Episode 160

October 07, 2025

00:15:36

160: Long reads meet single-cell omics

Hosted by

Gustavo B Barra
160: Long reads meet single-cell omics
Base by Base
160: Long reads meet single-cell omics

Oct 07 2025 | 00:15:36

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Show Notes

Wen L et al., Trends in Genetics - This review surveys the integration of single-molecule long-read sequencing (SMS) with single-cell genomics, epigenomics and transcriptomics, describing platforms, methods and the new biological 'dark matter' now accessible at single-cell resolution. Key terms: single-cell sequencing, long-read sequencing, alternative splicing, structural variation, transposable elements.

Study Highlights:
SMS platforms (PacBio HiFi and Oxford Nanopore) have improved accuracy and enable direct full-length cDNA sequencing to resolve alternative splicing and isoforms in individual cells. Long reads substantially improve detection of repetitive elements, structural variants, ecDNAs and enable chromosome-scale haplotype phasing from small cell numbers. SMS-based single-cell epigenome methods capture allele-specific DNA methylation, histone marks, TF binding and higher-order 3D chromatin interactions, including within repetitive regions. New single-cell long-read methods (for transcriptome, genome and multiple epigenomic layers) are expanding capabilities but remain constrained by capture efficiency, cost and amplification artifacts.

Conclusion:
SMS-based long-read single-cell omics opens access to genomic and epigenomic 'dark matter'—full-length isoforms, repeats, SVs and allele-specific regulation—and points toward future single-cell de novo assemblies, multi-omics and spatial long-read applications.

Music:
Enjoy the music based on this article at the end of the episode.

Article title:
Single-cell omics sequencing technologies: the long-read generation

First author:
Wen L

Journal:
Trends in Genetics

DOI:
10.1016/j.tig.2025.07.012

Reference:
Wen L. and Tang F. Single-cell omics sequencing technologies: the long-read generation. Trends in Genetics. 2025. https://doi.org/10.1016/j.tig.2025.07.012

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

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