Microarray-based discovery of plant growth-regulatory genes

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Plants are the ultimate source of all human food and (as fossil fuels) the majority source of the energy upon which modern civilisation depends. It is therefore of crucial importance that we fully understand how the growth of plants is controlled. Previous work has identified a family of proteins (known as the DELLA proteins) that restrain the growth of plants in response to signals from the environment. These signals warn plants of environmental conditions that are not optimal for growth. Plants then use their DELLA proteins to adapt their growth accordingly. However, it is clear that additional proteins control plant growth, and that the identification of these additional proteins has previously been hindered because their effects are masked by the effects of the DELLA proteins. This proposal firstly describes how genetics can be used to unmask the effects of these previously unknown growth-regulatory proteins, and secondly describes how harnessing the latest advances in plant genome biology and computational analysis will enable us to identify the genes encoding those growth-regulatory proteins. The systems that regulate the growth and development of organisms are often physiologically 'buffered'. Consider an imaginery case where growth is regulated by two distinct mechanisms, A and B. It is frequently found that a gene mutation affecting mechanism B only has a detectable effect on growth when mechanism A is not functioning. Thus, when A is functioning, B is genetically 'invisible' because mutations in genes involved with B have no effect on growth (no detectable 'phenotype'). The way to circumvent these problems is to perform mutant screens in genetic backgrounds lacking A. Accordingly, we are proposing to identify novel growth mutants from a genetic background in which the DELLA growth-regulatory mechanism (mechanism A in our imaginery case) is missing. The new mutants will be generated using fast-neutron mutagenesis. Fast neutrons are particularly useful mutagens because they tend to generate small deletions of contiguous segments of DNA from plant chromosomes. These deletions are usually small enough to be be contained within (or encompass) single genes. It has recently become possible to detect such deletions at the molecular level. Hybridization of DNA from deletion mutants to 'chip-array' representations of the entire plant genome (and subsequent computational analysis of the resulting data) allows precise detection of the location of the deletion mutation, and hence identification of the gene affected. However, whilst these methods work (see Case for Support), they are very new and still relatively crude. We therefore propose further methods improvement, both of the hybridisation reaction and of the software that does the data-analysis, so as to make the detetion of mutated genes both reliable and routine. The proposal therefore outlines the development of a mutation detection 'pipeline' that quickly leads from initial identification of novel mutations affecting growth, through microarray-based detection of the molecular site of those mutations, to the eventual identification of previously unknown growth-regulatory genes (and protein gene products). Once these previously unknown growth-regulatory proteins and genes are identified we will have moved a step further towards understanding how plant growth is controlled. We already know that growth is controlled in response to a complex network of different signals from both the environment and from the plants interior. Somehow, this network of signalling inputs is integrated into a single growth output. How this crucial integration is achieved is currently only incompletely understood. The work described in this proposal will enable the identification of proteins (additional to the DELLA proteins) that perform this integrating role, and will thus contribute to the ultimate goal of a full understanding of how plant growth control is achieved.