Mechanisms to generate inter-individual variability from single-cell heterogeneity

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Genetically identical individuals, from populations of bacteria to human twins, often behave differently, even though they have identical genes. We are interested to know how these differences are generated, and what effects these differences might have. Our model system of choice is a small model plant, Arabidopsis, which produces 1000s of genetically identical seeds each generation. Plants grow in a variable and noisy environment, including fluctuating light, water and temperature. Plants also have a noisy internal environment; recent work from our laboratory has revealed that even in plants that are genetically identical and grown in the same environment, around 9% of genes will be highly variable in their level of activation from plant to plant. We found that stress response genes that help plants survive environmental conditions such as drought, high salinity or extreme temperatures were particularly likely to be variable in their expression levels between plants. This variation in gene activation could be useful in nature for populations of genetically similar plants to hedge bets against unpredictable environmental stresses. This is because variable gene expression would mean that there are always a few plants in the population that are prepared to survive different stresses due to their variable gene activation. There might be a cost to having high expression of stress response genes, which could make variable gene expression more advantageous than all plants having high expression levels of a gene all of the time. As well as having potential benefits in the wild, variability between plants can also be a problem, such as in agriculture where environments are more controlled and farmers require uniform crops that germinate and flower at the same time and respond equally to applications of fertilisers and water.In this proposal, we seek to understand how the differences in gene activity between genetically identical plants grown in the same conditions are generated by cellular-level processes. To do this, we will use two different live imaging techniques to monitor gene activity of candidate 'noisy' pathways over time. We will use luminescent reporters (using a luciferase gene from fireflies) to give us a read out of the expression of our genes of interest at the level of whole seedlings. This technique will allow us to monitor how expression of a particular gene varies over time and across tissues such as leaves, stems and roots. We will also use fluorescent reporters (using green fluorescent protein from jelly fish) to allow higher resolution imaging of individual living cells in the tissues of interest. We will test how the variability in the levels of activity of genes in tissues and individual cells leads to the differences at the level of whole plants. To understand the results of our experiments, we will build mathematical models of the gene activation dynamics that will help us test our understanding and design new experiments. We will focus on a pathway controlled by a stress response hormone, ABA, as we have found that many genes regulated by it appear to be highly variable from plant to plant.Finally, we will determine the effects on plant growth and survival of the noisy gene activation we have characterised. We will track gene activity before and after the addition of stress, and examine whether the level of activation of a pathway before the stress correlates with the survival of a plant after stress. It could be that the random activation of the pathway before stress allows the plants that have higher expression to survive the sudden change in conditions (a bet-hedging strategy). In the future, understanding how plants produce and regulate noise in gene activity will be important for the development of more uniform crops and to understand how populations of wild plants can survive more frequent weather extremes due to climate change.