An integrated framework reinstating the environmental dimension for GWAS and genomic selection in crops.

Identifying mechanisms and pathways involved in gene-environment interplay and phenotypic plasticity is a long-standing challenge. It is highly desirable to establish an integrated framework with an environmental dimension for complex trait dissection and prediction. A critical step is to identify an environmental index that is both biologically relevant and estimable for new environments. With extensive field-observed complex traits, environmental profiles, and genome-wide single nucleotide polymorphisms for three major crops (maize, wheat, and oat), we demonstrated that identifying such an environmental index (i.e., a combination of environmental parameter and growth window) enables genome-wide association studies and genomic selection of complex traits to be conducted with an explicit environmental dimension. Interestingly, genes identified for two reaction-norm parameters (i.e., intercept and slope) derived from flowering time values along the environmental index were less colocalized for a diverse maize panel than for wheat and oat breeding panels, agreeing with the different diversity levels and genetic constitutions of the panels. In addition, we showcased the usefulness of this framework for systematically forecasting the performance of diverse germplasm panels in new environments. This general framework and the companion CERIS-JGRA analytical package should facilitate biologically informed dissection of complex traits, enhanced performance prediction in breeding for future climates, and coordinated efforts to enrich our understanding of mechanisms underlying phenotypic variation.

Examination of climatological wind patterns and simulated pollen dispersion in a complex island environment.

Complex terrain creates small-scale circulations which affect pollen dispersion but may be missed by meteorological observing networks and coarse-grid meteorological models. On volcanic islands, these circulations result from differing rates of surface heating between land and sea as well as rugged terrain. We simulated the transport of bentgrass, ryegrass, and maize pollen from 30 sources within the agricultural regions of the Hawaiian island Kaua'i during climatological conditions spanning season conditions and the La Niña, El Niño, and neutral phases of the El Niño-Southern Oscillation. Both pollen size and source location had major effects on predicted dispersion over and near the island. Three patterns of pollen dispersion were identified in response to prevailing wind conditions: southwest winds transported pollen inland, funneling pollen grains through valleys; east winds transported pollen over the ocean, with dispersive tails for the smallest pollen grains following the mean wind and extending as far as the island of Ni'ihau 35 km away; and northeast winds moved pollen inland counter to the prevailing flow due to a sea breeze circulation that formed over the source region. These results are the first to predict the interactions between complex island terrain and local climatology on grass pollen dispersion. They demonstrate how numerical modeling can provide guidance for field trials by illustrating the common flow regimes present in complex terrain, allowing field trials to focus on areas where successful sampling is more likely to occur.

A systems biology approach toward understanding seed composition in soybean.

BACKGROUND: The molecular, biochemical, and genetic mechanisms that regulate the complex metabolic network of soybean seed development determine the ultimate balance of protein, lipid, and carbohydrate stored in the mature seed. Many of the genes and metabolites that participate in seed metabolism are unknown or poorly defined; even more remains to be understood about the regulation of their metabolic networks. A global omics analysis can provide insights into the regulation of seed metabolism, even without a priori assumptions about the structure of these networks. RESULTS: With the future goal of predictive biology in mind, we have combined metabolomics, transcriptomics, and metabolic flux technologies to reveal the global developmental and metabolic networks that determine the structure and composition of the mature soybean seed. We have coupled this global approach with interactive bioinformatics and statistical analyses to gain insights into the biochemical programs that determine soybean seed composition. For this purpose, we used Plant/Eukaryotic and Microbial Metabolomics Systems Resource (PMR, http://www.metnetdb.org/pmr, a platform that incorporates metabolomics data to develop hypotheses concerning the organization and regulation of metabolic networks, and MetNet systems biology tools http://www.metnetdb.org for plant omics data, a framework to enable interactive visualization of metabolic and regulatory networks. CONCLUSIONS: This combination of high-throughput experimental data and bioinformatics analyses has revealed sets of specific genes, genetic perturbations and mechanisms, and metabolic changes that are associated with the developmental variation in soybean seed composition. Researchers can explore these metabolomics and transcriptomics data interactively at PMR.

Making the most of a scarce platinum-group metal: conductive ruthenia nanoskins on insulating silica paper.

Subambient thermal decomposition of ruthenium tetroxide from nonaqueous solution onto porous SiO(2) substrates creates 2-3 nm thick coatings of RuO(2) that cover the convex silica walls comprising the open, porous structure. The physical properties of the resultant self-wired nanoscale ruthenia significantly differ depending on the nature of the porous support. Previously reported RuO(2)-modified SiO(2) aerogels display electron conductivity of 5 x 10(-4) S cm(-1) (as normalized to the geometric factor of the insulating substrate, not the conducting ruthenia phase), whereas RuO(2)-modified silica filter paper at approximately 5 wt % RuO(2) exhibits approximately 0.5 S cm(-1). Electron conduction through the ruthenia phase as examined from -160 to 260 degrees C requires minimal activation energy, only 8 meV, from 20 to 260 degrees C. The RuO(2)(SiO(2)) fiber membranes are electrically addressable, capable of supporting fast electron-transfer reactions, express an electrochemical surface area of approximately 90 m(2) g(-1) RuO(2), and exhibit energy storage in which 90% of the total electron-proton charge is stored at the outer surface of the ruthenia phase. The electrochemical capacitive response indicates that the nanocrystalline RuO(2) coating can be considered to be a single-unit-thick layer of the conductive oxide, as physically stabilized by the supporting silica fiber.

Metabolic flux maps comparing the effect of temperature on protein and oil biosynthesis in developing soybean cotyledons.

Metabolic flux maps developed from 13C metabolic flux analysis (13C MFA) are effective tools for assessing the response of biological systems to genetic or environmental perturbations, and for identifying possible metabolic engineering targets. Experimental treatments were designed to distinguish between temperature effects prior to, and during incubation in vitro, on primary metabolism in developing soybeans. Biomass accumulation increased with temperature as did carbon partitioning into lipids. The flux through the plastidic oxidative pentose phosphate pathway (pgl(P)) relative to sucrose intake remained fairly constant [ approximately 56% (+/-24%)] when cotyledons were transferred from an optimum growth temperature to varying temperatures in in vitro culture, signifying a rigid node under these conditions. However, pgl(P) flux ranged from 57 to 77% of sucrose intake when growth temperature in planta varied and were cultured in vitro at the same temperature (as the plant), indicating a flexible node for this case. The carbon flux through the anaplerotic reactions catalysed by plastidic malic enzyme (me(P)), cytosolic phosphoenolpyruvate (PEP) carboxylase and the malate (Mal) transporter from the cytosol to mitochondrion varied dramatically with temperature and had a direct influence on the carbon partitioning into protein and oil from the plastidic pyruvate (Pyr) pool. These results of the in vitro culture indicate that temperature during early stages of development has a dominant effect on establishing capacity for flux through certain components of central carbon metabolism.

Gene flow in maize fields with different local pollen densities.

The development of maize (Zea mays L.) varieties as factories of pharmaceutical and industrial compounds has renewed interest in controlling pollen dispersal. The objective of this study was to compare gene flow into maize fields of different local pollen densities under the same environmental conditions. Two fields of approximately 36 ha were planted with a nontransgenic, white hybrid, in Ankeny, Iowa, USA. In the center of both fields, a 1-ha plot of a yellow-seeded stacked RR/Bt transgenic hybrid was planted as a pollen source. Before flowering, the white receiver maize of one field was detasseled in a 4:1 ratio to reduce the local pollen density (RPD). The percentage of outcross in the field with RPD was 42.2%, 6.3%, and 1.3% at 1, 10, and 35 m from the central plot, respectively. The percentage of outcross in the white maize with normal pollen density (NPD) was 30.1%, 2.7%, and 0.4%, respectively, at these distances. At distances greater than 100 m, the outcross frequency decreased below 0.1 and 0.03% in the field with RPD and NPD, respectively. A statistical model was used to compare pollen dispersal based on observed outcross percentages. The likelihood ratio test confirmed that the models of outcrossing in the two fields were significantly different (P is practically 0). Results indicated that when local pollen is low, the incoming pollen has a competitive advantage and the level of outcross is significantly greater than when the local pollen is abundant.

Quantification of compartmented metabolic fluxes in developing soybean embryos by employing biosynthetically directed fractional (13)C labeling, two-dimensional [(13)C, (1)H] nuclear magnetic resonance, and comprehensive isotopomer balancing.

Metabolic flux quantification in plants is instrumental in the detailed understanding of metabolism but is difficult to perform on a systemic level. Toward this aim, we report the development and application of a computer-aided metabolic flux analysis tool that enables the concurrent evaluation of fluxes in several primary metabolic pathways. Labeling experiments were performed by feeding a mixture of U-(13)C Suc, naturally abundant Suc, and Gln to developing soybean (Glycine max) embryos. Two-dimensional [(13)C, (1)H] NMR spectra of seed storage protein and starch hydrolysates were acquired and yielded a labeling data set consisting of 155 (13)C isotopomer abundances. We developed a computer program to automatically calculate fluxes from this data. This program accepts a user-defined metabolic network model and incorporates recent mathematical advances toward accurate and efficient flux evaluation. Fluxes were calculated and statistical analysis was performed to obtain sds. A high flux was found through the oxidative pentose phosphate pathway (19.99 +/- 4.39 micromol d(-1) cotyledon(-1), or 104.2 carbon mol +/- 23.0 carbon mol per 100 carbon mol of Suc uptake). Separate transketolase and transaldolase fluxes could be distinguished in the plastid and the cytosol, and those in the plastid were found to be at least 6-fold higher. The backflux from triose to hexose phosphate was also found to be substantial in the plastid (21.72 +/- 5.00 micromol d(-1) cotyledon(-1), or 113.2 carbon mol +/-26.0 carbon mol per 100 carbon mol of Suc uptake). Forward and backward directions of anaplerotic fluxes could be distinguished. The glyoxylate shunt flux was found to be negligible. Such a generic flux analysis tool can serve as a quantitative tool for metabolic studies and phenotype comparisons and can be extended to other plant systems.