassel branches—makes a big difference for yield. Compact plants can be planted closer together, adding up to more ears per acre. But compact corn didn't happen by accident; years of hybrid breeding did that. Now, two new genome-based studies are making it possible to precisely adjust corn architecture to meet future demands.

The studies, published recently in and , identify genes and genomic markers that predict leaf angle and tassel branch number in corn. The research, led by scientists at the Donald Danforth Plant Science Center and the University of Illinois Urbana-Champaign, specifically focuses on factors that control pleiotropy, the phenomenon where a single gene influences multiple traits.

Pleiotropy poses a challenge for crop improvement because selecting for one beneficial trait can negatively impact another. But the researchers leveraged multiple approaches to identify variation in gene networks that control pleiotropy. Exploiting this variation means it may be possible to decouple pleiotropic traits like leaf angle and tassel branch number, offering a new approach to fine-tuning crop architecture.

"There are certain maize genes that, when perturbed, dramatically affect both leaf and tassel morphology," said Andrea Eveland, associate member at the Danforth Center and co-author on both papers. "By teasing apart how these genes are specifically regulated in early developmental programs that pattern different plant organs, we can gain flexibility in crop improvement and optimize key traits independently."

The study published in Genetics adapted an approach called genomic prediction to the task of quantifying the contributions of specific gene networks (transcription factors) with leaf angle and tassel branch number. Leveraging specific genomic information from corn, the researchers were also able to quantify the importance of similar gene networks in related species, sorghum and rice. This approach, especially when combined with high-throughput, high-resolution field phenotyping, could be game-changing for breeders.

"We essentially 'MacGyver-ed' genomic prediction to tell us about the contributions of these specific gene networks," said Alex Lipka, co-author of both studies and associate professor in the Department of Crop Sciences, part of the College of Agricultural, Consumer and Environmental Sciences at Illinois. "One of the most exciting findings was evidence that similar classes of transcription factors can accurately predict leaf angle in both maize and sorghum."

Lipka added that identifying the specific genes and transcription factors involved in key corn architecture traits could open up promising avenues for targeted breeding practices and lead to even greater productivity in the future.

The studies mark a key milestone in the collaborative research between developmental geneticists, computational biologists, and statisticians.