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

Sequencing Driven Accelerated Discovery of Genes Regulating Water Use Efficiency and Stomatal Patterning and in C4 Crops with High-Throughput Phenotyping

Authors:

Hui Jiang1* (hjiang@danforthcenter.org), Greg Ziegler1, Grace Tan2, Collin Luebbert1, Andrew B. Leakey2, Ivan Baxter1

Institutions:

1Donald Danforth Plant Science Center; 2Departments of Plant Biology and Crop Sciences, Institute for Genomic Biology, University of Illinois at Urbana-Champaign

Goals

Bioenergy feedstocks need to be deployed on marginal soils with minimal inputs to be economically viable and have a low environmental impact. Currently, crop water supply is a key limitation to production. The yields of C4 bioenergy crops such as Sorghum bicolor have increased through breeding and improved agronomy. Still, the amount of biomass produced for a given amount of water use (water use efficiency, or WUE) remains unchanged. Therefore, the project aims to develop novel technologies and methodologies to redesign the bioenergy feedstock sorghum for optimal WUE. Within this broader context, this subproject is using Setaria viridis as a rapid cycling model for gene discovery. The goal is to devise novel methods and develop resources to create genetic variations and streamline the phenotyping of WUE traits. These advancements are crucial for their application in forward genetics approaches aimed at identifying genes that regulate stomatal patterning and water use efficiency.

Abstract

Stomata regulate the exchange of carbon dioxide (CO2) and water vapor between the leaf and atmosphere, and therefore play a key role in determining WUE. Relatively little is known about the genes that regulate stomatal patterning and WUE in C4 grasses. To advance efforts to engineer improved WUE of bioenergy crops, researchers are developing novel methods to accelerate the use of forward genetics for gene discovery. The team conducted a forward genetic screen of 340 families of a NMU-mutagenized Setaria population, of which 185 lines were selected for having interesting visual phenotypes in a pre-screen. Researchers assessed whole-plant WUE by imaging and automated lysimeters and then collected leaf sections to screen for abnormalities in stomatal patterning. The high throughput optical tomography imaging was utilized to generate high resolution images of the leaf surface. Researchers utilize a machine learning model for identifying the size, shape, and number of stomata in Setaria. Seventy families of the first 155 families were identified to segregate for WUE and/or stomata mutant phenotypes and therefore selected for a second screen. Seeds harvested from 40 families were confirmed as fixed WUE and/or Stomata mutants. These families are part of a larger population which are being sequenced by DOE Joint Genome Institute (JGI) to create a sequence indexed mutant population. DNA isolated from representatives of each family, or the mutant segregants from a family, is being sequenced by JGI to identify disruptive SNPs in candidate genes. Preliminary analysis suggests that each line contains an average of 266 disruptive polymorphisms, with ~15 classified as high impact. The work demonstrates high-throughput phenotyping and genotyping strategies to quickly identify genes of interest, followed by verification of genes through transgenic approach for a role in water-use efficiency. Success in this effort could be leveraged to accelerate research on a wide range of other traits and species.

Funding Information

This research was supported by the DOE Office of Science, BER Program, grant no. DE-SC0023160 and DE-SC0018277.