DArT markers: Diversity analyses and mapping in Sorghum bicolor

The sequential nature of gel-based marker systems entails low throughput and high costs per assay. Commonly used marker systems such as SSR and SNP are also dependent on sequence information. These limitations result in high cost per data point and significantly limit the capacity of breeding programs to obtain sufficient return on investment to justify the routine use of marker-assisted breeding for many traits and particularly quantitative traits. Diversity Arrays Technology (DArT™) is a cost effective hybridisation-based marker technology that offers a high multiplexing level while being independent of sequence information. This technology offers sorghum breeding programs an alternative approach to whole-genome profiling. We report on the development, application, mapping and utility of DArT™ markers for sorghum germplasm. Results: A genotyping array was developed representing approximately 12,000 genomic clones using PstI+BanII complexity with a subset of clones obtained through the suppression subtractive hybridisation (SSH) method. The genotyping array was used to analyse a diverse set of sorghum genotypes and screening a Recombinant Inbred Lines (RIL) mapping population. Over 500 markers detected variation among 90 accessions used in a diversity analysis. Cluster analysis discriminated well between all 90 genotypes. To confirm that the sorghum DArT markers behave in a Mendelian manner, we constructed a genetic linkage map for a cross between R931945-2-2 and IS 8525 integrating DArT and other marker types. In total, 596 markers could be placed on the integrated linkage map, which spanned 1431.6 cM. The genetic linkage map had an average marker density of 1/2.39 cM, with an average DArT marker density of 1/3.9 cM. Conclusion: We have successfully developed DArT markers for Sorghum bicolor and have demonstrated that DArT provides high quality markers that can be used for diversity analyses and to construct medium-density genetic linkage maps. The high number of DArT markers generated in a single assay not only provides a precise estimate of genetic relationships among genotypes, but also their even distribution over the genome offers real advantages for a range of molecular breeding and genomics applications.

Homologues of the maize rust resistance gene Rp1-D are genetically associated with a major rust resistance QTL in sorghum

As part of a comparative mapping study between sugarcane and sorghum, a sugarcane cDNA clone with homology to the maize Rp1-D rust resistance gene was mapped in sorghum. The cDNA probe hybridised to multiple loci, including one on sorghum linkage group (LG) E in a region where a major rust resistance QTL had been previously mapped. Partial sorghum Rp1-D homologues were isolated from genomic DNA of rust-resistant and -susceptible progeny selected from a sorghum mapping population. Sequencing of the Rp1-D homologues revealed five discrete sequence classes: three from resistant progeny and two from susceptible progeny. PCR primers specific to each sequence class were used to amplify products from the progeny and confirmed that the five sequence classes mapped to the same locus on LG E. Cluster analysis of these sorghum sequences and available sugarcane, maize and sorghum Rp1-D homologue sequences showed that the maize Rp1-D sequence and the partial sugarcane Rp1-D homologue were clustered with one of the sorghum resistant progeny sequence classes, while previously published sorghum Rp1-D homologue sequences clustered with the susceptible progeny sequence classes. Full-length sequence information was obtained for one member of a resistant progeny sequence class ( Rp1-SO) and compared with the maize Rp1-D sequence and a previously identified sorghum Rp1 homologue ( Rph1-2). There was considerable similarity between the two sorghum sequences and less similarity between the sorghum and maize sequences. These results suggest a conservation of function and gene sequence homology at the Rp1 loci of maize and sorghum and provide a basis for convenient PCR-based screening tools for putative rust resistance alleles in sorghum.

Assessing and reducing vulnerability to climate change: Moving from theory to practical decision-support

As climate change continues to impact socio-ecological systems, tools that assist conservation managers to understand vulnerability and target adaptations are essential. Quantitative assessments of vulnerability are rare because available frameworks are complex and lack guidance for dealing with data limitations and integrating across scales and disciplines. This paper describes a semi-quantitative method for assessing vulnerability to climate change that integrates socio-ecological factors to address management objectives and support decision-making. The method applies a framework first adopted by the Intergovernmental Panel on Climate Change and uses a structured 10-step process. The scores for each framework element are normalized and multiplied to produce a vulnerability score and then the assessed components are ranked from high to low vulnerability. Sensitivity analyses determine which indicators most influence the analysis and the resultant decision-making process so data quality for these indicators can be reviewed to increase robustness. Prioritisation of components for conservation considers other economic, social and cultural values with vulnerability rankings to target actions that reduce vulnerability to climate change by decreasing exposure or sensitivity and/or increasing adaptive capacity. This framework provides practical decision-support and has been applied to marine ecosystems and fisheries, with two case applications provided as examples: (1) food security in Pacific Island nations under climate-driven fish declines, and (2) fisheries in the Gulf of Carpentaria, northern Australia. The step-wise process outlined here is broadly applicable and can be undertaken with minimal resources using existing data, thereby having great potential to inform adaptive natural resource management in diverse locations.

Resistance of Brassicaceae plants to root-knot nematode (Meloidogyne spp.) in northern Australia

Brassicaceae plants have the potential as part of an integrated approach to replace fumigant nematicides, providing the biofumigation response following their incorporation is not offset by reproduction of plant-parasitic nematodes on their roots. Forty-three Brassicaceae cultivars were screened in a pot trial for their ability to reduce reproduction of three root-knot nematode isolates from north Queensland, Australia: M. arenaria (NQ1), M. javanica (NQ2) and M. arenaria race 2 (NQ5/7). No cultivar was found to consistently reduce nematode reproduction relative to forage sorghum, the current industry standard, although a commercial fodder radish (Raphanus sativus) and a white mustard (Sinapis alba) line were consistently as resistant to the formation of galls as forage sorghum. A second pot trial screened five commercially available Brassicaceae cultivars, selected for their biofumigation potential, for resistance to two nematode species, M. javanica (NQ2) and M. arenaria (NQ5/7). The fodder radish cv. Weedcheck, was found to be as resistant as forage sorghum to nematode reproduction. A multivariate cluster analysis using the resistance measurements, gall index, nematode number per g of root and multiplication for two nematode species (NQ2 and NQ5/7) confirmed the similarity in resistance between the radish cultivar and forage sorghum. A field trial confirmed the resistance of the fodder radish cv. Weedcheck, with a similar reduction in the number of Meloidogyne spp. juveniles recovered from the roots 8 weeks after planting. The use of fodder radish cultivars as biofumigation crops to manage root-knot nematodes in tropical vegetable production systems deserves further investigation.

Remote sensing of nitrogen and water stress in wheat

Nitrogen (N) is the largest agricultural input in many Australian cropping systems and applying the right amount of N in the right place at the right physiological stage is a significant challenge for wheat growers. Optimizing N uptake could reduce input costs and minimize potential off-site movement. Since N uptake is dependent on soil and plant water status, ideally, N should be applied only to areas within paddocks with sufficient plant available water. To quantify N and water stress, spectral and thermal crop stress detection methods were explored using hyperspectral, multispectral and thermal remote sensing data collected at a research field site in Victoria, Australia. Wheat was grown over two seasons with two levels of water inputs (rainfall/irrigation) and either four levels (in 2004; 0, 17, 39 and 163 kg/ha) or two levels (in 2005; 0 and 39 kg/ha N) of nitrogen. The Canopy Chlorophyll Content Index (CCCI) and modified Spectral Ratio planar index (mSRpi), two indices designed to measure canopy-level N, were calculated from canopy-level hyperspectral data in 2005. They accounted for 76% and 74% of the variability of crop N status, respectively, just prior to stem elongation (Zadoks 24). The Normalised Difference Red Edge (NDRE) index and CCCI, calculated from airborne multispectral imagery, accounted for 41% and 37% of variability in crop N status, respectively. Greater scatter in the airborne data was attributable to the difference in scale of the ground and aerial measurements (i.e., small area plant samples against whole-plot means from imagery). Nevertheless, the analysis demonstrated that canopy-level theory can be transferred to airborne data, which could ultimately be of more use to growers. Thermal imagery showed that mean plot temperatures of rainfed treatments were 2.7 °C warmer than irrigated treatments (P < 0.001) at full cover. For partially vegetated fields, the two-Dimensional Crop Water Stress Index (2D CWSI) was calculated using the Vegetation Index-Temperature (VIT) trapezoid method to reduce the contribution of soil background to image temperature. Results showed rainfed plots were consistently more stressed than irrigated plots. Future work is needed to improve the ability of the CCCI and VIT methods to detect N and water stress and apply both indices simultaneously at the paddock scale to test whether N can be targeted based on water status. Use of these technologies has significant potential for maximising the spatial and temporal efficiency of N applications for wheat growers. ‘Ground–breaking Stuff’- Proceedings of the 13th Australian Society of Agronomy Conference, 10-14 September 2006, Perth, Western Australia.

Mapping quantitative trait loci for resistance to Pratylenchus thornei from synthetic hexaploid wheat in the International Triticeae Mapping Initiative (ITMI) population

Root-lesion nematode (Pratylenchus thornei) is a serious pathogen of wheat in many countries. The International Triticeae Mapping Initiative (ITMI) population of recombinant inbred lines (RILs) was assessed for resistance to P. thornei to determine the chromosome locations of the resistance genes. The ITMI population is derived from a cross between the resistant synthetic hexaploid wheat W-7984 and a susceptible bread wheat cultivar Opata 85. Two years of phenotypic data for resistance to P. thornei were obtained in replicated glasshouse trials. Quantitative trait locus (QTL) analysis was performed using available segregation and map data for 114 RILs. A QTL on chromosome 6DS showed consistent effects for reduced nematode numbers (partial resistance) across years and accounted for 11% and 23% of the phenotypic variation. A second QTL for P. thornei resistance on chromosome 2BS accounted for an additional 19% and 5%. Restriction fragment length polymorphism (RFLP) and simple sequence repeat (SSR) markers associated with the QTLs are physically located in regions rich in major genes at the distal ends of the short chromosome arms of 6D and 2B. SSR markers with potential for marker-assisted selection of P. thornei resistance effective in different genetic backgrounds have been identified.

The climate change risk management matrix for the grazing industry of northern Australia

The complexity, variability and vastness of the northern Australian rangelands make it difficult to assess the risks associated with climate change. In this paper we present a methodology to help industry and primary producers assess risks associated with climate change and to assess the effectiveness of adaptation options in managing those risks. Our assessment involved three steps. Initially, the impacts and adaptation responses were documented in matrices by ‘experts’ (rangeland and climate scientists). Then, a modified risk management framework was used to develop risk management matrices that identified important impacts, areas of greatest vulnerability (combination of potential impact and adaptive capacity) and priority areas for action at the industry level. The process was easy to implement and useful for arranging and analysing large amounts of information (both complex and interacting). Lastly, regional extension officers (after minimal ‘climate literacy’ training) could build on existing knowledge provided here and implement the risk management process in workshops with rangeland land managers. Their participation is likely to identify relevant and robust adaptive responses that are most likely to be included in regional and property management decisions. The process developed here for the grazing industry could be modified and used in other industries and sectors. By 2030, some areas of northern Australia will experience more droughts and lower summer rainfall. This poses a serious threat to the rangelands. Although the impacts and adaptive responses will vary between ecological and geographic systems, climate change is expected to have noticeable detrimental effects: reduced pasture growth and surface water availability; increased competition from woody vegetation; decreased production per head (beef and wool) and gross margin; and adverse impacts on biodiversity. Further research and development is needed to identify the most vulnerable regions, and to inform policy in time to facilitate transitional change and enable land managers to implement those changes.

Multivariate analysis of fresh-cut carambola slices stored under different temperatures.

Quality of fresh-cut carambola (Averrhoa carambola L) is related to many chemical and biochemical variables especially those involved with softening and browning, both influenced by storage temperature. To study these effects, a multivariate analysis was used to evaluate slices packaged in vacuum-sealed polyolefin bags, and stored at 2.5 degrees C, 5 degrees C and 10 degrees C, for up to 16 d. The quality of slices at each temperature was correlated with the duration of storage, O(2) and CO(2) concentration in the package, physical chemical constituents, and activity of enzymes involved in softening (PG) and browning (PPO) metabolism. Three quality groups were identified by hierarchical cluster analysis, and the classification of the components within each of these groups was obtained from a principal component analysis (PCA). The characterization of samples by PCA clearly distinguished acceptable and non-acceptable slices. According to PCA, acceptable slices presented higher ascorbic acid content, greater hue angles ((o)h) and final lightness (L-5) in the first principal component (PC1). On the other hand, non-acceptable slices presented higher total pectin content. PPO activity in the PC1. Non-acceptable slices also presented higher soluble pectin content, increased pectin solubilisation and higher CO(2) concentration in the second principal component (PC2) whereas acceptable slices showed lower total sugar content. The hierarchical cluster and PCA analyses were useful for discriminating the quality of slices stored at different temperatures.

Recruitment sources of brown trout identified by otolith trace element signatures.

This study examined whether element: Ca ratios within the otoliths of juvenile brown trout could provide accurate trace element signatures for specific natal tributaries, and attempted to match these to trace element natal signatures found within the otoliths of adult trout caught in the main stem rivers of the same catchment. The trace element signatures of juvenile trout otoliths were analysed from a sample of eight tributaries representing the main sub-catchments of the Motueka River catchment, New Zealand. Trace element signatures were determined using laser ablation inductively coupled plasma mass spectrometry, and differentiated using linear discriminant function analysis with an overall cross-validated classification success of 96.8%. Temporal stability in element: Ca ratios was investigated by repeat collections of juvenile fish over two years. Natal signatures from 11 of 23 adult trout sampled from the catchment main stems were matched to one of the eight tributary signatures showing recruitment sources to be spread relatively evenly throughout the catchment. This study demonstrates the potential of using otolith trace element analysis to determine the natal origins of freshwater fish within a catchment.