Project: Read the RNA in its entirety, cell by cell

About

We described in 2020, in an article published in Nature Communications (https://pubmed.ncbi.nlm.nih.gov/32788667/), a new method for more finely analyzing the structure of RNA, in order to detect splicing or editing variations with resolution down to single cell. These approaches combine microfluidics tools with long-length nucleic acid sequencing. Their development aims to improve the construction of single cell atlases which are currently being produced.
Numerous protocols are already available for single-cell analysis of somatic mutations or DNA methylation, chromatin accessibility, epigenetic profiles, and copy number variations. Single-cell transcriptomics (scRNA-seq) remains the most comprehensive approach, enabling qualitative transcriptome analysis across hundreds of thousands of cells.
A current limitation of scRNA-seq lies in the way the sequencing is performed, which is most often limited to a single end of each RNA molecule. This is sufficient to quantitatively describe the level of gene expression, but information about splicing and sequence heterogeneity, distributed throughout the transcript, is usually lost.
To obtain more comprehensive transcriptome sequence information, we implemented a full-length sequencing approach using a Nanopore sequencer.
The developed method has been named ScNaUmi-seq. ScNaUmi-seq could thus allow for the analysis of the mutational landscape of tumors, or even the documentation of splicing mechanisms established during early development (https://pubmed.ncbi.nlm.nih.gov/34497388/). This development therefore adds an important new layer of information to improve our understanding of different cell types.
A more recent article (https://www.biorxiv.org/content/10.1101/2020.08.24.252296v1), currently available as a preprint, extends this work by applying the same approach to spatial transcriptomics samples. The method, called Spatial Isoform Transcriptomics (SiT), allows for the definition of spatial variations in genome splicing and/or editing.