Dataset Information

Oxalate oxidases and differentiating surface structure in wheat: germins.

ABSTRACT: Oxalate oxidases (OXOs) have been found to be concentrated in the surface tissues of wheat embryos and grains: germin is concentrated in root and leaf sheaths that surround germinated embryos; pseudogermin (OXO-psi) is concentrated in the epidermis and bracts that 'encircle' mature grains. Most strikingly, the epidermal accumulation of OXO-psi was found to presage the transition of a delicate 'skin', similar to the fragile epidermis of human skin, into the tough shell (the miller's 'beeswing') that is typical of mature wheat grains. A narrow range of oxalate concentration (1--2 mM) in the hydrated tissues of major crop cereals (barley, maize, oat, rice, rye and wheat) contrasted with wide variations in their OXO expression, e.g. cold-tolerant and cold-sensitive varieties of maize have similar oxalate contents but the former was found to contain approx. 20-fold more germin than did the latter. Well-known OXOs in sorghum, a minor cereal, and beet, a dicotyledon, were found to have little antigenic relatedness to the germins, but the beet enzyme did share some of the unique stability properties that are peculiar to the germin-like OXOs that are found only in the major crop cereals. Their concentration in surface structures of domesticated wheat suggests a biochemical role for germin-like OXOs: programmed cell death in surface tissues might be a constitutive as well as an adaptive form of differentiation that helps to produce refractory barriers against tissue invasion by predators. Incidental to the principal investigation, and using an OXO assay (oxalate-dependent release of CO(2)) that did not rely on detecting H(2)O(2), which is often fully degraded in cell extracts, it was found that OXO activity in soluble extracts of wheat was manifested only in standard solution assays if the extract was pretreated in a variety of ways, which included preincubation with pepsin or highly substituted glucuronogalactoarabinoxylans (cell-wall polysaccharides).

SUBMITTER: Lane BG

PROVIDER: S-EPMC1221152 | biostudies-other | 2000 Jul

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:Ensuring future food security for a growing population while climate change and urban sprawl put pressure on agricultural land will require sustainable intensification of current farming practices. For the crop breeder this means producing higher crop yields with less resources due to greater environmental stresses. While easy gains in crop yield have been made mostly "above ground," little progress has been made "below ground"; and yet it is these root system traits that can improve productivity and resistance to drought stress. Wheat pre-breeders use soil coring and core-break counts to phenotype root architecture traits, with data collected on rooting density for hundreds of genotypes in small increments of depth. The measured densities are both large datasets and highly variable even within the same genotype, hence, any rigorous, comprehensive statistical analysis of such complex field data would be technically challenging. Traditionally, most attributes of the field data are therefore discarded in favor of simple numerical summary descriptors which retain much of the high variability exhibited by the raw data. This poses practical challenges: although plant scientists have established that root traits do drive resource capture in crops, traits that are more randomly (rather than genetically) determined are difficult to breed for. In this paper we develop a hierarchical nonlinear mixed modeling approach that utilizes the complete field data for wheat genotypes to fit, under the Bayesian paradigm, an "idealized" relative intensity function for the root distribution over depth. Our approach was used to determine heritability: how much of the variation between field samples was purely random vs. being mechanistically driven by the plant genetics? Based on the genotypic intensity functions, the overall heritability estimate was 0.62 (95% Bayesian confidence interval was 0.52 to 0.71). Despite root count profiles that were statistically very noisy, our approach led to denoised profiles which exhibited rigorously discernible phenotypic traits. Profile-specific traits could be representative of a genotype, and thus, used as a quantitative tool to associate phenotypic traits with specific genotypes. This would allow breeders to select for whole root system distributions appropriate for sustainable intensification, and inform policy for mitigating crop yield risk and food insecurity.

Dataset Information

Oxalate oxidases and differentiating surface structure in wheat: germins.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure