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LETTER TO THE EDITOR

Translational Genomics for Bioenergy Production: There's Room for More Than One Model

Department of Biology
Program in Molecular Plant Biology
Colorado State University
Fort Collins, CO 80523

Jan E. Leach

Department of Bioagricultural Sciences
and Pest Management
Program in Molecular Plant Biology
Colorado State University
Fort Collins, CO 80523

dbush{at}colostate.edu

Lawrence and Walbot's commentary (Lawrence and Walbot, 2007) on the application of translational genomics in developing energy crops focused on maize as the model species for biofuel research. Here, we discuss the reasons why other model species will also make important contributions.

To fully appreciate the value of other models, it is important to consider the traits that must be enhanced in new energy crops if they are to achieve the goals of 30% liquid fuel contribution by 2030 (U.S. DOE, 2006). Ideal energy crops will maximize yield per acre with minimum inputs and exhibit value-added traits that enhance their use as biofuel feedstock. They will have a high water and nutrient use efficiency, they will be resistant to pests and pathogens, and they will display structural characteristics favorable for harvest and processing. These agronomic traits are essential to maximize yield and minimize inputs. Finally, new energy crops ideally would be grown on second-tier agricultural lands because, in the long run, biofuel production should not compete with food production on prime soils. Since the human population is expected to increase by two to three billion people by 2050 (United Nations Population Division revised report 2004 and U.S. Census Bureau), sustainable biofuel production must focus on developing new energy crops with maximum production under limiting conditions for fresh water, nutrients, and temperature.

In addition to enabling agronomic traits, many argue that new energy crops must focus on cell wall production since the bulk of photosynthetic free energy is found in the polymers of this complex matrix (U.S. DOE, 2006). Thus, value-added traits will be developed in new energy crops that enhance yields of usable cell wall components that can be processed into biofuel. Examples include (1) increasing total cell wall content per plant (larger plants), (2) increasing carbon content per individual cell wall, (3) altering the cell wall composition to minimize the energy required to digest available carbon, and (4) introducing new proteins that enhance cell wall digestibility (such as inducible, secreted cellulase) or that create novel feedstocks for biorefining. As developed in the Lawrence and Walbot commentary, the top candidates for the new energy crops are perennial grasses. These grasses are attractive because of their high water and nutrient use efficiency, their large biomass production, and their ability to grow on marginal soils. However, they lack the genetic resources, breeding programs, agricultural know-how, and physiological understanding necessary to drive rapid enhancements of desirable agronomic or value-added traits. Thus, model species that have preexisting genetic and genomic tools must play a major role in speeding the identification and translation of gene(s) that enhance desirable traits in the new energy crops.

Lawrence and Walbot argue that maize should be a primary model for new energy crops because it is a C₄ grass, it is more closely related to candidate perennial grasses (Miscanthus and switchgrass) than other grass models, it has a rich stock of genetic and genomic tools, its genome will be completed in late 2008, and a community of experienced agronomists and researchers already exists. Taken together, these are good arguments for using maize as one model system for new energy crops.

Other grasses also have many desirable characteristics as model systems for new energy crops. In particular, rice is a powerful additional primary model for identifying desirable genes relevant to new energy crops because, along with its tremendous history of improvement and cultivation, it has a deep pool of genetic and genomic resources (Leung et al., 2007). Breeding programs that exploit a wide variety of genetic stocks are already well established for rice worldwide, and mechanisms for exchange of genetic materials are in place. Induced variation in rice is provided by growing collections of tagged lines (Tos17, Ac/Ds, and T-DNA) and collections of chemically or physically induced mutant lines (Hirochika et al., 2004; Wu et al., 2005; http://orygenesdb.cirad.fr/). As with maize, these programs are supported by a community of agronomists, breeders, molecular biologists, and physiologists that will facilitate the discovery and understanding of new genes that enhance the desirable traits outlined above. Rice is not a C₄ grass and therefore would not be an appropriate model to investigate and/or modify that pathway. On the other hand, it is an excellent model for a wealth of other agronomic (nutrient use efficiency, temperature resistance, pest resistance, architectural modification, etc.) and value-added traits that are the primary focus for improving the new energy crops. Genes encoding the catalytic subunit of cellulose synthase (CesA), for example, are considered possible targets for modification of cell wall structure for more efficient ethanol production. That approach is supported by earlier studies of cesA mutants in Arabidopsis and rice (Tanaka et al., 2003; Somerville, 2006). Although CesA genes are present in maize, no mutants have been identified (Holland et al., 2000), presumably because mutation leads to a lethal phenotype. Thus, exclusive use of maize as a model system might not advance understanding of cellulose-associated traits in biofuel production.

Rice genomic tools have moved well beyond the initial genome sequence report in 2002 cited by Lawrence and Walbot. A high-quality, finished sequence of the japonica subspecies (var Nipponbare) (International Rice Genome Sequencing Project, 2005) and a draft sequence (6x sequence coverage) of the indica subspecies (var 93-11; Yu et al., 2005) are now available, and high-quality, uniform annotation of the rice genome continues at both the structural and functional level (Yuan et al., 2005). Rice functional genomic resources include gene expression and expressed sequence tags (Matsumura et al., 1999; Gowda et al., 2004; Nobuta et al., 2007), full-length cDNA information (Kikuchi et al., 2003), and several types of microarray platforms (www.ricearray.org; http://www.affymetrix.com/products/arrays/specific/rice.affx; http://www.chem.agilent.com/Scripts/PDS.asp?lPage=12133). Within 2007, genome-wide single nucleotide polymorphism data for a diverse panel of 20 rice lines will be made public (McNally et al., 2006). The 20 rice lines and the associated phenotypic and molecular data as well as genetic stocks already available or in development from these lines constitute invaluable resources because of the wide phenotypic diversity of traits among the lines, including large differences in biomass accumulation. Rice transformation and regeneration are now fairly routine (Komari et al., 1998; Toki et al., 2006), so once identified, gene function in desirable traits can be validated using a suite of tools and approaches, including the induced variation mentioned above (Hirochika et al., 2004) and gene silencing and overexpression techniques (Miki and Shimamoto, 2004). In addition to the tremendous genomic resources available for rice, there are useful, complementary genomic resources, such as the complete genome sequences of two major rice pathogens, Magnaporthe oryzae (Dean et al., 2005) and Xanthomonas oryzae pv oryzae (Lee et al., 2005; Ochiai et al., 2005).

Together, these extraordinary resources for identifying genes linked to the molecular mechanisms that underlie key agronomic and value-added traits and the ease with which they can be manipulated and studied in rice argue for rice as another useful model for the new energy crops. The power of exploiting natural biodiversity in rice in combination with genomic tools lies in the fact that the same genes can then be examined, and manipulated, in other grasses that are being developed as energy crops. Many of these resources are not available for maize at this time, and it would take many years to develop comparable tools from scratch in grass species currently discussed as energy crops (e.g., switchgrass and Miscanthus). Although rice is not as closely related to switchgrass and Miscanthus as is maize, the high degree of synteny in the grasses suggests there will be little problem translating genomic results from rice to homologous genes in the new energy crops.

Finally, rice is grown in many developing countries and is the primary source of calories for 40% of the world population. Not surprisingly, half of the agronomic biomass residues produced worldwide is rice straw (Sticklen, 2006), which represents a biofuel feedstock for ethanol production in these resource poor communities. Thus, many advances using rice as a biofuel model would translate into direct applications on a global scale for this important food crop.

The take-home message of these brief remarks is that maize and rice are both excellent model species that should be exploited in our drive to develop new energy crops. If we are to advance this field as quickly as possible, we cannot afford to put all our eggs in one basket of discovery.

Footnotes

www.plantcell.org/cgi/doi/10.1105/tpc.107.191040

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