Construction of microsatellite linkage maps for Corymbia

The genus Corymbia is closely related to the genus Eucalyptus, and like Eucalyptus contains tree species that are important for sub-tropical forestry. Corymbia's close relationship with Eucalyptus suggests genetic studies in Corymbia should benefit from transfer of genetic information from its more intensively studied relatives. Here we report a genetic map for Corymbia spp. based on microsatellite markers identified de novo in Corymbia sp or transferred from Eucalyptus. A framework consensus map was generated from an outbred F 2 population (n = 90) created by crossing two unrelated Corymbia torelliana x C. citriodora subsp. variegata F1 trees. The map had a total length of 367 cM (Kosambi) and was composed of 46 microsatellite markers distributed across 13 linkage groups (LOD 3). A high proportion of Eucalyptus microsatellites (90%) transferred to Corymbia. Comparative analysis between the Corymbia map and a published Eucalyptus map identified eight homeologous linkage groups in Corymbia with 13 markers mapping on one or both maps. Further comparative analysis was limited by low power to detect linkage due to low genome coverage in Corymbia, however, there was no convincing evidence for chromosomal structural differences because instances of non-synteny were associated with large distances on the Eucalyptus map. Segregation distortion was primarily restricted to a single linkage group and due to a deficit of hybrid genotypes, suggesting that hybrid inviability was one factor shaping the genetic composition of the F2 population in this inter-subgeneric hybrid. The conservation of microsatellite loci and synteny between Corymbia and Eucalyptus suggests there will be substantial value in exchanging information between the two groups.

How accurate are the marker orders in crop linkage maps generated from large marker datasets?

Marker ordering during linkage map construction is a critical component of QTL mapping research. In recent years, high-throughput genotyping methods have become widely used, and these methods may generate hundreds of markers for a single mapping population. This poses problems for linkage analysis software because the number of possible marker orders increases exponentially as the number of markers increases. In this paper, we tested the accuracy of linkage analyses on simulated recombinant inbred line data using the commonly used Map Manager QTX (Manly et al. 2001: Mammalian Genome 12, 930-932) software and RECORD (Van Os et al. 2005: Theoretical and Applied Genetics 112, 30-40). Accuracy was measured by calculating two scores: % correct marker positions, and a novel, weighted rank-based score derived from the sum of absolute values of true minus observed marker ranks divided by the total number of markers. The accuracy of maps generated using Map Manager QTX was considerably lower than those generated using RECORD. Differences in linkage maps were often observed when marker ordering was performed several times using the identical dataset. In order to test the effect of reducing marker numbers on the stability of marker order, we pruned marker datasets focusing on regions consisting of tightly linked clusters of markers, which included redundant markers. Marker pruning improved the accuracy and stability of linkage maps because a single unambiguous marker order was produced that was consistent across replications of analysis. Marker pruning was also applied to a real barley mapping population and QTL analysis was performed using different map versions produced by the different programs. While some QTLs were identified with both map versions, there were large differences in QTL mapping results. Differences included maximum LOD and R-2 values at QTL peaks and map positions, thus highlighting the importance of marker order for QTL mapping

A consensus genetic map of sorghum that integrates multiple component maps and high-throughput Diversity Array Technology (DArT) markers

Background: Sorghum genome mapping based on DNA markers began in the early 1990s and numerous genetic linkage maps of sorghum have been published in the last decade, based initially on RFLP markers with more recent maps including AFLPs and SSRs and very recently, Diversity Array Technology (DArT) markers. It is essential to integrate the rapidly growing body of genetic linkage data produced through DArT with the multiple genetic linkage maps for sorghum generated through other marker technologies. Here, we report on the colinearity of six independent sorghum component maps and on the integration of these component maps into a single reference resource that contains commonly utilized SSRs, AFLPs, and high-throughput DArT markers. Results: The six component maps were constructed using the MultiPoint software. The lengths of the resulting maps varied between 910 and 1528 cM. The order of the 498 markers that segregated in more than one population was highly consistent between the six individual mapping data sets. The framework consensus map was constructed using a "Neighbours" approach and contained 251 integrated bridge markers on the 10 sorghum chromosomes spanning 1355.4 cM with an average density of one marker every 5.4 cM, and were used for the projection of the remaining markers. In total, the sorghum consensus map consisted of a total of 1997 markers mapped to 2029 unique loci ( 1190 DArT loci and 839 other loci) spanning 1603.5 cM and with an average marker density of 1 marker/0.79 cM. In addition, 35 multicopy markers were identified. On average, each chromosome on the consensus map contained 203 markers of which 58.6% were DArT markers. Non-random patterns of DNA marker distribution were observed, with some clear marker-dense regions and some marker-rare regions. Conclusion: The final consensus map has allowed us to map a larger number of markers than possible in any individual map, to obtain a more complete coverage of the sorghum genome and to fill a number of gaps on individual maps. In addition to overall general consistency of marker order across individual component maps, good agreement in overall distances between common marker pairs across the component maps used in this study was determined, using a difference ratio calculation. The obtained consensus map can be used as a reference resource for genetic studies in different genetic backgrounds, in addition to providing a framework for transferring genetic information between different marker technologies and for integrating DArT markers with other genomic resources. DArT markers represent an affordable, high throughput marker system with great utility in molecular breeding programs, especially in crops such as sorghum where SNP arrays are not publicly available.

Driving better vegetable irrigation through profitable practice change

The availability and quality of irrigation water has become an issue limiting productivity in many Australian vegetable regions. Production is also under competitive pressure from supply chain forces. Producers look to new technologies, including changing irrigation infrastructure, exploring new water sources, and more complex irrigation management, to survive these stresses. Often there is little objective information investigating which improvements could improve outcomes for vegetable producers, and external communities (e.g. meeting NRM targets). This has led to investment in inappropriate technologies, and costly repetition of errors, as business independently discover the worth of technologies by personal experience. In our project, we investigated technology improvements for vegetable irrigation. Through engagement with industry and other researchers, we identified technologies most applicable to growers, particularly those that addressed priority issues. We developed analytical tools for ‘what if’ scenario testing of technologies. We conducted nine detailed experiments in the Lockyer Valley and Riverina vegetable growing districts, as well as case studies on grower properties in southern Queensland. We investigated root zone monitoring tools (FullStop™ wetting front detectors and Soil Solution Extraction Tubes - SSET), drip system layout, fertigation equipment, and altering planting arrangements. Our project team developed and validated models for broccoli, sweet corn, green beans and lettuce, and spreadsheets for evaluating economic risks associated with new technologies. We presented project outcomes at over 100 extension events, including irrigation showcases, conferences, field days, farm walks and workshops. The FullStops™ were excellent for monitoring root zone conditions (EC, nitrate levels), and managing irrigation with poor quality water. They were easier to interpret than the SSET. The SSET were simpler to install, but required wet soil to be reliable. SSET were an option for monitoring deeper soil zones, unsuitable for FullStop™ installations. Because these root zone tools require expertise, and are labour intensive, we recommend they be used to address specific problems, or as a periodic auditing strategy, not for routine monitoring. In our research, we routinely found high residual N in horticultural soils, with subsequently little crop yield response to additional nitrogen fertiliser. With improved irrigation efficiency (and less leaching), it may be timely to re-examine nitrogen budgets and recommendations for vegetable crops. Where the drip irrigation tube was located close to the crop row (i.e. within 5-8 cm), management of irrigation was easier. It improved nitrogen uptake, water use efficiency, and reduced the risk of poor crop performance through moisture stress, particularly in the early crop establishment phases. Close proximity of the drip tube to the crop row gives the producer more options for managing salty water, and more flexibility in taking risks with forecast rain. In many vegetable crops, proximate drip systems may not be cost-effective. The next best alternative is to push crop rows closer to the drip tube (leading to an asymmetric row structure). The vegetable crop models are good at predicting crop phenology (development stages, time to harvest), input use (water, fertiliser), environmental impacts (nutrient, salt movement) and total yields. The two immediate applications for the models are understanding/predicting/manipulating harvest dates and nitrogen movements in vegetable cropping systems. From the economic tools, the major influences on accumulated profit are price and yield. In doing ‘what if’ analyses, it is very important to be as accurate as possible in ascertaining what the assumed yield and price ranges are. In most vegetable production systems, lowering the required inputs (e.g. irrigation requirement, fertiliser requirement) is unlikely to have a major influence on accumulated profit. However, if a resource is constraining (e.g. available irrigation water), it is usually most profitable to maximise return per unit of that resource.

Potential Animal and Environmental Sources of Q Fever Infection for Humans in Queensland

Q fever is a vaccine-preventable disease; despite this, high annual notification numbers are still recorded in Australia. We have previously shown seroprevalence in Queensland metropolitan regions is approaching that of rural areas. This study investigated the presence of nucleic acid from Coxiella burnetii, the agent responsible for Q fever, in a number of animal and environmental samples collected throughout Queensland, to identify potential sources of human infection. Samples were collected from 129 geographical locations and included urine, faeces and whole blood from 22 different animal species; 45 ticks were removed from two species, canines and possums; 151 soil samples; 72 atmospheric dust samples collected from two locations and 50 dust swabs collected from domestic vacuum cleaners. PCR testing was performed targeting the IS1111 and COM1 genes for the specific detection of C.burnetii DNA. There were 85 detections from 1318 animal samples, giving a detection rate for each sample type ranging from 2.1 to 6.8%. Equine samples produced a detection rate of 11.9%, whilst feline and canine samples showed detection rates of 7.8% and 5.2%, respectively. Native animals had varying detection rates: pooled urines from flying foxes had 7.8%, whilst koalas had 5.1%, and 6.7% of ticks screened were positive. The soil and dust samples showed the presence of C.burnetii DNA ranging from 2.0 to 6.9%, respectively. These data show that specimens from a variety of animal species and the general environment provide a number of potential sources for C.burnetii infections of humans living in Queensland. These previously unrecognized sources may account for the high seroprevalence rates seen in putative low-risk communities, including Q fever patients with no direct animal contact and those subjects living in a low-risk urban environment.