Service Project: "CRISPR Bioinformatics"

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Bioinformatics analysis has always played a key role in the history of the CRISPR-Cas system. The characteristic repetitive structure of CRISPR loci has been known since 1987 but it was only in 2005 when a computational analysis revealed that spacers could match bacteriophage genomes, leading to the later-confirmed hypothesis that the CRISPR-Cas system acts as an immune system. Bioinformatic approaches have always been instrumental in the detection of new functions and applications, one prominent example being the in-silico detection of endogenous targets of CRISPR-Cas systems which hinted towards endogenous regulatory mechanisms. The discovery of new and unusual CRISPR-Cas elements and functions by computational analyses, however, requires careful definition of the different standard elements of a CRISPR-Cas system. Only a precise and comprehensive classification can avoid the detection of too many false positives, which occur only due to an incomplete detection of all standard elements.Thus, we wish to support the experimental groups of the SPP 2141 in the detection of new functions for CRISPR-Cas systems by setting up a thorough classification of all the major elements of the CRISPR-Cas system. These classification tools will then be employed in the detection of novel elements and functions in collaboration with the aforementioned experimental groups. This will comprise new and comprehensive detection and classification approaches for: 1) CRISPR arrays and their associated elements such as protospacers and PAM; 2) Cas proteins and complete CRISPR-Cas systems in genomic and metagenomic data; and 3) CRISPR-related sRNAs like tracRNA and scaRNAs. We will use this information to search for CRISPR-Cas systems with unusual composition, such as orphan Cas proteins and CRISPR arrays. However we expect to find many other unusual compositions, especially within metagenomic data, which have not yet been screened for previously in any CRISPR-Cas systems so far. In addition, we will actively assist the experimental groups in the analysis of CRISPR-related NGS data.