Agency: GTR | Branch: BBSRC | Program: | Phase: Research Grant | Award Amount: 156.22K | Year: 2016
Septoria tritici blotch (STB) of wheat is the most economically important disease affecting wheat production in Northern Europe. STB is controlled using a combination of agronomy, genetic resistance and fungicides however, selection and subsequent adaptation of the underlying pathogen populations can lead to breakdowns in host resistance and resistance to chemical controls. As the pathogen adapts we will need to understand the composition of the pest population (or pathotypes) to be able to describe specific differences between members of the same species and how these differences affect the range of wheat varieties affected by STB. An effective and cost-efficient solution for STB will directly depend on our understanding of the underlying pathogen (Zymoseptoria tritici). The use of advanced sequencing technologies has the potential to quickly and efficiently screen many individual pathogen isolates, providing a wealth of information at a low cost. This type of approach has already been demonstrated to be a powerful tool in yellow rust of wheat. However, the cost of purchasing machinery required to conduct sequencing is often prohibitive and runs can take between 24-48 hours to complete. There are also requirements for high-powered computing facilities and experienced operators to conduct the relevant analyses to arrange sequencing data in to a practical format. NanoPath will employ the MinION sequencer from Oxford Nanopore Technologies as a surveillance tool to improve the speed and ease at which researchers can identify and survey new pests in the field. This will first assess the utility of the MinION and help to develop a model and computational platform to apply nanopore sequencing to a wider range of crop pathogens. The MinION device is portable and able to generate sequencing data following a relatively easy-to-use process. We also propose to implement a data analysis pipeline that will make use of a number of open-source primary data software tools optimised for the discovery and characterisation of genetic variants this crop pathogen.
Agency: GTR | Branch: BBSRC | Program: | Phase: Research Grant | Award Amount: 571.88K | Year: 2015
Despite its importance and growing demand within the UK, and globally, the rate of increase in wheat yields on UK farms have stagnated. To meet global future demand, annual wheat yield increases must grow to at least 1.4% and increasing the rate of genetic improvement using modern approaches is one way to do this. The ability to record vast quantities of genetic and phenotypic information cheaply (e.g. genetic markers and spectral images of field trials - termed in this proposal as Genomics and Phenomics) presents a new opportunity for increasing the rate of genetic improvement. The rate of genetic improvement is affected by (1) the accuracy of selection, (2) breeding cycle time, (3) selection intensity, and (4) the amount of genetic diversity to be selected upon. In the medium to long term, concerns about genetic diversity are being addressed through national and international projects to introgress traits and alleles from landraces and progenitor species. However, the major barrier to the immediate increase in the rate of genetic improvement in wheat is the length of the breeding cycle time. Even at their fastest wheat breeding programs require at least four to six seasons to complete a cycle, principally due to the time required to reduce the number of individuals for selection to a subset that can be intensively phenotyped. Genomic selection (GS) is a new breeding tool that, amongst other advantages, can dramatically reduce breeding cycle time as selection can occur without the need to record phenotypes. In wheat this means breeding cycle time could be reduced to one season, dramatically increasing the rate of genetic improvement. In the extreme, using glasshouses to complete 2 cycles of selection per year, 10 cycles could be undertaken in the 5-year time frame currently taken for a single selection cycle. GS uses a training population that is phenotyped and genotyped to construct a prediction equation. This equation is used to predict the breeding values of unphenotyped individuals, which, in wheat, would allow reduction of the breeding cycle to one season. GS assumes that saturating the genome of all individuals with molecular markers and estimating the effect of these markers (i.e. training the prediction equation) will allow capture of a large proportion of the genetic variation caused by the underlying quantitative trait loci. If the proportion of the captured genetic variation is large and well estimated the prediction equation will be able to make accurate predictions about breeding values. Similarly, in Phenomics the phenotype could be saturated with descriptors, which could lead to a better separation of its environmental and genetic components as well as generating more precise phenotypes. Creation of training populations is a required investment for GS and strategic use of resources to achieve the required size is needed to optimize the cost and benefit of GS. Use of a genotyping and imputation strategy is paramount for reducing costs. Field trials are also costly. Use of novel high-dimensional approaches for capturing extra traits and variables (Phenomics) could enhance the value of field trials generally, as well as enabling more powerful GS. This proposal will use field trials and simulation to design and evaluate Genomics and Phenomics strategies for increasing rates of genetic improvement in wheat. This will include GS training population designs and low cost collection of genotype data, assessment of the properties of high-dimensional environmental descriptors and quantification of their power, assessment of the properties of trait phenotypes collected by high-dimensional data recording devices and quantification of their relationships to standard traits. Results will be generalised to other species with breeding programs similar to those of wheat as well as to other type of experiments and field trials (e.g. National List evaluations).
Agency: GTR | Branch: BBSRC | Program: | Phase: Research Grant | Award Amount: 431.75K | Year: 2016
We propose to develop a modern platform for rice breeding in Vietnam focused on traits of agronomic interest. Rice is a staple food for a population of 90 million in Vietnam and it is also one of the main exporter commodities of the country. Vietnam is experiencing an exceptional growth in its economic output and population rising as a global leading agricultural country. There is, however, an increasing threat from climate change such as emerging pathogens, periods of droughts and rising sea levels. The areas under greatest risk are the deltas of the Red and Mekong rivers, which represent the major rice growing regions of Vietnam. The rapid selection of rice varieties that are tolerant and resilient to these conditions will help to mitigate some of these challenges and contribute to ensure food security in Vietnam. The Genome Analysis Centre (TGAC) in the UK and the Agricultural Genetics Institute (AGI) in Vietnam initiated a collaboration to sequence the genome of a reduced number of Vietnamese rice varieties with the purpose to characterise the genetic variations in native lines and develop molecular markers that could be used to accelerate rice breeding. The application of new genomics technologies to improve crop breeding is one of the priorities at the National Institute of Agricultural Botany (NIAB) at UK. The proposed project continues the partnership initiated between TGAC and AGI as a collaboration with NIAB. We aim at expanding the pilot project phase I to complete the re-sequencing of around 600 lines. We will complement the generation of these data with the development of databases and the application of bioinformatics pipelines to identify associations of alleles with specific phenotypes. We expect to characterise markers that will enable more efficient rice breeding. The application of modern technologies to rice breeding will also provide an excellent example of how these strategies could be applied to other plant species such as wheat and barley. Rice has a simple genome for which many genomics resources have been already generated and it offers an excellent model for the evaluation and assessment of new strategies for breeding that could later be applied to more complex crops. This collaboration with Vietnam will also open opportunities to work with world leading scientists with experience in rice breeding and agronomy.
Agency: Cordis | Branch: FP7 | Program: ERC-AG | Phase: ERC-AG-SH6 | Award Amount: 2.49M | Year: 2014
This project explores the concept of agricultural spread as analogous to enforced climate change and asks how cereals adapted to new environments when agriculture was introduced into Europe. Archaeologists have long recognized that the ecological pressures placed on crops would have had an impact on the spread and subsequent development of agriculture, but previously there has been no means of directly assessing the scale and nature of this impact. Recent work that I have directed has shown how such a study could be carried out, and the purpose of this project is to exploit these breakthroughs with the goal of assessing the influence of environmental adaptation on the spread of agriculture, its adoption as the primary subsistence strategy, and the subsequent establishment of farming in different parts of Europe. This will correct the current imbalance between our understanding of the human and environmental dimensions to the domestication of Europe. I will use methods from population genomics to identify loci within the barley and wheat genomes that have undergone selection since the beginning of cereal cultivation in Europe. I will then use ecological modelling to identify those loci whose patterns of selection are associated with ecogeographical variables and hence represent adaptations to local environmental conditions. I will assign dates to the periods when adaptations occurred by sequencing ancient DNA from archaeobotanical assemblages and by computer methods that enable the temporal order of adaptations to be deduced. I will then synthesise the information on environmental adaptations with dating evidence for the spread of agriculture in Europe, which reveals pauses that might be linked to environmental adaptation, with demographic data that indicate regions where Neolithic populations declined, possibly due to inadequate crop productivity, and with an archaeobotanical database showing changes in the prevalence of individual cereals in different regions.
Agency: GTR | Branch: BBSRC | Program: | Phase: Research Grant | Award Amount: 1.34M | Year: 2016
Optimising biological nitrogen (N) use is pivotal to maximizing crop yields and ameliorating the adverse environmental impacts of excess agricultural N application. New opportunity exists to provide solutions to cereal crop N use via the translation of basic research into application. The Cambridge-India Network for Translational Research in N (CINTRIN) will establish a complete but flexible pipeline connecting developmental research, crop breeding, agritechnology and extension. The framework of CINTRIN will be provided by the University of Cambridge, NIAB and ADAS, together with ICRISAT, Punjab Agricultural University, NIPGR and the technology companies KisanHub (SME) and BenchBio (SME). The framework partners are widely connected, opening many opportunitites to expand and extend the VJC in future. CINTRIN will provide innovative approaches to tackle crop biological N use. Firstly, it will promote a new understanding of the underpinning science associated with optimization of crop N use, built on an exciting new discovery of distinct life history strategies for N use in the model plant Arabidopsis thaliana. This work has identified N sensitive (NS) and N insensitive (NIS) types which vary fundamentally in their developmental response to N. This work indicates that the ability to protect seed yield under low N supply appears to come at the expense of the ability to exploit high N supply effectively. This model for developmental N use has the potential to revolutionise the way we think about the N requirements and uses of crops. Within CINTRIN, a translational pipeline will couple the molecular basis of plant development to the physiology of N uptake and partitioning. Through advanced genomics and pre-breeding, new N ideotypes will be defined in crops important for the UK (wheat) and India (wheat, sorghum, pearl and foxtail millet). Field observations and data- driven methods of technology transfer will allow dissemination of the results and ultimately advice on cultivar-specific fertiliser N application to be offered directly to farmers. Secondly, the exchanges in personnel between India and the UK via CINTRIN will enhance the skills of the next generation of plant technologists and provide an exemplar for building capacity in fundamental plant sciences and translation into germplasm and agronomic outputs in both the UK and India. Thirdly, CINTRIN will build on the enterprise and spin-out capacity associated with existing Cambridge and India SME alliances, whereby knowledge can be harnessed by industry to develop wealth and employment in the agri-tech sector. Overall, the vision for CINTRIN is that networks of applied expertise will feed-forward from advances in developmental biology, through to genomics-led pre-breeding of cereal crop staples with optimal biological N use. The JVC will assimilate feedback from CINTRIN translational and outreach activities which relate to sustainable intensification and yield resilience, particularly via farmer networks in the UK and India. In the UK this will be linked to the Defra Sustainable Intensification Platform (SIP; NIAB leads Project 1, investigating Integrated Farm Management for improved economic, environmental and social performance with a group of 30 partners spanning universities, research institutes, farming industry and environmental organisations). CINTRIN will deliver a translational pipeline to produce new ideotypes for optimized N use in agriculture. It will provide training in developmental research, and new knowledge relevant to underpinning optimal biological N use for sustainable intensification. It will promote excellence in science in both the UK and India and provide innovation for application in commercial farming activities.