Understanding the full range of RNA molecules produced by our genes is crucial for insights into health and disease. While traditional short-read RNA sequencing has been instrumental, it often falls short in distinguishing between similar RNA variants, known as isoforms. A recent study led by researchers at the Genome Institute of Singapore addresses this challenge by benchmarking various RNA sequencing protocols, highlighting the advantages of long-read sequencing technologies like Nanopore and PacBio.​

The research team analyzed seven human cell lines using five different RNA sequencing methods, including both short-read and long-read approaches. They discovered that long-read sequencing provides a more accurate and comprehensive view of RNA isoforms, enabling the identification of novel transcripts, fusion events, and RNA modifications such as N6-methyladenosine (m6A). This comprehensive dataset, known as SG-NEx, serves as a valuable resource for developing computational tools aimed at profiling complex transcriptional events at the isoform level.​

Overview of the SG-NEx datasets and processing pipeline

a, Seven human cell lines were sequenced with multiple replicates using different RNA-seq protocols. Short-read cDNA was sequenced with 150-bp paired-end reads. hES cells, human embryonic stem cells. Icons from Noun Project under a Creative Commons license CC BY 3.0: colon, Mungang Kim; leukocytes, ProSymbols; liver, Prettycons; lung, Mahmure Alp; breast, Karina; ovary, Amethyst Studio; hES cells, DailyPM. b, Number of sequencing runs generated for each SG-NEx core cell line. c, Number of sequencing runs for each of the RNA-seq technologies. d, Illustration of the nf-core Nextflow pipeline (nanoseq) for streamlined processing of Nanopore long-read RNA-seq data.

By offering a clearer picture of the transcriptome, long-read RNA sequencing holds promise for advancing our understanding of gene expression and its implications in various biological processes and diseases.​