scCAT-seq:single-cell identification and quantification of mRNA isoforms by cost-effective short-read sequencing of cap and tail

Abstract

AbstractThe differences in transcription start sites (TSS) and transcription end sites (TES) among gene isoforms can affect the stability, localization, and translation efficiency of mRNA. Isoforms also allow a single gene different functions across various tissues and cells However, methods for efficient genome-wide identification and quantification of RNA isoforms in single cells are still lacking. Here, we introduce single cell Cap And Tail sequencing (scCAT-seq). In conjunction with a novel machine learning algorithm developed for TSS/TES characterization, scCAT-seq can demarcate transcript boundaries of RNA transcripts, providing an unprecedented way to identify and quantify single-cell full-length RNA isoforms based on short-read sequencing. Compared with existing long-read sequencing methods, scCAT-seq has higher efficiency with lower cost. Using scCAT-seq, we identified hundreds of previously uncharacterized full-length transcripts and thousands of alternative transcripts for known genes, quantitatively revealed cell-type specific isoforms with alternative TSSs/TESs in dorsal root ganglion (DRG) neurons, mature oocytes and ageing oocytes, and generated the first atlas of the non-human primate cornea. The approach described here can be widely adapted to other short-read or long-read methods to improve accuracy and efficiency in assessing RNA isoform dynamics among single cells.