• Canada
• 2013-2022close
• UK Research and Innovation close
• UKRI|BBSRC close
• 2014 close

Oil crops are one of the most important agricultural commodities. In the U.K. (and Northern Europe and Canada) oilseed rape is the dominant oil crop and worldwide it accounts for about 12% of the total oil and fat production. There is an increasing demand for plant oils not only for human food and animal feed but also as renewable sources of chemicals and biofuels. This increased demand has shown a doubling every 8 years over the last four decades and is likely to continue at, at least, this rate in the future. With a limitation on agricultural land, the main way to increase production is to increase yields. This can be achieved by conventional breeding but, in the future, significant enhancements will need genetic manipulation. The latter technique will also allow specific modification of the oil product to be achieved. In order for informed genetic manipulation to take place, a thorough knowledge of the biosynthesis of plant oils is needed. Crucially, this would include how regulation of oil quality and quantity is controlled. The synthesis of storage oil in plant seeds is analogous to a factory production line, where the supply of raw materials, manufacture of components and final assembly can all potentially limit the rate of production. Recently, we made a first experimental study of overall regulation of storage oil accumulation in oilseed rape, which we analysed by a mathematical method called flux control analysis. This showed that it is the final assembly that is the most important limitation on the biosynthetic process. The assembly process requires several enzyme steps and we have already highlighted one of these, diacylglycerol acyltransferase (DGAT), as being a significant controlling factor. We now wish to examine enzymes, other than DGAT, involved in storage lipid assembly and in supply of component parts. This will enable us to quantify the limitations imposed by different enzymes of the pathway and, furthermore, will provide information to underpin logical steps in genetic manipulation leading to plants with increased oil synthesis and storage capabilities. We will use rape plants where the activity of individual enzymes in the biosynthetic pathway have been changed and quantify the effects on overall oil accumulation. To begin with we will use existing transgenic oilseed rape, with increased enzyme levels, where increases in oil yields have been noted; these are available from our collaborators (Canada, Germany). For enzymes where there are no current transgenic plants available, we will make these and carry out similar analyses. Although our primary focus is on enzymes that increase oil yields, we will also examine the contribution the enzyme phospholipid: diacylglycerol acyltransferase (PDAT) makes to lipid production because this enzyme controls the accumulation of unsaturated oil, which has important dietary implications. In the analogous model plant Arabidopsis, PDAT and DGAT are both important during oil production. Once we have assembled data from these transgenic plants we will have a much better idea of the control of lipid production in oilseed rape. Our quantitative measurements will provide specific targets for future crop improvements. In addition, because we will be monitoring oil yields as well as flux control we will be able to correlate these two measures. Moreover, plants manipulated with multiple genes (gene stacking) will reveal if there are synergistic effects of such strategies. Because no one has yet defined quantitatively the oil synthesis pathway in crops, data produced in the project will have a fundamental impact in basic science. By combining the expertise of three important U.K. labs. with our world-leading international collaborators, this cross-disciplinary project will ensure a significant advance in knowledge of direct application to agriculture.

Life expectancies in the UK have increased rapidly over the last century. If this continues, recent studies have predicted that the majority of babies born since 2000 will live to 100. Our ageing population poses serious economic and medical problems, unless we can find ways of alleviating the process of physiological deterioration and many diseases that are associated with old age. Simple biological measures (or 'biomarkers') capable of illuminating the wider process of ageing and predicting the onset of common diseases of old age could provide important new understanding of the underlying causes of individual variation in ageing rates, as well as interventions to promote healthy ageing. Telomere length (TL) is an exciting candidate biomarker of ageing. Telomeres cap and protect our chromosomes and become shorter with each cell division. When telomeres become very short, cells stop functioning properly, with potentially negative consequences for wider bodily function. Accordingly, the process of telomere attrition is thought to play an important role in the way we age. In humans, telomeres are usually measured in white blood cells, because blood is relatively easy to obtain, and average TL of these cells declines with age. Excitingly, short TL in adulthood predicts various age-related diseases and reduced subsequent survival. However, age only explains a small part of the massive variation in TL among individuals, and we currently do not know why adult TL varies so much. Is it because of genetic or environmental effects on TL at birth, or is it down to differences in growth rates or experiences through early life and adulthood which affect the rate of telomere shortening? To answer this question we need blood samples and information over the entire lifetimes of individuals. This has not been possible in humans because we are so long lived. Furthermore, there are considerable differences in the telomere biology of short-lived and long-lived mammals, so laboratory mice may be poor models for humans. In this project, we will use a remarkably detailed long-term study of Soay sheep on St Kilda to tackle the question of how and why TL varies across the entire lifespan and what this means for the ageing process. It might seem odd to be using wild sheep on a remote island for such a purpose. In fact, the telomere biology of sheep and humans is similar, and the Soay sheep are one of the most closely monitored populations of mammals anywhere in the world. Since 1985, every sheep has been individually marked and followed closely across its lifetime, so we know how quickly they grew, when they bred, where they lived, when they died and we have detailed information on their genetics and the environmental conditions they experience. Importantly, we also regularly re-capture these animals and have collected blood samples repeatedly from around 3000 individuals all the way from birth to death. We will measure TL from archived blood samples to test whether differences in TL in late adulthood are mainly the result of differences in TL at birth or in telomere loss thereafter. We will also test how genes and environment during development influence TL and how natural selection acts on variation in TL. The uniquely detailed, life-long nature of our study will provide the first tests of the causes of individual variation in telomere attrition rates across the entire lifespan of a long-lived mammal. We will also extend the fieldwork on St Kilda to collect samples for more extensive telomere and immunological analyses. Laboratory studies show that a few very short telomeres are enough to compromise cell function, and in white blood cells this could compromise our immune system. Using newly-collected field data and blood samples, we will test both of these predictions outside of the lab for the first time, shedding new light on how changes in TL may influence our ability to fight disease, maintain health and survive in later adulthood.

All animals need to make the most of new opportunities or deal with changing environmental conditions. These changes may be short-term such as seasonal change, or long-term shifts such as climate change, and often impact the availability of food resources and, potentially, survival. Broadly, two different strategies might be used to increase access to resources in a changing environment. Animals might develop new solutions to problems (innovation), and thus find new resources themselves, or they might observe others and copy successful solutions. The latter, called social learning, is expected to be much more frequent than innovation, allows new behaviours to spread rapidly between individuals and is thought to be fundamental in forming traditions. Social learning has long fascinated biologists and anthropologists; understanding how behaviours spread and traditions are maintained in animals can shed light on the factors promoting complex culture in humans. An important determinant of social learning is the social organisation of the population in which learning occurs. It was long thought that only humans could exhibit highly developed cultural transmission due to their capacity for communication and learning that is facilitated by long-term social bonds. However recent research has found locally maintained cultural behaviour in a wide range of animals. Further, social network analysis in both human and other animal populations has allowed population structure to be accurately measured. Thus, using social networks to map the spread of new behaviours provides an exciting opportunity to understand this important learning process. In this study, we will study the spread of novel information in wild populations of a common bird, the great tit. All individuals in our large study population are tagged with microchips allowing us to track them automatically; our pilot data shows that they will learn socially. We will develop devices where one of two simple solutions provides access to food, and train an individual to solve one solution on the task in captivity before releasing it back into the woodland where we will place a number of these devices. Using this approach, we will be able to track who has learnt, from whom they learnt, and which of the two solutions they learnt. Using the social network of this population, we will track the spread of the new behaviours, and determine what characteristics made some individuals more important in spreading them. By training different individuals on the two different solutions, we will also see how local traditions develop and are maintained. Not all traditions or behaviours are advantageous. For example, in humans it has been shown that obesity can spread through friendship groups. In the second phase of this project we will alter the reward to different solutions of the task by replacing the popular solution with a low reward (peanut granules instead of a worm), maintaining the high reward on the less popular solution. This will test whether bad traditions are maintained through social reinforcement where individuals blindly copy the majority even when better solutions exist. Finally, we will develop some new technology that will predict what solution new individuals should be learning based upon the behavior of the group they belong to. By changing the behaviour at the device in response, we will then test in detail what elements of the behaviour observed in others is used when social learning. This will be the first time that anyone has used an active device to directly manipulate the behaviour of wild animals in this way. This will itself advance scientists' abilities to understand what rules individuals follow when making decisions such as who to copy and when. Such knowledge will be widely applicable across disciplines, for example in providing new opportunities for active conservation of threatened species by introducing behaviours that improve survival.

United Kingdom