Optimizing Single-Cell Long-Read Sequencing for Enhanced Isoform Detection in Pancreatic Islets [sc_islet]

The goal of this study was to optimize single-cell long-read RNA sequencing in pancreatic islets to enable accurate isoform-level gene expression analysis. We aimed to overcome key technical limitations—including insufficient read lengths, high error rates, and transcript abundance bias—that have hindered long-read sequencing in single cells. Specifically, we compared 5' and 3' library preparation strategies and evaluated transcript depletion methods to improve detection of low-abundance isoforms. Our objective was to establish a robust protocol that enhances isoform identification and reveals differential transcript usage across pancreatic islet cell types. Overall design: Single-cell RNA-seq libraries from dissociated pancreatic islets of 10-week-old C57BL/6 mice. We generated three libraries: one generated with 3' 10x Genomics technology, one generated with 5' 10x Genomics technology, and one generated with 5' 10x Genomics technology with protocol modifications (extention time and dNTP concentration). The 3' library was sequenced on a Illumina short-read sequencer. The two 5' libraries were sequenced on an Oxford Nanopore long-read sequencer.