Automatic discovery and annotation of the impact of chemical modifications in RNA on structure and binding

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A bio-molecule present in every living organism is Ribonucleic Acid (RNA). Like Desoxyribonucleic acid (DNA) they are formed of four different components, called bases. They share the first three called Adenine (A), Cytosine (C) and Guanine (G). The fourth is unique in RNA and called Uracil (U). They fulfill many essential roles, as transferring information, making proteins, and regulating genes. To do those things, they adopt complex three-dimensional structures. In the past decades, sequencing technologies has given us a lot of information about the ensemble of RNA sequences. Many complex experimental techniques have also allowed to determine some three-dimensional structures with extreme precision. Nonetheless, obtaining the structure is much more challenging than the sequence. Computational methods have been used to understand the relationship between the sequence, the structure, and ultimately their function. Those tools have proven to be invaluable to understand the massive amount of sequence data that has been produced and allowed to detect diseases by errors in the sequence, even to design new drugs by creating sequences that adopt specific structures with a desirable function. We now know that the sequence is not enough to fully understand the function of RNA. In both cases epigenetic factors, exterior to the sequence, manifest themselves as chemical modification on the bases. It has been recently discovered that they are essential for RNA to perform as they can have a strong effect on their structure. While over 190 modifications are observed in crystal structure, only a handful have been studied. Their number is steadily growing since just this year, the first sequencing technique to massively detect chemical modifications in sequences was designed, and promises a flood of new data. This proposal aims to create new computational methods to understand the impact of the chemical modification on their structure and function. It is divided in two main themes. The first one will study known structures that contain chemically modified RNAs. We will design a new ontology to describe the new interactions involving those chemically modified base pairs. We will in parallel create new algorithms to identify conserved structural modules, especially those with interactions, to understand how the global conformation of the RNA is impacted. Those will be used to better predict global conformation, and design RNAs with novel desirable functions. The second theme will look at the sequences. Although they often are without a known structures, they contain a lot of information that can be extracted from their large numbers. We will create bioinformatic methods to extract from evolutionary information connected networks of positions in the sequences that have co-evolved together, hinting at their functional necessity. Those will be used to understand and predict the role of chemical modifications in binding to other molecules.