Computational Methods for Locating and Analyzing Conserved Gene Regulatory DNA Elements

This thesis presents methods for locating and analyzing cis-regulatory DNA elements involved with the regulation of gene expression in multicellular organisms. The regulation of gene expression is carried out by the combined effort of several transcription factor proteins collectively binding the DNA on the cis-regulatory elements. Only sparse knowledge of the 'genetic code' of these elements exists today. An automatic tool for discovery of putative cis-regulatory elements could help their experimental analysis, which would result in a more detailed view of the cis-regulatory element structure and function. We have developed a computational model for the evolutionary conservation of cis-regulatory elements. The elements are modeled as evolutionarily conserved clusters of sequence-specific transcription factor binding sites. We give an efficient dynamic programming algorithm that locates the putative cis-regulatory elements and scores them according to the conservation model. A notable proportion of the high-scoring DNA sequences show transcriptional enhancer activity in transgenic mouse embryos. The conservation model includes four parameters whose optimal values are estimated with simulated annealing. With good parameter values the model discriminates well between the DNA sequences with evolutionarily conserved cis-regulatory elements and the DNA sequences that have evolved neutrally. In further inquiry, the set of highest scoring putative cis-regulatory elements were found to be sensitive to small variations in the parameter values. The statistical significance of the putative cis-regulatory elements is estimated with the Two Component Extreme Value Distribution. The p-values grade the conservation of the cis-regulatory elements above the neutral expectation. The parameter values for the distribution are estimated by simulating the neutral DNA evolution. The conservation of the transcription factor binding sites can be used in the upstream analysis of regulatory interactions. This approach may provide mechanistic insight to the transcription level data from, e.g., microarray experiments. Here we give a method to predict shared transcriptional regulators for a set of co-expressed genes. The EEL (Enhancer Element Locator) software implements the method for locating putative cis-regulatory elements. The software facilitates both interactive use and distributed batch processing. We have used it to analyze the non-coding regions around all human genes with respect to the orthologous regions in various other species including mouse. The data from these genome-wide analyzes is stored in a relational database which is used in the publicly available web services for upstream analysis and visualization of the putative cis-regulatory elements in the human genome.

Modeling Efficient Classification as a Process of Confidence Assessment and Delegation

In visual object detection and recognition, classifiers have two interesting characteristics: accuracy and speed. Accuracy depends on the complexity of the image features and classifier decision surfaces. Speed depends on the hardware and the computational effort required to use the features and decision surfaces. When attempts to increase accuracy lead to increases in complexity and effort, it is necessary to ask how much are we willing to pay for increased accuracy. For example, if increased computational effort implies quickly diminishing returns in accuracy, then those designing inexpensive surveillance applications cannot aim for maximum accuracy at any cost. It becomes necessary to find trade-offs between accuracy and effort. We study efficient classification of images depicting real-world objects and scenes. Classification is efficient when a classifier can be controlled so that the desired trade-off between accuracy and effort (speed) is achieved and unnecessary computations are avoided on a per input basis. A framework is proposed for understanding and modeling efficient classification of images. Classification is modeled as a tree-like process. In designing the framework, it is important to recognize what is essential and to avoid structures that are narrow in applicability. Earlier frameworks are lacking in this regard. The overall contribution is two-fold. First, the framework is presented, subjected to experiments, and shown to be satisfactory. Second, certain unconventional approaches are experimented with. This allows the separation of the essential from the conventional. To determine if the framework is satisfactory, three categories of questions are identified: trade-off optimization, classifier tree organization, and rules for delegation and confidence modeling. Questions and problems related to each category are addressed and empirical results are presented. For example, related to trade-off optimization, we address the problem of computational bottlenecks that limit the range of trade-offs. We also ask if accuracy versus effort trade-offs can be controlled after training. For another example, regarding classifier tree organization, we first consider the task of organizing a tree in a problem-specific manner. We then ask if problem-specific organization is necessary.

Mining Cell Transition Data

Cell transition data is obtained from a cellular phone that switches its current serving cell tower. The data consists of a sequence of transition events, which are pairs of cell identifiers and transition times. The focus of this thesis is applying data mining methods to such data, developing new algorithms, and extracting knowledge that will be a solid foundation on which to build location-aware applications. In addition to a thorough exploration of the features of the data, the tools and methods developed in this thesis provide solutions to three distinct research problems. First, we develop clustering algorithms that produce a reliable mapping between cell transitions and physical locations observed by users of mobile devices. The main clustering algorithm operates in online fashion, and we consider also a number of offline clustering methods for comparison. Second, we define the concept of significant locations, known as bases, and give an online algorithm for determining them. Finally, we consider the task of predicting the movement of the user, based on historical data. We develop a prediction algorithm that considers paths of movement in their entirety, instead of just the most recent movement history. All of the presented methods are evaluated with a significant body of real cell transition data, collected from about one hundred different individuals. The algorithms developed in this thesis are designed to be implemented on a mobile device, and require no extra hardware sensors or network infrastructure. By not relying on external services and keeping the user information as much as possible on the user s own personal device, we avoid privacy issues and let the users control the disclosure of their location information.

‘How to’ guide for measuring fan performance and efficiency in meat chicken sheds

This ‘how to’ guide provides readers with method to measure fan performance and energy efficiency of fans installed in meat chicken sheds. These methods are also useful for identifying fans that are under-performing or require maintenance. For more information about fan energy efficiency, a complementary report is available on the RIRDC website ‘Review of fan efficiency in meat chicken sheds’ (RIRDC Publication No. 15/018). A spreadsheet was also developed under this project for comparing and ranking fans against others in terms of energy efficiency, air flow and costs (‘Tunnel Ventilation Fan Comparison Spreadsheet’), and is available on the RIRDC website.

Strategies to limit the impact of nematode pressure on sugarcane productivity in the Isis

Two trials were done in this project. One was a continuation of work started under a previous GRDC/SRDC-funded activity, 'Strategies to improve the integration of legumes into cane based farming systems'. This trial aimed to assess the impact of trash and tillage management options and nematicide application on nematodes and crop performance. Methods and results are contained in the following publication: Halpin NV, Stirling GR, Rehbein WE, Quinn B, Jakins A, Ginns SP. The impact of trash and tillage management options and nematicide application on crop performance and plant-parasitic nematode populations in a sugarcane/peanut farming system. Proc. Aust. Soc. Sugar Cane Technol. 37, 192-203. Nematicide application in the plant crop significantly reduced total numbers of plant parasitic nematodes (PPN) but there was no impact on yield. Application of nematicide to the ratoon crop significantly reduced sugar yield. The study confirmed other work demonstrating that implementation of strategies like reduced tillage reduced populations of total PPN, suggesting that the soil was more suppressive to PPN in those treatments. The second trial, a variety trial, demonstrated the limited value of nematicide application in sugarcane farming systems. This study has highlighted that growers shouldn’t view nematicides as a ‘cure all’ for paddocks that have historically had high PPN numbers. Nematicides have high mammalian toxicity, have the potential to contaminate ground water (Kookana et al. 1995) and are costly. The cost of nematicide used in R1 was approx. $320 - $350/ha, adding $3.50/t of cane in a 100 t/ha crop. Also, our study demonstrated that a single nematicide treatment at the application rate registered for sugarcane is not very effective in reducing populations of nematode pests. There appears to be some levels of resistance to nematodes within the current suite of varieties available to the southern canelands. For example the soil in plots that were growing Q183 had 560% more root knot nematodes / 200mL soil compared to plots that grew Q245. The authors see great value in investment into a nematode screening program that could rate varieties into groups of susceptibility to both major sugarcane nematode pests. Such a rating could then be built into a decision support ‘tree’ or tool to better enable producers to select varieties on a paddock by paddock basis.

Physical Oceanographic Influences on Queensland Reef Fish and Scallops : Final Report FRDC 2013/020

The project examined coastal and physical oceanographic influences on the catch rates of coral trout (Plectropomus leopardus) and saucer scallops (Amusium balloti) in Queensland. The research was undertaken to explain variation observed in the catches, and to improve quantitative assessment of the stocks and management advice. 3.1 OBJECTIVES 1. Review recent advances in the study of physical oceanographic influences on fisheries catch data, and describe the major physical oceanographic features that are likely to influence Queensland reef fish and saucer scallops. 2. Collate Queensland’s physical oceanographic data and fisheries (i.e. reef fish and saucer scallops) data. 3. Develop stochastic population models for reef fish and saucer scallops, which can link physical oceanographic features (e.g. sea surface temperature anomalies) to catch rates, biological parameters (e.g. growth, reproduction, natural mortality) and ecological aspects (e.g. spatial distribution).

Priority list of endemic diseases for the red meat industries

This report provides a systematic review of the most economically damaging endemic diseases and conditions for the Australian red meat industry (cattle, sheep and goats). A number of diseases for cattle, sheep and goats have been identified and were prioritised according to their prevalence, distribution, risk factors and mitigation. The economic cost of each disease as a result of production losses, preventive costs and treatment costs is estimated at the herd and flock level, then extrapolated to a national basis using herd/flock demographics from the 2010-11 Agricultural Census by the Australian Bureau of Statistics. Information shortfalls and recommendations for further research are also specified. A total of 17 cattle, 23 sheep and nine goat diseases were prioritised based on feedback received from producer, government and industry surveys, followed by discussions between the consultants and MLA. Assumptions of disease distribution, in-herd/flock prevalence, impacts on mortality/production and costs for prevention and treatment were obtained from the literature where available. Where these data were not available, the consultants used their own expertise to estimate the relevant measures for each disease. Levels of confidence in the assumptions for each disease were estimated, and gaps in knowledge identified. The assumptions were analysed using a specialised Excel model that estimated the per animal, herd/flock and national costs of each important disease. The report was peer reviewed and workshopped by the consultants and experts selected by MLA before being finalised. Consequently, this report is an important resource that will guide and prioritise future research, development and extension activities by a variety of stakeholders in the red meat industry. This report completes Phase I and Phase II of an overall four-Phase project initiative by MLA, with identified data gaps in this report potentially being addressed within the later phases. Modelling the economic costs using a consistent approach for each disease ensures that the derived estimates are transparent and can be refined if improved data on prevalence becomes available. This means that the report will be an enduring resource for developing policies and strategies for the management of endemic diseases within the Australian red meat industry.

Chemical containment and eradication of screw− worm incursions in Australia

Screwworms are obligate, invasive parasites of warm-blooded animals. The female flies lay batches of eggs at the edge of wounds or other lesions. These eggs hatch to larvae or screw-worms which feed on affected animals for 6-7 days, burrowing deeply into subcutaneous tissues and causing severe trauma to animals, production loss and potentially death. Susceptible sites include wounds resulting from management practices such as castration, de-horning and ear tagging and lesions caused by the activities of other parasites such as buffalo flies and ticks. The navels of the new born and the vulval region of their mothers following parturition are highly susceptible and body orifices such as nose and ears are also frequent targets for ovipositing screwworm flies. The Old World screw-worm, Chrysomya bezziana (OWS) is considered one of the most serious exotic insect pest threatening Australia's livestock industries and is endemic in a number of our closest neighbouring countries. New World screwworm (NWS), Cochliomyia hominivorax, endemic to South America, has also entered Australia on at least 2 occasions. Many tropical and subtropical areas of Australia are suitable for the establishment of OWS and the potential range is expected to increase with climate change. The Australian screwworm preparedness strategy indicates a program of containment with chemical treatments followed by eradication of OWS using sterile male release and parasiticides. However, there is no longer an operational OWS sterile insect screw-worm facility anywhere in the world and establishing a large scale production facility would most optimistically take at least 2 years. In the interim, containment would be almost totally dependent on the availability of effective chemical controls. A review of chemical formulations available for potential use against OWS in Australia found that currently only one chemical, ivermectin administered by subcutaneous injection (s.c.) is registered for use against OWS and that many of the chemicals previously shown to be effective against OWS were no longer registered for animal use in Australia.18 From this review a number of Australian-registered chemicals were recommended as a priority for testing against OWS. The Australian Pesticides and Veterinary Medicines Authority (APVMA) can issue an emergency use permit for use of pesticides if they are registered in Australia for other animal uses and shown to be effective against OWS. This project tested the therapeutic and prophylactic efficacy of chemicals with potential for use in the treatment and control of OWS.

Climate savvy grazing (Developing improved grazing and related practices to assist beef production enterprises across northern Australia to adapt to a changing and more variable climate)

There is uncertainty over the potential changes to rainfall across northern Australia under climate change. Since rainfall is a key driver of pasture growth, cattle numbers and the resulting animal productivity and beef business profitability, the ability to anticipate possible management strategies within such uncertainty is crucial. The Climate Savvy Grazing project used existing research, expert knowledge and computer modelling to explore the best-bet management strategies within best, median and worse-case future climate scenarios. All three scenarios indicated changes to the environment and resources upon which the grazing industry of northern Australia depends. Well-adapted management strategies under a changing climate are very similar to best practice within current climatic conditions. Maintaining good land condition builds resource resilience, maximises opportunities under higher rainfall years and reduces the risk of degradation during drought and failed wet seasons. Matching stocking rate to the safe long-term carrying capacity of the land is essential; reducing stock numbers in response to poor seasons and conservatively increasing stock numbers in response to better seasons generally improves profitability and maintains land in good condition. Spelling over the summer growing season will improve land condition under a changing climate as it does under current conditions. Six regions were included within the project. Of these, the Victoria River District in the Northern Territory, Gulf country of Queensland and the Kimberley region of Western Australia had projections of similar or higher than current rainfall and the potential for carrying capacity to increase. The Alice Springs, Maranoa-Balonne and Fitzroy regions had projections of generally drying conditions and the greatest risk of reduced pasture growth and carrying capacity. Encouraging producers to consider and act on the risks, opportunities and management options inherent in climate change was a key goal of the project. More than 60,000 beef producers, advisors and stakeholders are now more aware of the management strategies which build resource resilience, and that resilience helps buffer against the effects of variable and changing climatic conditions. Over 700 producers have stated they have improved confidence, skills and knowledge to attempt new practices to build resilience. During the course of the project, more than 165 beef producers reported they have implemented changes to build resource and business resilience.

Review of productivity decline in sown grass pastures

Productivity decline in sown grass pastures is widespread in northern Australia and reduces production by approximately 50%, a farm gate cost to industry of > $17B over the next 30 years. Buffel grass is the most widely established sown species (>75% of plantings) and has been estimated to be “dominant” on 5.8 M hectares and “common” on a further 25.9 M hectares of Queensland. Legumes are the most cost effective mitigation option and can reclaim 30-50% of lost production. Commercial use of legumes has achieved mixed results with notable successes but many failures. There is significant opportunity to improve commercial results from legumes using existing technologies, however there is a need for targeted research to improve the reliability of establishment and productivity of legumes. This review recommends the grazing industry invest in targeted R,D&E to assist industry in improving production and sustainability of rundown pastures.

Fertilising for yield and quality in sown grass pastures and forage crops

Sown pasture rundown and declining soil fertility for forage crops are too serious to ignore with losses in beef production of up to 50% across Queensland. The feasibility of using strategic applications of nitrogen (N) fertiliser to address these losses was assessed by analysing a series of scenarios using data drawn from published studies, local fertiliser trials and expert opinion. While N fertilser can dramatically increase productivity (growth, feed quality and beef production gains of over 200% in some scenarios), the estimated economic benefits, derived from paddock level enterprise budgets for a fattening operation, were much more modest. In the best-performing sown grass scenarios, average gross margins were doubled or tripled at the assumed fertiliser response rates, and internal rates of return of up to 11% were achieved. Using fertiliser on forage sorghum or oats was a much less attractive option and, under the paddock level analysis and assumptions used, forages struggled to be profitable even on fertile sites with no fertiliser input. The economics of nitrogen fertilising on grass pasture were sensitive to the assumed response rates in both pasture growth and liveweight gain. Consequently, targeted research is proposed to re-assess the responses used in this analysis, which are largely based on research 25-40 years ago when soils were generally more fertile and pastures less rundown.

Use of phosphorus fertiliser for increased productivity of legume-based sown pastures in the Brigalow Belt region – a review

The Brigalow Belt bioregion of southern and central Queensland supports a large percentage of northern Australia's sown pastures and beef herd. The Brigalow soils were widely thought to have adequate phosphorus (P) for cropping, sown pastures and grazing animals, which has led to almost no use of P fertiliser on sown pastures. The majority of pastures established in the region were sown with tropical grasses only (i.e. no legumes were sown). Under grass-only pastures, nitrogen (N) mineralisation rates decline with time since establishment as N is 'tied-up' in soil organic matter. This process leads to a significant decline in pasture and animal productivity and is commonly called 'pasture rundown'. Incorporating pasture legumes has been identified as the best long-term solution to improve the productivity of rundown sown grass pastures. Pasture legumes require adequate P to grow well and fix large amounts of N to increase the productivity of rundown sown grass pastures. Producers and farm advisors have traditionally thought that P fertiliser is not cost-effective for legume-based improved pastures growing on inland areas of Queensland despite there being little, if any, data on production responses or their economic outcomes. Recent studies show large and increasing areas of low plant available soil P and large responses by pasture legumes to P fertiliser on Brigalow soils. The economic analysis in this scoping study indicates potential returns of 9–15% on extra funds invested from the application of P fertiliser, when establishing legumes into grass pastures on low P soils (i.e. lower than the critical P requirement of the legume grown). Higher returns of 12–24% may be possible when adding P fertiliser to already established grass/legume pastures on such soils. As these results suggest potential for significant returns from applying P fertiliser on legume pastures, it is recommended that research be conducted to better quantify the impacts of P fertiliser on productivity and profit. Research priorities include: quantifying the animal production and economic impact of fertilising legume-based pastures in the sub-tropics for currently used legumes; quantifying the comparative P requirements and responses of available legume varieties; understanding clay soil responses to applied P fertiliser; testing the P status of herds grazing in the Brigalow Belt; and quantifying the extent of other nutrient deficiencies (e.g. sulphur and potassium) for legume based pastures. Development and extension activities are required to demonstrate the commercial impacts of applying P fertiliser to legume based pastures.