Characterization of post-transcriptional regulatory network of RNA-binding proteins using computational predictions and deep sequencing data (2013)

This report is divided into three parts: Data Analysis, Mathematical&#13;\nModeling and Conclusion and future directions. In the Data Analysis part,&#13;\nvarious methods and tools for characterizing the post-transcriptional&#13;\nregulatory networks of RNA-binding proteins are discussed and applied.&#13;\nChapter 2 introduces PAR-CLIP, a method for transcriptomewide&#13;\nidentification of RNA binding proteins at nucleotide resolution.&#13;\nPAR-CLIP was successfully applied on RNA binding proteins and&#13;\ntheir binding specificity was characterized.&#13;\n&#13;\nPartly due to their vast volume, the data that were so far generated&#13;\nin CLIP experiments have not been put in a form that enables fast and&#13;\ninteractive exploration of binding sites. To address this need, Chapter&#13;\n3 presents CLIPZ, which is a database and analysis environment&#13;\nfor various kinds of deep sequencing (and in particular CLIP) data,&#13;\nthat aims to provide an open-access repository of information for&#13;\npost-transcriptional regulatory elements.&#13;\nChapter 4 revisits various CLIP methods. A set of ideas in terms&#13;\nof both experimental protocols and data analysis are presented to&#13;\nimprove the quality and reproducibility of such experiments. In&#13;\ngeneral, cytoplasmic RNAs are isolated in CLIP experiments. Like&#13;\nmany high-throughput experiments, CLIP has a certain amount of&#13;\nisolated RNAs which do not represent regulatory binding sites. To&#13;\nimprove the quality of the obtained RNAs, a set of novel methods for&#13;\ndata analysis are also suggested. These methods are added as new&#13;\ntools to the CLIPZ analysis platform.&#13;\nArgonaute CLIP data could in principle be beneficial in improving&#13;\nthe microRNA target site predictions. However, several questions still&#13;\nremain which cannot be addressed using CLIP methods. For example:&#13;\n• Argonaute CLIP data by default does not reveal which microRNAs&#13;\nare more likely to interact to the mRNA binding site at the&#13;\ntime of cross-linking.&#13;\n• As mentioned earlier, biochemical and structural studies of Thermus&#13;\nthermophilus Argonaute protein suggest that the&#13;\nprotein-RNA interaction between microRNA and the Argonaute&#13;\nprotein forms a physical structure that only some positions in&#13;\nthe microRNA become accessible to the target binding site. Having&#13;\ninferred the interacting microRNA, it is also interesting to&#13;\npredict the most plausible secondary structure of the hybridized&#13;\nmicroRNA-mRNA complex.&#13;\nMathematical Modeling part of the report contains Chapter 5. This&#13;\nchapter presents a novel mathematical model called MIRZA to address&#13;\nthe above mentioned questions. An in-depth introduction to&#13;\nMIRZA is presented and its performance in terms of identifying functionally&#13;\nrelevant targets of microRNAs is discussed.&#13;\nFinally, Conclusion and future directions part of the report contains&#13;\nChapter 6 in which discusses the main findings of the projects and&#13;\ngives an outlook of where future work could be taken up.