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.

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.

Establishment of an Australian mild onion industry - the sensory component

In recent years, there has been increasing interest from growers, merchants, supermarkets and consumers in the establishment of a national mild onion industry. Imperative to the success of the emergent industry is the application of the National Mild Onion Certification Scheme that will establish standards and recommendations to be met by growers to allow them to declare their product as certified mild onions. The use of sensory evaluation techniques has played an imperative role throughout the project timeline that has also included varietal evaluation, evaluation of current agronomic practices and correlation of chemical analysis data. Raw onion consumer acceptance testing on five different onion varieties established preferences amongst the varieties for odour, appearance, flavour, texture and overall and differences in the level of pungency and aftertaste perceived. Demographic information was obtained regarding raw and cooked onion use, frequency of consumption and responses to the idea of a mild, less pungent onion. Additionally, focus groups were conducted to further investigate consumer attitudes to onions. Currently, a trained onion panel is being established to evaluate several odour, flavour and aftertaste attributes. Sample assessments will be conducted in January 2004 and correlated with chemical analyses that will hopefully provide the corner-stone for the anticipated Certification Scheme.

A high-density consensus map of barley linking DArT markers to SSR, RFLP and STS loci and agricultural traits

Background: Molecular marker technologies are undergoing a transition from largely serial assays measuring DNA fragment sizes to hybridization-based technologies with high multiplexing levels. Diversity Arrays Technology (DArT) is a hybridization-based technology that is increasingly being adopted by barley researchers. There is a need to integrate the information generated by DArT with previous data produced with gel-based marker technologies. The goal of this study was to build a high-density consensus linkage map from the combined datasets of ten populations, most of which were simultaneously typed with DArT and Simple Sequence Repeat (SSR), Restriction Enzyme Fragment Polymorphism (RFLP) and/or Sequence Tagged Site (STS) markers. Results: The consensus map, built using a combination of JoinMap 3.0 software and several purpose-built perl scripts, comprised 2,935 loci (2,085 DArT, 850 other loci) and spanned 1,161 cM. It contained a total of 1,629 'bins' (unique loci), with an average inter-bin distance of 0.7 ± 1.0 cM (median = 0.3 cM). More than 98% of the map could be covered with a single DArT assay. The arrangement of loci was very similar to, and almost as optimal as, the arrangement of loci in component maps built for individual populations. The locus order of a synthetic map derived from merging the component maps without considering the segregation data was only slightly inferior. The distribution of loci along chromosomes indicated centromeric suppression of recombination in all chromosomes except 5H. DArT markers appeared to have a moderate tendency toward hypomethylated, gene-rich regions in distal chromosome areas. On the average, 14 ± 9 DArT loci were identified within 5 cM on either side of SSR, RFLP or STS loci previously identified as linked to agricultural traits. Conclusion: Our barley consensus map provides a framework for transferring genetic information between different marker systems and for deploying DArT markers in molecular breeding schemes. The study also highlights the need for improved software for building consensus maps from high-density segregation data of multiple populations.

Laboratory information management software for genotyping workflows: Applications in high throughput crop genotyping

Background: With the advances in DNA sequencer-based technologies, it has become possible to automate several steps of the genotyping process leading to increased throughput. To efficiently handle the large amounts of genotypic data generated and help with quality control, there is a strong need for a software system that can help with the tracking of samples and capture and management of data at different steps of the process. Such systems, while serving to manage the workflow precisely, also encourage good laboratory practice by standardizing protocols, recording and annotating data from every step of the workflow Results: A laboratory information management system (LIMS) has been designed and implemented at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) that meets the requirements of a moderately high throughput molecular genotyping facility. The application is designed as modules and is simple to learn and use. The application leads the user through each step of the process from starting an experiment to the storing of output data from the genotype detection step with auto-binning of alleles; thus ensuring that every DNA sample is handled in an identical manner and all the necessary data are captured. The application keeps track of DNA samples and generated data. Data entry into the system is through the use of forms for file uploads. The LIMS provides functions to trace back to the electrophoresis gel files or sample source for any genotypic data and for repeating experiments. The LIMS is being presently used for the capture of high throughput SSR (simple-sequence repeat) genotyping data from the legume (chickpea, groundnut and pigeonpea) and cereal (sorghum and millets) crops of importance in the semi-arid tropics. Conclusions: A laboratory information management system is available that has been found useful in the management of microsatellite genotype data in a moderately high throughput genotyping laboratory. The application with source code is freely available for academic users and can be downloaded from http://www.icrisat.org/bt-software-d-lims.htm

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

Maximising the contribution of native-range studies towards the identification and prioritisation of weed biocontrol agents

Effective study in the native range to identify potential agents underpins all efforts in classical biological control of weeds. Good agents that demonstrate both a high degree of host specificity and the potential to be damaging are a very limited resource and must therefore be carefully studied and considered. The overseas component is often operationally difficult and expensive but can contribute considerably more than a list of herbivores attacking a particular target. While the principles underlying this foreign component have been understood for some time, recently developed technologies and methods can make very significant contributions to foreign studies. Molecular and genetic characterisations of both target weed and agent organism can be increasingly employed to more accurately define the identity and phylogeny of them. Climate matching and modelling software is now available and can be utilised to better select agents for particular regions of concern. Relational databases can store collection information for analysis and future enquiry while quantification of sampling effort, employment of statistical survey methods and analysis by techniques such as rarefaction curves contribute to efficient and effective searching. Obtaining good and timely identifications for discovered agent organisms is perhaps the most serious issue confronting the modern explorer. The diminishing numbers of specialist taxonomists employed at the major museums while international and national protocols demand higher standards of identity exacerbates the issue. Genetic barcoding may provide a very useful tool to overcome this problem. Native-range work also offers under-exploited opportunities for contributing towards predicting safety, abundance and efficacy of potential agents in their target environment.

Best use modelling for sustainable Australia sports field surfaces

The Best Use Modelling for Sustainable Australian Sports Field Surfaces project has achieved significant success. The project has attracted participation from councils throughout Australia, with in excess of 300 sports fields evaluated from 18 councils to date. An important project component is the derivation of a recommended standard procedure for specifying the performance of playing surfaces. An associated step has been to establish recommended playing surface performance standards for community level sports fields. The derived modelling also provides information on the expected usage and associated costs of different sports surface development options. This is expected to assist the Australian turf production industry through demonstrating to councils that cost effective natural turf options exist that can meet higher usage expectation (as a viable alternative to synthetic turf). A web-accessed data base system will be made available to councils from January 2010 on (reference to www.passturf.com). This system will enable participating councils to record and analyse field performance over time. The system is considered world-leading, and will help keep the Australian parks industry to the international forefront. Tools developed as part of the project offer councils the opportunity to internally assess the performance of their current sports field provision, to identify any deficiencies and to determine the best corrective measure if any deficiency is identified. This is expected to offer community benefits to both sports facility providers and facility user groups. In turn this will aid the provision of affordable community access to safe and good quality playing surfaces. Tools and associated information material will be made available to councils throughout Australia by the end of this year, via the Parks and Leisure Aust. web site. The Best Use Modelling Project is work in progress. On-going input will be needed to ensure the web-accessed database software is as user friendly as possible, new performance testing data will need to be inputted, and tools provided to participating councils updated. Through the support of HAL there is now a well-structured, nationally-supported system in place for benchmarking playing surfaces and for assisting councils to optimise their resource allocation to sports field upgrade or maintenance work.

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.

MT10049 Pheromone component of a multi target approach to fruitspotting bug management

A pheromone-based trapping system will be developed for both A. lutescens and A. nitida to improve insecticide timing and to rationalise use.

A Paddock to reef monitoring and modelling framework for the Great Barrier Reef: Paddock and catchment component

Targets for improvements in water quality entering the Great Barrier Reef (GBR) have been set through the Reef Water Quality Protection Plan (Reef Plan). To measure and report on progress towards the targets set a program has been established that combines monitoring and modelling at paddock through to catchment and reef scales; the Paddock to Reef Integrated Monitoring, Modelling and Reporting Program (Paddock to Reef Program). This program aims to provide evidence of links between land management activities, water quality and reef health. Five lines of evidence are used: the effectiveness of management practices to improve water quality; the prevalence of management practice adoption and change in catchment indicators; long-term monitoring of catchment water quality; paddock & catchment modelling to provide a relative assessment of progress towards meeting targets; and finally marine monitoring of GBR water quality and reef ecosystem health. This paper outlines the first four lines of evidence. (C) 2011 Elsevier Ltd. All rights reserved.

NEESTIMATOR v2: re-implementation of software for the estimation of contemporary effective population size (N-e) from genetic data

NeEstimator v2 is a completely revised and updated implementation of software that produces estimates of contemporary effective population size, using several different methods and a single input file. NeEstimator v2 includes three single-sample estimators (updated versions of the linkage disequilibrium and heterozygote-excess methods, and a new method based on molecular coancestry), as well as the two-sample (moment-based temporal) method. New features include the following: (i) an improved method for accounting for missing data; (ii) options for screening out rare alleles; (iii) confidence intervals for all methods; (iv) the ability to analyse data sets with large numbers of genetic markers (10000 or more); (v) options for batch processing large numbers of different data sets, which will facilitate cross-method comparisons using simulated data; and (vi) correction for temporal estimates when individuals sampled are not removed from the population (Plan I sampling). The user is given considerable control over input data and composition, and format of output files. The freely available software has a new JAVA interface and runs under MacOS, Linux and Windows.

Is Mycoplasma bovis a missing component of the bovine respiratory disease complex in Australia?

Background: Bovine respiratory disease complex (BRDC) is a multi-factorial disease in which numerous factors, such as animal management, pathogen exposure and environmental conditions, contribute to the development of acute respiratory illness in feedlot cattle. The role of specific pathogens in the development of BRDC has been difficult to define because of the complex nature of the disease and the presence of implicated bacterial pathogens in the upper respiratory tract of healthy animals. Mycoplasma bovis is an important pathogen of cattle and recognised as a major contributor to cases of mastitis, caseonecrotic bronchopneumonia, arthritis and otitis media. To date, the role of M.bovis in the development of BRDC of Australian feeder cattle has not been investigated. Methods: In this review, the current literature pertaining to the role of M.bovis in BRDC is evaluated. In addition, preliminary data are presented that identify M.bovis as a potential contributor to BRDC in Australian feedlots, which has not been considered previously. Results and Conclusion: The preliminary results demonstrate detection of M.bovis in samples from all feedlots studied. When considered in the context of the reviewed literature, they support the inclusion of M.bovis on the list of pathogens to be considered during investigations into BRDC in Australia. © 2014 Australian Veterinary Association.

Integrating pest population models with biophysical crop models to better represent the farming system

Farming systems frameworks such as the Agricultural Production Systems simulator (APSIM) represent fluxes through the soil, plant and atmosphere of the system well, but do not generally consider the biotic constraints that function within the system. We designed a method that allowed population models built in DYMEX to interact with APSIM. The simulator engine component of the DYMEX population-modelling platform was wrapped within an APSIM module allowing it to get and set variable values in other APSIM models running in the simulation. A rust model developed in DYMEX is used to demonstrate how the developing rust population reduces the crop's green leaf area. The success of the linking process is seen in the interaction of the two models and how changes in rust population on the crop's leaves feedback to the APSIM crop modifying the growth and development of the crop's leaf area. This linking of population models to simulate pest populations and biophysical models to simulate crop growth and development increases the complexity of the simulation, but provides a tool to investigate biotic constraints within farming systems and further moves APSIM towards being an agro-ecological framework.