Genomic Science Program
U.S. Department of Energy | Office of Science | Biological and Environmental Research Program

2023 Abstracts

Harnessing Regulatory Variation to Elucidate Drought Resilience Mechanisms in Sorghum


Yuguo Xiao1, Indrajit Kumar1, Maxwell Braud1, Philip Ozersky1, Emmanuel Miguel Gonzalez2, Rajdeep S. Khangura3, Brian Dilkes3, Duke Pauli2, Todd C. Mockler1, and Andrea L. Eveland1([email protected])


1Donald Danforth Plant Science Center; 2University of Arizona; and 3Purdue University


  • Overall project objective: To define and functionally characterize genes and pathways related to drought stress tolerance in sorghum and the molecular mechanisms by which these factors drive phenotypic diversity.
  • Establish a foundation for deep explorations of gene regulatory networks in sorghum through integrative genomics analyses.
  • Enhance understanding of how genotype drives phenotype and environmental adaptation using high-resolution, field-based phenotyping of sorghum mutant collections and a novel diversity panel.
  • Map and characterize genes contributing to drought responsive phenotypes in sorghum.
  • Experimentally validate predictions of gene function using molecular and genetic assays and targeted gene editing.


Development of the next generation of bioenergy feedstocks will require strategies that utilize resource-limited agricultural lands, including the introduction of novel traits into crops to increase abiotic stress tolerance. This project investigates the innate drought resilience of sorghum (Sorghum bicolor), a bioenergy feedstock and cereal crop. Drought is a complex trait and identifying the genes underlying sorghum’s innate drought tolerance and how they are regulated in the broader context of the whole plant and its environment requires advanced approaches in genetics, genomics, and phenotyping.

This project leverages a field-based phenotyping infrastructure at Maricopa, Ariz., which provides an exceptional capability for managed stress trials in a hot and arid environment through controlled irrigation. An automated field scanner system collects high-resolution phenotyping data using a variety of sensors throughout the growing season, from seedling establishment to harvest. A sorghum mutant population was phenotyped under the field scanner to compare drought-stressed and well-watered plants. Each mutant’s genome has been sequenced so that sequence variants can be linked with phenotypes. Being able to assess the genotype-to-phenotype link in response to drought over the life cycle of the plant will facilitate discovery of genes and their functions. The team has also constructed a diverse panel of sorghum lines, which maximizes variation in water-use efficiencies as well as genetics and geographic origin. Each of these lines have also been sequenced through various efforts. This population was phenotyped in a controlled environment drought response experiment where samples were collected for population-level expression analyses and will subsequently be field-phenotyped under the field scanner this summer. State-of-the-art phenotyping data analytics pipelines have been developed as part of this project and DOE-funded initiatives (see poster by Gonzalez et al.) and are being extended to define stress-related phenotypes at multiple scales. Bulked segregant analysis-seq is used to accelerate mapping of causal loci that underlie mutants of interest. So far, researchers have identified candidate genes underlying defects in leaf senescence, plant architecture, and male fertility. Regulatory maps generated from diverse sorghum lines in response to stress are being used to nominate gene candidates and place them in the larger context of a drought response network. In addition, gene editing and transgenic methods are being used to characterize gene function.

This work will identify control points for enhancing the productivity of bioenergy crops in marginal environments through precision breeding or engineering, and thus accelerate the development of improved varieties that are high yielding with limited water resources.

Funding Information

This work is funded by DOE BER awards #DE-SC0023305 and #DE-SC0020401.