SANDPIT: Transgenerational effects and evolution

The capacity for parents to induce phenotypic effects in their offspring, with no genetic basis, has been documented in most kingdoms of living organisms. The stimulus that evokes such parental effects may appear only transiently during the parent's lifetime, and may have only a transient impact on the parent, and yet may nevertheless exert a long-lasting influence on the offspring if it is imposed during a critical window of sensitivity in the developmental process. These offspring may then transmit such effects to their own offspring, generating longer-term trans-generational effects. Despite increasing evidence for these effects, why they have evolved, and why they differ so widely across species, remains poorly understood. A key reason for this poor understanding is the lack of a robust theoretical framework for investigating the phenomenon. Trans-generational effects are particularly relevant to humans, as it is increasingly recognized that some aspects of phenotype are flexible in relation to prevailing conditions, whereas others are strongly influenced by ancestral experience. Processes such as climate change, economic development and migration all challenge organisms, including humans. How different organisms can respond to such challenges is determined in part by the variable contribution of trans-generational effects to phenotypic development. Thus, understanding trans-generational effects has many practical implications, for understanding how organisms will respond to different types of environmental change.Our research hypothesis is that trans-generational effects are an adaptive consequence of evolved life-history strategies, and that we can therefore predict under what ecological conditions they will arise. We propose to use novel life-history models to explain the diversity of trans-generational effects across species. These models consider how organisms should divide their resources between competing processes such as growth versus reproduction. A 'decision' in the parent generation has implications for the phenotype of the offspring, and hence what 'decision' should be made in this generation. We will use 'evolutionary game theory' in these models, which considers how the best strategy for one individual must take into account the strategies of other individuals, such as their offspring. In order to build these models, we will need to develop novel mathematical methods for modeling life-history evolution that can better accommodate trans-generational influences. Trans-generational effects pose some particularly intriguing challenges for mathematical modeling, because there are time lags between when information 'enters' phenotype (eg being a first-born), and when natural selection operates (eg on the offspring of that first-born individual). These time-lags are mathematically very complex, and they may be further complicated by asymmetries between the two parents. For example, the ovum develops during the mother's own fetal life, whereas the sperm develops during the father's adolescence. The two parents therefore provide information to the offspring from contrasting time periods, which might in turn influence how the offspring should respondWe are also interested in how organisms can respond to 'extreme events', such as forest fires or famines. These events occur less often than every generation, hence many generations never actually experience them. We will investigate how such extreme events might contribute to the evolution of trans-generational effects. Once developed, we will use our model to evaluate our theoretical analyses across different species. We will pay particular attention to humans, benefiting from data on cohort studies already available to the investigators. These cohort studies provide data on 3 or more generations, and will allow us to undertake analyses using insights from the mathematical modeling.

Because trans-generational effects are highly relevant to the generic issue of environmental change, our work is likely to benefit a wide variety of users, including policy makers, government and international health care providers including development charities, and commercial companies. Broad-scale ecological change, whether due to climate change or other human impacts such as deforestation and habitat change, is well-established to exert different effects on diverse organisms according to their capacity to adapt within and across generations. The nature of trans-generational effects is fundamental to this inter-species flexibility. Our work will aid those investigating how agricultural production systems may be adapted to tolerate increasingly stochastic conditions, for example by indicating what existing crop traits merit wider utilisation versus disinvestment; what kinds of traits might be selected for in novel crop variants currently under development; and what kind of time-scales are realistic for making such changes. Our work will also aid the development of economic models by clarifying the capacity of diverse biological organisms to respond, and hence the likely instability of future food supplies. The same issues may have implications for conservation biologists, improving understanding of differential vulnerability of species or ecosystems. This work therefore has major potential benefit for policy makers In the same vein, in the last two decades the 'developmental origins of adult disease' hypothesis has proven critical for understanding the early-life origins of degenerative diseases such as stroke, hypertension, type 2 diabetes and cardiovascular disease. These diseases are already endemic in industrialised populations, but are also increasingly prevalent in modernising populations. Researchers are now aware of the multi-generational nature of disease aetiology, with disease risk exacerbated by a disparity between the 'homeostatic capacity' of vital organs (heart, liver, kidney, lungs and pancreas) and the 'metabolic load' exerted by large body size, nutritionally-dense diet and sedentary lifestyle. Whilst 'metabolic load' has high plasticity and readily reflects prevailing ecological conditions, 'homeostatic capacity' has a strong trans-generational basis and has less flexibility to alter across the life-course. Improved understanding of the evolutionary basis of trans-generational effects is thus likely to make a key contribution to the development of public health policies targeted at reducing degenerative disease risk, with major implications both for the health of future generations, and for identifying the likely future health costs of treating degenerative diseases. It is arguably the failure for example to consider obesity as a trans-generational disease process that is responsible for the failure of most policy initiatives to have beneficial preventive effects. Many private sector companies are engaged in work involving living organisms relevant to these issues. Those developing or implementing agricultural technologies will benefit from information on biological variability in robusticity and vulnerability that is unlikely to emerge from their own activities or research. Equally, companies involved in the planning or implementation of economic development in modernising populations will benefit from improved understanding of how their current activities are likely to shape the future population profile, aiding them improve the health impact of products, or anticipate changing needs across generations. The project will contribute substantial career development to the post-doctoral and doctoral scientists, providing training and expertise in a current 'hot-topic' area of biology already benefitting from mathematical approaches, and extensive opportunities to develop their research and professional skills.