Advances in long-read single-cell transcriptomics

Hum Genet. 2024 Oct;143(9-10):1005-1020. doi: 10.1007/s00439-024-02678-x. Epub 2024 May 24.

Abstract

Long-read single-cell transcriptomics (scRNA-Seq) is revolutionizing the way we profile heterogeneity in disease. Traditional short-read scRNA-Seq methods are limited in their ability to provide complete transcript coverage, resolve isoforms, and identify novel transcripts. The scRNA-Seq protocols developed for long-read sequencing platforms overcome these limitations by enabling the characterization of full-length transcripts. Long-read scRNA-Seq techniques initially suffered from comparatively poor accuracy compared to short read scRNA-Seq. However, with improvements in accuracy, accessibility, and cost efficiency, long-reads are gaining popularity in the field of scRNA-Seq. This review details the advances in long-read scRNA-Seq, with an emphasis on library preparation protocols and downstream bioinformatics analysis tools.

Publication types

  • Review

MeSH terms

  • Animals
  • Computational Biology* / methods
  • Gene Expression Profiling* / methods
  • High-Throughput Nucleotide Sequencing / methods
  • Humans
  • Sequence Analysis, RNA / methods
  • Single-Cell Analysis* / methods
  • Transcriptome*