Eva Maria Novoa from the Center for Genomic Regulation in Spain presented at London Calling 2019 a session on “Accurate detection of m6A RNA modification in native RNA sequences using third-generation sequencing.” Novoa emphasized there is a difference between RNA levels and protein. They have been working in this field. Interestingly, RNA modifications have been known since the 1970s! RNA modifications are reversible and can be measured with Nanopore sequencing. The ability to detect RNA modifications boosted the field, and many more publications on this topic have been published in recent years. A student with Novoa examined the literature and found over 170 RNA modifications and numerous associations between RNA modification and human disease. However, the majority of modifications remain very challenging to detect. Martin Smith taught Novoa about Oxford Nanopore Technologies. Training sets are needed to detect modifications. Thus, Novoa and Smith designed RNAs to use for training. The software is called CURLCAKE: Compact Unstructured RNA Libraries Covering All KmErs. Novoa used sequencing errors to learn about RNA modifications using machine learning algorithms. They compared M6A motifs to control unmodified motifs. They then trained machine learning algorithms to detect the M6A motifs. The team then validated the approach in vivo using yeast wild-type and IME4 deletion strains. This approach was used to detect/distinguish other RNA modifications, including UNM, M5C, and pU. Some of the challenges are decreasing the input RNA to obtain better yields. Barcoding strategies are of interest, and they have developed barcodes. This field is of personal interest, and I really enjoyed this session!
