Using biplots to interpret gene expression patterns in plants

Sum: Plant biologists in fields of ecology, evolution, genetics and breeding frequently use multivariate methods. This paper illustrates Principal Component Analysis (PCA) and Gabriel's biplot as applied to microarray expression data from plant pathology experiments. Availability: An example program in the publicly distributed statistical language R is available from the web site (www.tpp.uq.edu.au) and by e-mail from the contact. Contact: scott.chapman@csiro.au.

Pathogens associated with nursery plants imported into Western Australia

A small survey of the potting mix taken from 15 consignments of nursery grown plants imported into Western Australia from other states in Australia found that Phytophthora spp. were present in 10% of the samples and Pythium spp. were present in 25% of the samples. Plant pathogenic nematodes were isolated from 12 of 13 consignments. Potting mix appears to be an important route by which plant pathogens can be passively introduced into Western Australia.

Virtual plants - integrating architectural and physiological models

Recent advances in computer technology have made it possible to create virtual plants by simulating the details of structural development of individual plants. Software has been developed that processes plant models expressed in a special purpose mini-language based on the Lindenmayer system formalism. These models can be extended from their architectural basis to capture plant physiology by integrating them with crop models, which estimate biomass production as a consequence of environmental inputs. Through this process, virtual plants will gain the ability to react to broad environmental conditions, while crop models will gain a visualisation component. This integration requires the resolution of the fundamentally different time scales underlying the approaches. Architectural models are usually based on physiological time; each time step encompasses the same amount of development in the plant, without regard to the passage of real time. In contrast, physiological models are based in real time; the amount of development in a time step is dependent on environmental conditions during the period. This paper provides a background on the plant modelling language, then describes how widely-used concepts of thermal time can be implemented to resolve these time scale differences. The process is illustrated using a case study. (C) 1997 Elsevier Science Ltd.

Supervisory control of wastewater treatment plants by combining principal component analysis and fuzzy c-means clustering

In this paper a methodology for integrated multivariate monitoring and control of biological wastewater treatment plants during extreme events is presented. To monitor the process, on-line dynamic principal component analysis (PCA) is performed on the process data to extract the principal components that represent the underlying mechanisms of the process. Fuzzy c-means (FCM) clustering is used to classify the operational state. Performing clustering on scores from PCA solves computational problems as well as increases robustness due to noise attenuation. The class-membership information from FCM is used to derive adequate control set points for the local control loops. The methodology is illustrated by a simulation study of a biological wastewater treatment plant, on which disturbances of various types are imposed. The results show that the methodology can be used to determine and co-ordinate control actions in order to shift the control objective and improve the effluent quality.

Promoters for pregenomic RNA of banana streak badnavirus are active for transgene expression in monocot and dicot plants

Two putative promoters from Australian banana streak badnavirus (BSV) isolates were analysed for activity in different plant species. In transient expression systems the My (2105 bp) and Cv (1322 bp) fragments were both shown to have promoter activity in a wide range of plant species including monocots (maize, barley, banana, millet, wheat, sorghum), dicots (tobacco, canola, sunflower, Nicotiana benthamiana, tipu tree), gymnosperm (Pinus radiata) and fern (Nephrolepis cordifolia). Evaluation of the My and Cv promoters in transgenic sugarcane, banana and tobacco plants demonstrated that these promoters could drive high-level expression of either the green fluorescent protein (GFP) or the beta -glucuronidase (GUS) reporter gene (uidA) in vegetative plant cells. In transgenic sugarcane plants harbouring the Cv promoter, GFP expression levels were comparable or higher (up to 1.06% of total soluble leaf protein as GFP) than those of plants containing the maize ubiquitin promoter (up to 0.34% of total soluble leaf protein). GUS activities in transgenic in vitro-grown banana plants containing the My promoter were up to seven-fold stronger in leaf tissue and up to four-fold stronger in root and corm tissue than in plants harbouring the maize ubiquitin promoter. The Cv promoter showed activities that were similar to the maize ubiquitin promoter in in vitro-grown banana plants, but was significantly reduced in larger glasshouse-grown plants. In transgenic in vitro-grown tobacco plants, the My promoter reached activities close to those of the 35S promoter of cauliflower mosaic virus (CaMV), while the Cv promoter was about half as active as the CaMV 35S promoter. The BSV promoters for pregenomic RNA represent useful tools for the high-level expression of foreign genes in transgenic monocots.