All biological organisms are, in fact, systems within systems. They are composed of networks of interdependent components that integrate to form a unified whole. Through systems approaches, researchers demonstrate these linkages by modifying the level of one component and observing the communicated effects on others.
Plants adjust their growth in response to a multitude of exogenous and endogenous cues. To thrive, they optimize their use of resources to meet their needs for energy and biosynthetic building blocks. Their ability to grow depends entirely on their own photosynthetic and metabolic capacity, so they constantly adjust their rate of development to match their metabolic status.
We perform detailed analyses of these complex interactions – integrating systems data rather than reducing the system to the interactions of its parts.
Unbiased screens of genotyped populations have replaced the pathway-oriented, (single) gene-driven analyses of decades past. We are searching for novel genes controlling metabolism and growth (metabolic and biomass quantitative trait loci). We focus on the complex ways plants respond to abiotic stresses, such as nutrient deprivation, anoxia, etc., to develop a picture of the processes taking place. We gear our analyses towards unravelling regulatory processes and the signal molecules involved.
We are becoming increasingly competent at acquiring and analysing phenotype data (transcripts, proteins, enzymes, metabolites, fluxes, growth, photosynthetic rates, etc.), which is leading quite naturally to network-based analyses of the molecular processes underlying systems phenomena.
These network analyses form the basis for multiple hypotheses regarding the importance of single parameters. In this context, a major challenge is the development and implementation of strategies that allow the independent validation/falsification of hypotheses derived from networks.
We are using and developing genetic implements (e.g., inducible expression or repression systems) that allow us to disturb and subsequently monitor the plant system. In addition, we are using chemical genomics – a strategy employing libraries of small molecules (natural compounds, aptamers, or the products of combinatorial chemistry) with high-throughput screening – to identify compounds that act as positive or negative regulators of individual gene products, pathways, or cellular phenotypes. Finally, we are making small, systematic changes in gene expression (e.g., knockout heterozygotes) and monitoring system responses.
From genome structure to genome function and genome evolution
There are two basic types of genomics approaches: structural approaches (such as mapping, sequencing, comparisons between and among genomes, and studies of genome organisation) and functional approaches with which gene expression is analysed at transcriptome (mRNA), metabolome (metabolite), or proteome (protein) levels, often using high throughput technology.
A few years ago, our institute made a profound fundamental genomic contribution (in the framework of an international consortium) by establishing the first complete BAC-based physical map of the Arabidopsis genome (see Developmental Physiology and Genomics). This map aided large-scale sequencing efforts. Now that Arabidopsis has been mapped and sequenced, the challenge is rapid and accurate plant phenotyping at the molecular level. Every group in our institute applies genomics in the context of analysing altered plant systems.
We are also interested in understanding how plant genomes evolved. In addition to using genomics data to reconstruct the co-evolution of the three genomes of the plant cell (in the nucleus, the plastids and the mitochondria), we have begun to reproduce key processes in plant genome evolution in laboratory experiments. We have developed genetic screens allowing us to observe gene transfer between compartments in real time and to elucidate the molecular event involved in functional activation of successfully transferred genes.