High-resolution melt-curve analysis of random-amplified-polymorphic-DNA markers, for the characterisation of pathogenic Leptospira.

A new test for pathogenic Leptospira isolates, based on RAPD-PCR and high-resolution melt (HRM) analysis (which measures the melting temperature of amplicons in real time, using a fluorescent DNA-binding dye), has recently been developed. A characteristic profile of the amplicons can be used to define serovars or detect genotypes. Ten serovars, of leptospires from the species Leptospira interrogans (serovars Australis, Robinsoni, Hardjo, Pomona, Zanoni, Copenhageni and Szwajizak), L. borgpetersenii (serovar Arborea), L. kirschneri (serovar Cynopteri) and L. weilii (serovar Celledoni), were typed against 13 previously published RAPD primers, using a real-time cycler (the Corbett Life Science RotorGene 6000) and the optimised reagents from a commercial kit (Quantace SensiMix). RAPD-HRM at specific temperatures generated defining amplicon melt profiles for each of the tested serovars. These profiles were evaluated as difference-curve graphs generated using the RotorGene software package, with a cut-off of at least 8 'U' (plus or minus). The results demonstrated that RAPD-HRM can be used to measure serovar diversity and establish identity, with a high degree of stability. The characterisation of Leptospira serotypes using a DNA-based methodology is now possible. As an objective and relatively inexpensive and rapid method of serovar identification, at least for cultured isolates, RAPD-HRM assays show convincing potentia.

Simple software processes and tests improve the reliability and usefulness of a model.

Models are abstractions of reality that have predetermined limits (often not consciously thought through) on what problem domains the models can be used to explore. These limits are determined by the range of observed data used to construct and validate the model. However, it is important to remember that operating the model beyond these limits, one of the reasons for building the model in the first place, potentially brings unwanted behaviour and thus reduces the usefulness of the model. Our experience with the Agricultural Production Systems Simulator (APSIM), a farming systems model, has led us to adapt techniques from the disciplines of modelling and software development to create a model development process. This process is simple, easy to follow, and brings a much higher level of stability to the development effort, which then delivers a much more useful model. A major part of the process relies on having a range of detailed model tests (unit, simulation, sensibility, validation) that exercise a model at various levels (sub-model, model and simulation). To underline the usefulness of testing, we examine several case studies where simulated output can be compared with simple relationships. For example, output is compared with crop water use efficiency relationships gleaned from the literature to check that the model reproduces the expected function. Similarly, another case study attempts to reproduce generalised hydrological relationships found in the literature. This paper then describes a simple model development process (using version control, automated testing and differencing tools), that will enhance the reliability and usefulness of a model.

Breedcow and Dynama software redevelopment

The project renewed the Breedcow and Dynama software making it compatible with modern computer operating systems and platforms. Enhancements were also made to the linkages between the individual programs and their operation. The suite of programs is a critical component of the skill set required to make soundly based plans and production choices in the north Australian beef industry.

ITC Hardwoods Nutrition R&D

Hardwoods nutrition R&D to improve tree growth, wood quality and resistance to disease attack. Improved diagnotic tools. North Queensland and Burnett region soils.

DNA markers linked to the R(2) rust resistance gene in sunflower (Helianthus annuus L.) facilitate anticipatory breeding for this disease variant.

Pre-emptive breeding for host disease resistance is an effective strategy for combating and managing devastating incursions of plant pathogens. Comprehensive, long-term studies have revealed that virulence to the R (2) sunflower (Helianthus annuus L.) rust resistance gene in the line MC29 does not exist in the Australian rust (Puccinia helianthi) population. We report in this study the identification of molecular markers linked to this gene. The three simple sequence repeat (SSR) markers ORS795, ORS882, and ORS938 were linked in coupling to the gene, while the SSR marker ORS333 was linked in repulsion. Reliable selection for homozygous-resistant individuals was efficient when the three markers, ORS795, ORS882, and ORS333, were used in combination. Phenotyping for this resistance gene is not possible in Australia without introducing a quarantinable race of the pathogen. Therefore, the availability of reliable and heritable DNA-based markers will enable the efficient deployment of this gene, permitting a more effective strategy for generating sustainable commercial cultivars containing this rust resistance gene.

The use of genetic correlations to evaluate associations between SNP markers and quantitative traits

Open-pollinated progeny of Corymbia citriodora established in replicated field trials were assessed for stem diameter, wood density, and pulp yield prior to genotyping single nucleotide polymorphisms (SNP) and testing the significance of associations between markers and assessment traits. Multiple individuals within each family were genotyped and phenotyped, which facilitated a comparison of standard association testing methods and an alternative method developed to relate markers to additive genetic effects. Narrow-sense heritability estimates indicated there was significant additive genetic variance within this population for assessment traits ( h ˆ 2 =0.28to0.44 ) and genetic correlations between the three traits were negligible to moderate (r G = 0.08 to 0.50). The significance of association tests (p values) were compared for four different analyses based on two different approaches: (1) two software packages were used to fit standard univariate mixed models that include SNP-fixed effects, (2) bivariate and multivariate mixed models including each SNP as an additional selection trait were used. Within either the univariate or multivariate approach, correlations between the tests of significance approached +1; however, correspondence between the two approaches was less strong, although between-approach correlations remained significantly positive. Similar SNP markers would be selected using multivariate analyses and standard marker-trait association methods, where the former facilitates integration into the existing genetic analysis systems of applied breeding programs and may be used with either single markers or indices of markers created with genomic selection processes.

Online identification guides for Australian smut fungi (Ustilaginomycotina) and rust fungi (Pucciniales)

Interactive identification keys for Australian smut fungi (Ustilaginomycotina and Pucciniomycotina, Microbotryales) and rust fungi (Pucciniomycotina, Pucciniales) are available online at http://collections.daff.qld.gov.au. The keys were built using Lucid software, and facilitate the identification of all known Australian smut fungi (317 species in 37 genera) and 100 rust fungi (from approximately 360 species in 37 genera). The smut and rust keys are illustrated with over 1,600 and 570 images respectively. The keys are designed to assist a wide range of end-users including mycologists, plant health diagnosticians, biosecurity scientists, plant pathologists, and university students. The keys are dynamic and will be regularly updated to include taxonomic changes and incorporate new detections, taxa, distributions and images. Researchers working with Australian smut and rust fungi are encouraged to participate in the on-going development and improvement of these keys.