Variation in cell wall composition and bioenergy potential of rice straw

2014 Summer.In most grain crops the leaf and straw is often under-utilized. This biomass is largely plant cell wall, whose heterogeneous composition and recalcitrance limits end uses such as forage or bioenergy. I review the desirable traits for several bioenergy pathways from this biomass and identify traits in biomass that need to be optimized for enzymatic or thermochemical conversion of the biomass to energy. Sufficient variation exists across species and varieties for improving these traits through breeding. I assess variation in cellulose, lignin, hemicellulose, ash, total glucose, total xylose, mixed linkage glucan, saccarification yield and efficiency, hydroxyproline content and bulk density across two environments in the leaf and stem tissue of five rice varieties. Environment and tissue type are highly influential on the composition and yield phenotypes, and some traits perform better than others at predicting bioenergy yield in the field environment. Optimizing specific bioenergy-related phenotypes in isolation is not sufficient as overall crop health relies on many components. The plant cell wall serves an important function in crop health as a critical barrier against pests and diseases. I investigate the role of a family of putative broad spectrum defense response genes in rice, OsOXOs, that degrade oxalic acid: a pathogenicity factor. When expression of these genes is modified, I find a large impact on disease resistance to Sclerotinia sclerotiorum but little impact in the presence of Rhizoctonia solani. OsOXOs must play an important role in defense against S. sclerotiorum which relies on oxalic acid as a pathogenicity factor, because OsOXOs can degrade oxalic acid. R. solani utilizes a broader range of enzymes and compounds, limiting the effectiveness of OsOXOs against R. solani. With the bioenergy phenotyping methods optimized above, I assess saccharification yield of a rice mapping population, along with other agronomic traits including total biomass, flowering time, grain yield, and plant height. Transgressive segregation is apparent for all traits and quantitative trait loci (QTL) mapping approaches are presented. With the methods and populations evaluated here, we are closer to identifying the conditions and genes that can maximize biomass tailored for many purposes

Natural variation in Arabidopsis thaliana: Molecular genetic architecture of stress tolerance under water deficit

Abstract only availableThe functional genomics tools available for studying Arabidopsis thaliana are a great resource for researchers trying to characterize and understand the genetic basis of natural variation. Genome wide transcript profiling can simultaneously monitor the gene expression programs regulated by growth and development and signal transduction pathways in response to environmental stress conditions. The responses of plants to water deficit depend on the extent and rate of water loss and its timing and duration. As a physical stress, water deficit triggers biochemical responses through a cascade that includes stress perception, signal transduction and regulation of gene expression. Arabidopsis accessions differ largely in their adaptation to stress tolerance. To understand the genetic basis of this intra-specific variation we analyzed five accessions under gradual water deficit leading to severe stress conditions. The changes in the gene expression profiles under water deficit conditions were studied using functional genomics tools, microarray and quantitative real time PCR and the regulatory roles of stress induced and developmental related transcripts will be discussed.Plant Genomics Internships @ M

Agricultural residue gasification for low-cost, low-carbon decentralized power:An empirical case study in Cambodia

Abstract not availableJohn L. Field, Paul Tanger, Simon J. Shackley, Stephan M. Haefel

Complete harvest: the future of rice as bioenergy, A

Communicating science to different groups of society is a critical need. Beyond basic research which seeks knowledge, applied research attempts to address real world issues; both aspects of scientific research can be highlighted. In order to give our research a broad audience and highlight the motivation, collaboration, and potential benefit of our research, I conceived and directed a short documentary of one of my research projects. Footage was shot both at the field site in the Philippines, and on the Colorado State University campus, along with interviews of some of the key collaborators

TSPmap, a tool making use of traveling salesperson problem solvers in the efficient and accurate construction of high-density genetic linkage maps

BackgroundRecent advances in nucleic acid sequencing technologies have led to a dramatic increase in the number of markers available to generate genetic linkage maps. This increased marker density can be used to improve genome assemblies as well as add much needed resolution for loci controlling variation in ecologically and agriculturally important traits. However, traditional genetic map construction methods from these large marker datasets can be computationally prohibitive and highly error prone.ResultsWe present TSPmap, a method which implements both approximate and exact Traveling Salesperson Problem solvers to generate linkage maps. We demonstrate that for datasets with large numbers of genomic markers (e.g. 10,000) and in multiple population types generated from inbred parents, TSPmap can rapidly produce high quality linkage maps with low sensitivity to missing and erroneous genotyping data compared to two other benchmark methods, JoinMap and MSTmap. TSPmap is open source and freely available as an R package.ConclusionsWith the advancement of low cost sequencing technologies, the number of markers used in the generation of genetic maps is expected to continue to rise. TSPmap will be a useful tool to handle such large datasets into the future, quickly producing high quality maps using a large number of genomic markers

Additional file 4: Figure S2. of TSPmap, a tool making use of traveling salesperson problem solvers in the efficient and accurate construction of high-density genetic linkage maps

Linkage maps generated by TSPmap using marker datasets from A. Arabidopsis thaliana [26] and B. & C. rice [27] compared to those generated by JoinMap. (DOCX 213 kb

Data from: Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice

To ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. Here we demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor-intensive measures of flowering time, height, biomass, grain yield, and harvest index. Genetic mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution

Data from: Cell wall composition and bioenergy potential of rice straw tissues are influenced by environment, tissue type, and genotype

Breeding has transformed wild plant species into modern crops, increasing the allocation of their photosynthetic assimilate into grain, fiber, and other products for human use. Despite progress in increasing the harvest index, much of the biomass of crop plants is not utilized. Potential uses for the large amounts of agricultural residues that accumulate are animal fodder or bioenergy, though these may not be economically viable without additional efforts such as targeted breeding or improved processing. We characterized leaf and stem tissue from a diverse set of rice genotypes (varieties) grown in two environments (greenhouse and field) and report bioenergy-related traits across these variables. Among the 16 traits measured, cellulose, hemicelluloses, lignin, ash, total glucose, and glucose yield changed across environments, irrespective of the genotypes. Stem and leaf tissue composition differed for most traits, consistent with their unique functional contributions and suggesting that they are under separate genetic control. Plant variety had the least influence on the measured traits. High glucose yield was associated with high total glucose and hemicelluloses, but low lignin and ash content. Bioenergy yield of greenhouse-grown biomass was higher than field-grown biomass, suggesting that greenhouse studies overestimate bioenergy potential. Nevertheless, glucose yield in the greenhouse predicts glucose yield in the field (ρ = 0.85, p < 0.01) and could be used to optimize greenhouse (GH) and field breeding trials. Overall, efforts to improve cell wall composition for bioenergy require consideration of production environment, tissue type, and variety