Current methods for determining RNA structure with short-read sequencing cannot capture most differences between distinct transcript isoforms. Researchers at A*STAR, Singapore present RNA structure analysis using nanopore sequencing (PORE-cupine), which combines structure probing using chemical modifications with direct long-read RNA sequencing and machine learning to detect secondary structures in cellular RNAs. PORE-cupine also captures global structural features, such as RNA-binding-protein binding sites and reactivity differences at single-nucleotide variants. The researchers show that shared sequences in different transcript isoforms of the same gene can fold into different structures, highlighting the importance of long-read sequencing for obtaining phase information. They also demonstrate that structural differences between transcript isoforms of the same gene lead to differences in translation efficiency. By revealing nano-specific RNA structure, PORE-cupine will deepen understanding of the role of structures in controlling gene regulation.
Schematic of direct RNA sequencing followed by signal processing
RNAs were structure probed and nanopore sequenced, yielding characteristic voltage signals. The non-structure-probed signal was used as a training set to predict modifications from the structure-probed data set.
Availability – Source code for all scripts (R version 3.4.1) and commands used for analysis can be found at http://github.com/awjga/PORE-cupine.