N6-methyladenosine (m6A) is the most abundant internal RNA modification in eukaryotic mRNAs and influences many aspects of RNA processing. miCLIP (m6A individual-nucleotide resolution UV crosslinking and immunoprecipitation) is an antibody-based approach to map m6A sites with single-nucleotide resolution. However, due to broad antibody reactivity, reliable identification of m6A sites from miCLIP data remains challenging. Here, we present miCLIP2 in combination with machine learning to significantly improve m6A detection. The optimized miCLIP2 results in high-complexity libraries from less input material. Importantly, we established a robust computational pipeline to tackle the inherent issue of false positives in antibody-based m6A detection. The analyses were calibrated with Mettl3 knockout cells to learn the characteristics of m6A deposition, including m6A sites outside of DRACH motifs. To make our results universally applicable, we trained a machine learning model, m6Aboost, based on the experimental and RNA sequence features. Importantly, m6Aboost allows prediction of genuine m6A sites in miCLIP2 data without filtering for DRACH motifs or the need for Mettl3 depletion. Using m6Aboost, we identify thousands of high-confidence m6A sites in different murine and human cell lines, which provide a rich resource for future analysis. Collectively, our combined experimental and computational methodology greatly improves m6A identification.

Oligodendrocytes are the myelinating glial cells of the central nervous system. In the course of brain development, oligodendrocyte precursor cells migrate, scan the environment and differentiate into mature oligodendrocytes with multiple cellular processes which recognize and ensheath neuronal axons. During differentiation, oligodendrocytes undergo dramatic morphological changes requiring cytoskeletal rearrangements which need to be tightly regulated. The non-receptor tyrosine kinase Fyn plays a central role in oligodendrocyte differentiation and myelination. In order to improve our understanding of the role of oligodendroglial Fyn kinase, we have identified Fyn targets in these cells. Purification and mass-spectrometric analysis of tyrosine-phosphorylated proteins in response to overexpressed active Fyn in the oligodendrocyte precursor cell line Oli-neu, yielded the adaptor molecule p130Cas. We analyzed the function of this Fyn target in oligodendroglial cells and observed that reduction of p130Cas levels by siRNA affects process outgrowth, the thickness of cellular processes and migration behavior of Oli-neu cells. Furthermore, long term p130Cas reduction results in decreased cell numbers as a result of increased apoptosis in cultured primary oligodendrocytes. Our data contribute to understanding the molecular events taking place during oligodendrocyte migration and morphological differentiation and have implications for myelin formation.

In the central nervous system, oligodendroglial expression of myelin basic protein (MBP) is crucial for the assembly and structure of the myelin sheath. MBP synthesis is tightly regulated in space and time, particularly at the post-transcriptional level. We have identified the DEAD-box RNA helicase DDX5 (also known as p68) in a complex with mRNA in oligodendroglial cells. Expression of DDX5 is highest in progenitor cells and immature oligodendrocytes, where it localizes to heterogeneous populations of cytoplasmic ribonucleoprotein (RNP) complexes associated with mRNA in the cell body and processes. Manipulation of the amount of DDX5 protein inversely affects the level of MBP. We present evidence that DDX5 is involved in post-transcriptional regulation of MBP protein synthesis, with implications for oligodendroglial development. In addition, knockdown of DDX5 results in an increased abundance of MBP isoforms containing exon 2 in immature oligodendrocytes, most likely by regulating alternative splicing of Our findings contribute to the understanding of the complex nature of MBP post-transcriptional control in immature oligodendrocytes where DDX5 appears to affect the abundance of MBP proteins via distinct but converging mechanisms.

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N6-methyladenosine (m6A) is the most abundant internal RNA modification in eukaryotic mRNAs and influences many aspects of RNA processing, such as RNA stability and translation. miCLIP (m6A individual-nucleotide resolution UV crosslinking and immunoprecipitation) is an antibody-based approach to map m6A sites in the transcriptome with single-nucleotide resolution. However, due to broad antibody reactivity, reliable identification of m6A sites from miCLIP data remains challenging. Here, we present several experimental and computational innovations, that significantly improve transcriptome-wide detection of m6A sites. Based on the recently developed iCLIP2 protocol, the optimised miCLIP2 results in high-complexity libraries from less input material, which yields a more comprehensive representation of m6A sites. Next, we established a robust computational pipeline to identify true m6A sites from our miCLIP2 data. The analyses are calibrated with data from Mettl3 knockout cells to learn the characteristics of m6A deposition, including a significant number of m6A sites outside of DRACH motifs. In order to make these results universally applicable, we trained a machine learning model, m6Aboost, based on the experimental and RNA sequence features. Importantly, m6Aboost allows prediction of genuine m6A sites in miCLIP data without filtering for DRACH motifs or the need for Mettl3 depletion. Using m6Aboost, we identify thousands of high-confidence m6A sites in different murine and human cell lines, which provide a rich resource for future analysis. Collectively, our combined experimental and computational methodology greatly improves m6A identification.HighlightsmiCLIP2 produces complex libraries to map m6A RNA modificationsMettl3 KO miCLIP2 allows to identify Mettl3-dependent RNA modification sitesMachine learning predicts genuine m6A sites from human and mouse miCLIP2 data without Mettl3 KOm6A modifications frequently occur outside of DRACH motifs and associates with alternative splicing