Switchgrass responses to future climate change
 

The effects of climate change during the next 50-100 yrs will largely determine shifts in habitat type and quality, as well as the potential to use habitats for biofuel production. Although decreasing precipitation is expected to reduce plant productivity, the severity of impact will depend on the magnitude and frequency of altered rainfall, physiological tolerance envelopes of species, as well as the ability of switchgrass to acclimate or adapt. As such, a major goal of climate change ecology is to determine responses of target plant species under realistic field conditions. Here, we will use sophisticated field rainout shelters and realistic planting densities to explore switchgrass responses to predicted climate. To understand gene expression responses to drought we will implement RNA-sequencing on various switchgrass varieties under different drought regimes. Further, collaborations with multiple USDA field stations will allow for studying switchgrass response across many ecological regions. Geographic data will be integrated with previously developed yield models to predict switchgrass response across the landscape.

The primary goals of this project will be to 1) Estimate the environmental and genetic variability for drought-related traits, overall physiology, and performance among diverse Panium virgatum varieties grown under future climate environments; 2) Identify drought-tolerant P. virgatum varieties for further study and potential biofuel use; 3) Expand our understanding of switchgrass physiology x environment interactions as well as the degree of geographical genotype x environment interactions through collaborative field trails; 4) Predict switchgrass productivity with future climate change using the genomic, physiological, and ecological data from this work to parameterize simulation models; 5) Determine gene expression response to drought across ecotypes.
 

Project 1: DISCOVERING PLANT DRIVERS OF ADAPTATION AND SUSTAINABILITY

Our latitudinal garden experiments represent a highly valuable shared resource that has facilitated numerous multi-disciplinary studies both at particular field locations and across the geographic range of the plantings. We have maintained ~ 800 upland/lowland cross progeny and ~ 800 natural accessions from the GWAS panel as potted material. We will continue to propagate this material with support from the LBJ Wildflower Center (WFC) in Austin TX and D. Lowry at KBS MI. We will use these divisions to rebalance and reinvigorate our plantings, to protect field material against loss and contamination, and to establish new experiments in support of ongoing work. In particular, we will focus future plantings to represent zones of adaptation by parsing material into genetic diversity groups planted at regional scales with new replicated plantings at our core sites in Austin TX, Columbia MO, and KBS MI.

Goals:

• Continue common garden studies to discover traits and genes underlying adaptation and sustainability.

•  Identify the genetic drivers of seed dormancy, seedling recruitment, and establishment ability across broad environmental gradients using “sow, select, sequence” experiments.

•  Evaluate the impact of switchgrass traits on ecosystem processes in stand plantings

Project 2: GENOMIC RESOURCES FOR SWITCHGRASS

The switchgrass community has benefited from considerable investment by DOE in genomic tools. Core resources include a high-quality genome assembly and annotation (Alamo-AP13), Gene Atlas characterization of gene expression, and diversity resequencing. These items are vital to the success of our genetic mapping, pre-breeding and improvement efforts. In collaboration with JGI, we will expand these resources in support of our project and the broader switchgrass community.

Goals:

• Extend switchgrass genomic resources with advanced genome assemblies spanning diversity groups

• Improve genetic mapping analyses to capture content variation and its impact on adaptation using advanced[JTE1]  pan-genome and k-mer based mapping

Project 3: FUNCTIONAL GENOMICS TO DISCOVER KEY PANICUM GENES

Functional genomic tools have been critical in expanding our understanding of key aspects of plant biology. In particular, mutant populations have been remarkably powerful tools for gene discovery (Redei and Koncz 1992) in both forward and reverse genetics. In forward genetics, a mutant population is phenotyped for a feature of interest to identify lines carrying unknown lesions in genes affecting the trait. Co-segregation and map-based cloning, or more recently sequencing based methods, can then identify causal genes. Forward mutant screens are especially valuable because of their ability to make novel discoveries. In contrast, reverse genetic studies center on studying known genes, perhaps identified from earlier studies or in other species or from features of its gene model. Unfortunately, no mutant resources have been available for perennial feedstock grasses. This is due to their complex outbred and polyploidy nature, and has limited widespread gene discovery and annotation in feedstocks. A library of mutants affords an easy means of identifying new genes or alleles and allows a host of subsequent functional genomic studies. In addition to clean complementation, functional genomic methods allow for the development of targeted gene knockouts, the creation of over-expression lines, and specific gene edits. Here, we develop mutant population and functional genomic tools for Panicum hallii and P. virgatum.

Goals:

•  Identify genes influencing key adaptation and sustainability traits in Panicum[JTE1]  using a novel fast-neutron mutant population as both a forward and reverse genetics tool.

• Extend transformation and gene editing methods in P. hallii and P. virgatum, including the development of new tools for the study of perennial grass biology.

Project 4: DISCOVERING PLANT-MICROBE DRIVERS OF ADAPTATION AND SUSTAINABILITY

Nearly every compartment of a plant harbors communities of bacteria, fungi, oomycetes, protists, and/or viruses. Together they can influence host growth, fitness, and local adaptation. We have developed a preliminary characterization of the switchgrass microbiome using culture- and sequence-based assays. These methods have identified thousands of microbes and quantified their abundance across the species range. In parallel, we have used genetic mapping to identify regions of the host genome influencing associations with individual microbes. These studies have generated exciting hypotheses about plant–microbe interactions and their role in adaptation. Here, we further build a culture collection of microbes for use in experiments and study both synthetic and evolved communities and their role in stress tolerance using growth chamber, greenhouse, and field experiments. 

Goals:

• Fully characterize the switchgrass microbiome through sequencing and microbial isolate collections across field sites, host material, and years.

• Leverage switchgrass GWAS and the P. hallii mutant population to identify candidate genes affecting plant-microbial interactions.

• Use microbial selection experiments to manipulate microbial communities to improve plant performance and sustainability

• Study individual microbes, in both synthetic and evolve communities, and their roles in stress tolerance

PROJECT 5: PREDICTING AND TESTING PERFORMANCE AND SUSTAINABILITY

Despite more than two decades of research, there are still surprisingly large gaps in our understanding of switchgrass biology. Unfortunately, collection of vital data will take time and modeling will be an important tool for filling gaps, directing empirical studies, and pre-breeding efforts. We will link information from Projects 1-4 with modeling to generate performance predictions across environmental gradients. We will leverage genomic prediction as a starting point for designing and creating switchgrass ideotypes.  We will strengthen and test the sensitivity of predictions with expanded data collected in our garden experiments, then utilize forecasts from these initial models to frame new field plantings of modified plants to measure plant performance across soil–climate gradients.

Goals:

• Use common gardens to evaluate performance and sustainability in diverse environments and stands.

• Use targeted crosses, gene edits, and microbiome amendments to stack key traits and create generalists/specialist switchgrass guided by prediction from models

• Use genomic selection to predict plant performance, performance stability, and sustainability.