USDA-DOE Plant Feedstock Genomics for Bioenergy

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USDA-DOE Plant Feedstock Genomics for Bioenergy BERAC Thursday, June 7, 2012 Cathy Ronning, DOE-BER Ed Kaleikau, USDA-NIFA

Plant Feedstock Genomics for Bioenergy Joint competitive grants program initiated in 2006 DOE Office of Science Office of Biological and Environmental Research USDA National Institute of Food and Agriculture (formerly USDA-CSREES) Agriculture and Food Research Initiative (AFRI) Competitive Grants Program

Goal: Genomics-based research leading to improved use of biomass and plant feedstocks for the production of fuels such as ethanol or renewable chemical feedstocks: Improve biomass characteristics, biomass yield, or sustainability, water and nitrogen use efficiency Understand carbon partitioning and nutrient cycling in feedstocks Enhance fundamental knowledge of structure, function, and organization of feedstock plant genomes Enable plants to be efficiently bred or manipulated for such use

USDA-DOE Joint Program supports Regulation of: gene networks proteins metabolites Comparative genomics Systems biology basic research: Integration of genomics with more traditional approaches Lignin biosynthetic pathway

The program scope has evolved: 2006-2007 Regulatory mechanisms: lignocellulose, cell wall Genetic markers Genome organization Model plants Regulatory mechanisms: feedstock manipulation -Sustainability, environmental stresses -Comparative analyses, bioinformatics Regulatory networks: C partitioning, nutrient cycling Phenotyping for gene/allele discovery Phenomics (genotype-to-phenotype)

The program scope has evolved: Regulatory mechanisms: lignocellulose, cell wall Genetic markers Genome organization Model plants 2008 Regulatory mechanisms: feedstock manipulation -Sustainability, environmental stresses -Comparative analyses, bioinformatics Regulatory networks: C partitioning, nutrient cycling Phenotyping for gene/allele discovery Phenomics (genotype-to-phenotype)

The program scope has evolved: Regulatory mechanisms: lignocellulose, cell wall Genetic markers Genome organization Model plants Regulatory mechanisms: feedstock manipulation -Sustainability, environmental stresses -Comparative analyses, bioinformatics 2009-2010 Regulatory networks: C partitioning, nutrient cycling Phenotyping for gene/allele discovery Phenomics (genotype-to-phenotype)

The program scope has evolved: Regulatory mechanisms: lignocellulose, cell wall Genetic markers Genome organization Model plants Regulatory mechanisms: feedstock manipulation -Sustainability, environmental stresses -Comparative analyses, bioinformatics Regulatory networks: C partitioning, nutrient cycling 2011-2012 Phenotyping for gene/allele discovery Phenomics (genotype-to-phenotype)

Project Management Jointly managed between USDA- NIFA and DOE-BER Competitive, peer-reviewed Annual PI meetings, concurrent with DOE-BER Awardee Meeting (DC area, odd years) or Plant and Animal Genome Conference (PAG- San Diego, even years)

Portfolio of Feedstocks: Poplar Medicago Foxtail millet Sorghum Switchgrass Brachypodium Rice Miscanthus Sunflower Prairie Cordgrass Maize Energy Cane Soybean Processes and Resources: Small RNAs Plant-microbe interactions Cell wall biosynthetic pathways Database development

Projects are located across the US:

Allocations by Crop: Populus Brachy Sorghum Switchgrass Rice Grasses Miscanthus Medicago Maize Foxtail millet Sunflower Soybean Energy cane Wheat Prairie cordgrass

Allocations by Research Area: Basic Sciences Genomics/ Genetics/ Breeding Resource Development

96 pubs and counting! Plant Cell Planta Crop Science Theoretical and Applied Genetics Current Opinion Plant Biology Nature Biotechnology PLoS ONE BMC Bioinformatics Science Nature Genetics BMC Plant Biology Nature Crop Science Bioenergy Research Plant Physiology J Proteome Research BMC Genomics PNAS Plant Genome Genetics Plant Cell

Model plant: Brachypodium Brachypodium distachyon: - short life cycle; small genome Australian Plant Phenomics Facility (APPF), Adelaide Laser confocal microscopy of maize leaf. Pink: mesophyll cells (high PSII activity); purple: bundle sheath cells (low activity); green: lignin Chlorophyll fluorescence measures photosynthesis: Arabidopsis (above, wheat (left). Blue: high rate; red: low. With Phenomics, Plant Scientists Hope to Shift Breeding Into Overdrive. Science (2009) 325:380-381

Identification of an important component of the Sorghum Lignin Biosynthetic Pathway Objective: Determine role of brown midrib (bmr6) gene on lignin biosynthesis in sorghum. Approach Search for sorghum lignification gene homologs through comparative genomics. Putative cinnamyl alcohol dehydrogenase (CAD) gene identified, major component of lignin biosynthetic pathway. Cloning and subsequent molecular analysis confirmed identity as bmr6. Results: bmr6 plants display reduced lignin content, relatively little effect on overall plant fitness. Identification of a major sorghum lignin biosynthetic gene will greatly facilitate development of new strategies to convert grass feedstocks to biofuels. Sattler et al (2009), Plant Physiol 150:584-595; Saballos et al (2009), Genetics 181:783-795

Genetic maps of Miscanthus sinensis and M. sacchariflorus reveal synteny with sorghum. Objective: Generate genetic linkage maps to facilitate Miscanthus breeding programs. Approach: EST-SSR-based map constructed using the progenitors of Miscanthus x giganteus; comparative genomic analysis with sorghum. Kim et al. 2012. SSR-based genetic maps of Miscanthus sinensis and M. sacchariflorus, and their comparison to sorghum. Theor Appl Genet doi 10.1007/s00122-012-1790-1. Result/Impact: Genome coverage with cdna-derived SSR loci permitted alignment of Miscanthus linkage groups to sorghum chromosomes, and provides basis for well-saturated molecular linkage map to accelerate breeding.

Maize juvenility gene enhances biofuel production in bioenergy crops Objective: Investigate biomass properties in maize Corngrass1 (Cg1) mutant. Approach: - Cg1 plants maintain juvenility, contain less lignin and more convertible starch. - Transgenic switchgrass with Cg1 has significantly higher glucose release without expensive pretreatment. - Complete inhibition of flowering in Cg1 plants prohibits transgene escape. Result/Impact: Transferring Cg1 gene to bioenergy crops could result in reduced recalcitrance and lowered conversion costs, offering promising new approach for improvement of dedicated bioenergy crops. Chuck et al. 2011. Overexpression of the maize Corngrass1 microrna prevents flowering, improves digestibility, and increases starch content of switchgrass Proc Nat Acad Sci 10.1073/pnas.1113971108.

Yield + Stover Index Yield + Stov Yield + Stover In 7 6 Breeding Research: Corn for both Food and Fuel 5 0 5 1 2 3 9 0 1 2 3 8 7 7 6 MARS Genomewide selection selection MARS QTL-based Genomewide selection selection 6 5 0 1 2 3 MARS Cycle Genomewide of selection selection Multiple QTL all with minor effects for grain yield, lignin, glucose concentration, and glucose release after thermochemical treatment. Higher selection gains for yield and stover quality when all markers, rather than markers with significant effects only, were used in selection. Lorenzana et al. 2010. Quantitative trait loci and trait correlations for maize stover cell wall composition and glucose release for cellulosic ethanol. Crop Sci. 50: 541-555.

Epigenetic modifications and gene expression in Populus Objective: Investigate variation in genomelevel cytosine methylation in poplar. Approach: Methylated DNA (MeDIP) from seven P. trichocarpa tissues sequenced, mapped to reference genome; compared gene expression of methylated and unmethylated genes among tissues. Results/Impact: First description of genomescale epigenomic differentiation of tree or perennial plant species; foundation to understand heterosis and dioecy, facilitate Poplar improvement. Vining et al. 2012. Dynamic DNA cytosine methylation in the Populus trichocarpa genome: tissue-level variation and relationship to gene expression. BMC Genomics 2012, 13:27.

Database Resources for Bioenergy Feedstocks: Soybean KnowledgeBase (SoyKB): Joshi et al. Soybean KnowledgeBase (SoyKB): a web resource for soybean translational genomics. BMC Genomics 2012, 13(Suppl 1):S15. Biofuel Feedstock Genomics Resource (BFGR) Genome Browsers: Arabidopsis thaliana Brachypodium distachyon Oryza sativa Populus trichocarpa Sorghum bicolor Vitis vinifera Zea mays Childs et al. The Biofuel Feedstock Genomics Resource: a web-based portal and database to enable functional genomics of plant biofuel feedstock species. Database 2012; doi:10.1093/database/bar061..

Foxtail millet genome sequence: a collaboration with JGI, BESC, JBEI A model plant more closely related to switchgrass than previously sequenced reference genomes. Also sequenced the wild relative green foxtail (S. viridis) and compared the two genomes. Can be used to study switchgrass traits such as cell wall formation, and to learn how grasses can adapt and thrive under various environmental conditions. Bennetzen et al. 2012. Reference genome sequence of the model plant Setaria. Nature Biotech May 2012; doi:10.1038/nbt.2196.

2011: Ten Projects Selected for Awards Totaling $12.2M ($10.2M DOE, $2M USDA) Switchgrass, Populus, sorghum, Brachypodium, Miscanthus, energy cane 2012: DE-FOA-0000598 issued November, 2011; proposals due February 24, 2012; currently under review

Plant Feedstock Genomics for Bioenergy Contact Information: Cathy Ronning, DOE catherine.ronning@science.doe.gov 301-903-9549 Ed Kaleikau, USDA ekaleikau@nifa.usda.gov 202-401-1931 http://genomicscience.energy.gov/research/doeusda/ index.shtml