Understanding isoform expression by pairing long-read sequencing with single-cell and spatial transcriptomics
- Natan Belchikov1,2,3,
- Justine Hsu1,2,
- Xiang Jennie Li1,2,4,
- Julien Jarroux1,2,
- Wen Hu1,2,
- Anoushka Joglekar5,6 and
- Hagen U. Tilgner1,2
- 1Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York 10065, USA;
- 2Center for Neurogenetics, Weill Cornell Medicine, New York, New York 10021, USA;
- 3Physiology, Biophysics, and Systems Biology Program, Weill Cornell Medicine, New York, New York 10065, USA;
- 4Computational Biology Master's Program, Weill Cornell Medicine, New York, New York 10065, USA;
- 5New York Genome Center, New York, New York 10013, USA;
- 6Department of Biomedical Informatics, Columbia University, New York, New York 10032, USA
Abstract
RNA isoform diversity, produced via alternative splicing, and alternative usage of transcription start and poly(A) sites, results in varied transcripts being derived from the same gene. Distinct isoforms can play important biological roles, including by changing the sequences or expression levels of protein products. The first single-cell approaches to RNA sequencing—and later, spatial approaches—which are now widely used for the identification of differentially expressed genes, rely on short reads and offer the ability to transcriptomically compare different cell types but are limited in their ability to measure differential isoform expression. More recently, long-read sequencing methods have been combined with single-cell and spatial technologies in order to characterize isoform expression. In this review, we provide an overview of the emergence of single-cell and spatial long-read sequencing and discuss the challenges associated with the implementation of these technologies and interpretation of these data. We discuss the opportunities they offer for understanding the relationships between the distinct variable elements of transcript molecules and highlight some of the ways in which they have been used to characterize isoforms’ roles in development and pathology. Single-nucleus long-read sequencing, a special case of the single-cell approach, is also discussed. We attempt to cover both the limitations of these technologies and their significant potential for expanding our still-limited understanding of the biological roles of RNA isoforms.
This article, published in Genome Research, is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.
