[show abstract][hide abstract] ABSTRACT: Grass species represent a major source of food, feed, and fiber crops and potential feedstocks for biofuel production. Most of the biomass is contributed by cell walls that are distinct in composition from all other flowering plants. Identifying cell wall-related genes and their functions underpins a fundamental understanding of growth and development in these species. Toward this goal, we are building a knowledge base of the maize (Zea mays) genes involved in cell wall biology, their expression profiles, and the phenotypic consequences of mutation. Over 750 maize genes were annotated and assembled into gene families predicted to function in cell wall biogenesis. Comparative genomics of maize, rice (Oryza sativa), and Arabidopsis (Arabidopsis thaliana) sequences reveal differences in gene family structure between grass species and a reference eudicot species. Analysis of transcript profile data for cell wall genes in developing maize ovaries revealed that expression within families differed by up to 100-fold. When transcriptional analyses of developing ovaries before pollination from Arabidopsis, rice, and maize were contrasted, distinct sets of cell wall genes were expressed in grasses. These differences in gene family structure and expression between Arabidopsis and the grasses underscore the requirement for a grass-specific genetic model for functional analyses. A UniformMu population proved to be an important resource in both forward- and reverse-genetics approaches to identify hundreds of mutants in cell wall genes. A forward screen of field-grown lines by near-infrared spectroscopic screen of mature leaves yielded several dozen lines with heritable spectroscopic phenotypes. Pyrolysis-molecular beam mass spectrometry confirmed that several nir mutants had altered carbohydrate-lignin compositions.
[show abstract][hide abstract] ABSTRACT: The maize (Zea mays) brittle stalk2 (bk2) is a recessive mutant, the aerial parts of which are easily broken. The bk2 phenotype is developmentally regulated and appears 4 weeks after planting, at about the fifth-leaf stage. Before this time, mutants are indistinguishable from wild-type siblings. Afterward, all organs of the bk2 mutants turn brittle, even the preexisting ones, and they remain brittle throughout the life of the plant. Leaf tension assays and bend tests of the internodes show that the brittle phenotype does not result from loss of tensile strength but from loss in flexibility that causes the tissues to snap instead of bend. The Bk2 gene was cloned by a combination of transposon tagging and a candidate gene approach and found to encode a COBRA-like protein similar to rice (Oryza sativa) BC1 and Arabidopsis (Arabidopsis thaliana) COBRA-LIKE4. The outer periphery of the stalk has fewer vascular bundles, and the sclerids underlying the epidermis possess thinner secondary walls. Relative cellulose content is not strictly correlated with the brittle phenotype. Cellulose content in mature zones of bk2 mature stems is lowered by 40% but is about the same as wild type in developing stems. Although relative cellulose content is lowered in leaves after the onset of the brittle phenotype, total wall mass as a proportion of dry mass is either unchanged or slightly increased, indicating a compensatory increase in noncellulosic carbohydrate mass. Fourier transform infrared spectra indicated an increase in phenolic ester content in the walls of bk2 leaves and stems. Total content of lignin is unaffected in bk2 juvenile leaves before or after appearance of the brittle phenotype, but bk2 mature and developing stems are markedly enriched in lignin compared to wild-type stems. Despite increased lignin in bk2 stems, loss of staining with phloroglucinol and ultraviolet autofluorescence is observed in vascular bundles and sclerid layers. Consistent with the infrared analyses, levels of saponifiable hydroxycinnamates are elevated in bk2 leaves and stems. As Bk2 is highly expressed during early development, well before the onset of the brittle phenotype, we propose that Bk2 functions in a patterning of lignin-cellulosic interactions that maintain organ flexibility rather than having a direct role in cellulose biosynthesis.
[show abstract][hide abstract] ABSTRACT: About 10% of plant genomes are devoted to cell wall biogenesis. Our goal is to establish methodologies that identify and classify cell wall phenotypes of mutants on a genome-wide scale. Toward this goal, we have used a model system, the elongating maize (Zea mays) coleoptile system, in which cell wall changes are well characterized, to develop a paradigm for classification of a comprehensive range of cell wall architectures altered during development, by environmental perturbation, or by mutation. Dynamic changes in cell walls of etiolated maize coleoptiles, sampled at one-half-d intervals of growth, were analyzed by chemical and enzymatic assays and Fourier transform infrared spectroscopy. The primary walls of grasses are composed of cellulose microfibrils, glucuronoarabinoxylans, and mixed-linkage (1 --> 3),(1 --> 4)-beta-D-glucans, together with smaller amounts of glucomannans, xyloglucans, pectins, and a network of polyphenolic substances. During coleoptile development, changes in cell wall composition included a transient appearance of the (1 --> 3),(1 --> 4)-beta-D-glucans, a gradual loss of arabinose from glucuronoarabinoxylans, and an increase in the relative proportion of cellulose. Infrared spectra reflected these dynamic changes in composition. Although infrared spectra of walls from embryonic, elongating, and senescent coleoptiles were broadly discriminated from each other by exploratory principal components analysis, neural network algorithms (both genetic and Kohonen) could correctly classify infrared spectra from cell walls harvested from individuals differing at one-half-d interval of growth. We tested the predictive capabilities of the model with a maize inbred line, Wisconsin 22, and found it to be accurate in classifying cell walls representing developmental stage. The ability of artificial neural networks to classify infrared spectra from cell walls provides a means to identify many possible classes of cell wall phenotypes. This classification can be broadened to phenotypes resulting from mutations in genes encoding proteins for which a function is yet to be described.