Journal: Trends in Biotechnology
Article Title: New Twists in Detecting mRNA Modification Dynamics
Figure Lengend Snippet: Nanopore Sequencing. (A) Schematic of the library preparation procedure for Nanopore direct RNA sequencing. PolyA RNA is enriched using oligo-dT primers and a reverse transcription (RT) adaptor is ligated. After second-strand synthesis, the sequencing adapter RMX, which is preloaded with motor protein and tether protein, is then ligated. (B) Schematic of Nanopore direct RNA sequencing. The motor protein feeds the RNA molecule through the nanopore in the 3′–5′ direction. The five bases passing through a nanopore cause a characteristic disruption in the current which is stored as raw signal. (C) A current trace (squiggle plot) showing the raw signal generated by nanopore sequencing of a single mRNA molecule. Leader and adapter sequences are shaded yellow and pink, the polyA tail is shaded green, and the mRNA body is shaded orange. The inset (top right) illustrates how the nucleotide sequence is inferred from the raw current trace originating from a sliding window of five nucleotides (k-mer). Machine-learning algorithms are then used to calculate the probability that a signal corresponds to a given k-mer, thus inferring the nucleotide sequence from the calculated probabilities. (D) The two features recorded by Oxford Nanopore Technologies (ONT) sequencers are the current signal (in arbitrary units, AU) and the time that a given k-mer takes to transverse the pore (signal length, retention time or 'dwell'). The scatter plot depicts the distribution of mean current and signal length for 100 reads each in a different sequence context of the unmodified k-mer CACCC (blue) and the modified k-mer CAm 5 CCC (orange, identified by parallel bisulfite sequencing, where m 5 C is 5-methylcytosine). Note that, despite an identical k-mer, the signal varies as a result of different measurements and intrinsic noise in different reads, and possibly also by the different surrounding sequence of a given k-mer. This variability can be represented as a signal density plot for each k-mer, depicted in the top-right inset (density distribution for raw current signal). RNA modifications can affect raw current reads as well as signal length, resulting in a shift in signal distributions (e.g., divergence between blue and orange). However, these signal shifts can be modest, as shown by the largely overlapping density plots for CACCC and CAm 5 CCC, making accurate prediction of modified bases a computational challenge. Plots were generated with Sequoia, an interactive visual analytics platform for interpretation and feature extraction from ONT sequencing datasets [ 138 ].
Article Snippet: We aim to highlight the strengths and limitations of current methods regarding specificity, sensitivity, and reproducibility, with a particular focus on emerging single-molecule direct RNA sequencing by Nanopore.
Techniques: Nanopore Sequencing, RNA Sequencing Assay, Sequencing, Generated, Modification, Chick Chorioallantoic Membrane Assay, Countercurrent Chromatography, Methylation Sequencing