Systems biology

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    testing - finding cis-elements
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    testing - thermodynamic model
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Systems biology of gene regulation

The spatio-temporal regulation of gene expression lies at the core of animal development and adult function. One of the great challenges is to ‘crack’ the regulatory code. In previous work, we developed methods for the detection and analysis of the small cis-regulatory elements that control transcription and translation. Applying these tools to the segmentation process in the Drosophila embryo, one of the key paradigms in developmental pattern formation, we identified many new elements and generated the first computational model that explicitly describes the binding of transcription factors to regulatory sequence and the resulting expression, thus capturing the mechanistic core of the process. More recently, we have used these methods to decipher the regulatory architecture underlying the crucial transition from non-periodic to periodic patterns during segmentation.

Ongoing studies

We are currently expanding this work in several directions. In the segmentation paradigm, we seek to further experimentally test and improve our computational models: In one project, we are generating synthetic cis-elements to systematically explore the rules of cis-element architecture and test how well actual and predicted expression match. Second, the DNA binding preferences of transcription factors are typically not well sampled and thus represent a significant source of error in the modeling. Here, we are collaborating with physicists to develop new (high throughput) methods to measure the binding energy landscape of transcription factors ex vivo and, ultimately, in vivo. We are extending this approach to include the core promoter, which plays a crucial role in setting the transcription rates of different types of genes; to address this question, we combine bioinformatic, molecular, and biochemical methods. All new experimental data are fed into our computational models and examined for their ability to improve predictive power.

In a second independent line of investigation, we are applying our approaches and concepts to more complex paradigms and regulatory systems at later stages of Drosophila development, where pattern formation occurs over longer time periods and amid constant cell proliferation and death. Due to the paucity of existing experimental data, we are embarked on a large-scale effort to map transcription factor binding sites and measure their occupancy genome-wide under different gain- and loss-of-function conditions using chromatin immune precipitation and deep sequencing. We compare these data with genome-wide nucleosome and RNA polymerase II occupancy and nascent transcription rates. The overall goal of this work is to identify and characterize the regulatory networks that govern cell proliferation, differentiation and death.