Bioinformatic analyses of CRISPR elements

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Most archaea and many bacteria have a defence system against a variety of invading genetic elements called CRISPR-Cas systems, which is based on RNA. This project aims at a better understanding of the CRISPR-Cas system by using highly advanced bioinformatics approaches. First, we will develop a fully automated annotation pipeline for CRISPR-Cas systems. There is a severe deficit in convenient annotation applications for CRISPR-Cas systems. In addition to our automated characterization of CRISPR evolution (CRISPRmap), we intend to develop a web-server toolbox for a comprehensive automatic in silico characterization of many other important aspects of CRISPR-Cas systems, including the prediction of the CRISPR orientation, the leader sequence and the first automated annotation of CRISPR-Cas subtypes.Second, we want to identify CRISPR targets (i.e. protospacers) and characterize associated protospacer-adjacent motif, PAM, important for both adaptation and interference. Our goal is to first collect a set of protospacers from viral genomes and metagenomics data. Subsequently, we will identify and analyze patterns of associated PAMs. Characterized PAM motifs and their properties will be validated the groups of Schmitz-Streit and Randau.Third, we want to detect requirements of a CRISPR array that lead to efficient cleavage in a cell. These requirements do not only help to expand our knowledge of the diverse CRISPR processing mechanisms, but also aid in the design of artificial arrays for experiments. With experiments performed by the Hess and Marchfelder groups, we will measure the effect of detailed sequence and structure constraints on processing efficiency.Finally, we want to, in collaboration with Jörg Vogel/Nadja Heidrich and Emmanuelle Charpentier, characterize further type II systems that require a non-coding RNA (tracrRNA). These systems are especially interesting since they are widely used for genome editing.