Systematic benchmarking of commercial workflows for isoform-resolved single-nucleus transcriptomics

Abstract

Short-read sequencing-based single-cell transcriptomics represents the current gold standard for studying cellular transcriptomes but remains limited in its ability to resolve full-length transcript isoforms and splicing patterns. Long-read single-cell and single-nucleus RNA sequencing (LR sc/snRNA-seq) enables the transcriptome-wide characterization of full-length isoforms at cellular resolution, yet the relative performance of commercially available workflows remains insufficiently explored. Here, using nuclei extracted from a standardized multi-species benchmark sample and Oxford Nanopore Technologies long-read sequencing, we systematically benchmarked four LR snRNA-seq strategies: 10x Genomics 3', 10x Genomics 5', ArgenTag, and Parse Biosciences. Comparing transcriptome features qualitatively and quantitatively, as well as the concordance with matched short-read data and the ability to resolve cellular heterogeneity, we identified substantial method-specific differences in read length and yield, transcript coverage, isoform detection, and recovery of sample-specific biological information, with the 10x Genomics 3' and 5' assays emerging as the most balanced approaches for comprehensive isoform-resolved single-nucleus transcriptomics. Altogether, our study provides a systematic assessment of four commercially available workflows for performing LR snRNA-seq and highlights key methodological trade-offs related to distinct library preparation strategies, thus providing practical guidance for future isoform-resolved transcriptome studies at the single-nucleus level.

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BibTeX RIS

BibTeX

@misc{kohler2026systematic,
  title = {{Systematic benchmarking of commercial workflows for isoform-resolved single-nucleus transcriptomics}},
  author = {F. Köhler and A. Delgado-Tejedor and M. Zehnsdorf and M. Salgado Albarran and L. Zalba Jadraque and I. Gonzalez Navarrete and L. Cozzuto and J. Ponomarenko and B. Fuste Perez},
  howpublished = {bioRxiv},
  year = {2026},
  month = sep,
  doi = {10.64898/2026.09.01.748518},
  url = {https://www.biorxiv.org/content/10.64898/2026.09.01.748518v1},
  note = {CC BY},
}

RIS

TY  - UNPB
TI  - Systematic benchmarking of commercial workflows for isoform-resolved single-nucleus transcriptomics
AU  - F. Köhler
AU  - A. Delgado-Tejedor
AU  - M. Zehnsdorf
AU  - M. Salgado Albarran
AU  - L. Zalba Jadraque
AU  - I. Gonzalez Navarrete
AU  - L. Cozzuto
AU  - J. Ponomarenko
AU  - B. Fuste Perez
PY  - 2026
DA  - 2026/09/01
PB  - bioRxiv
DO  - 10.64898/2026.09.01.748518
UR  - https://www.biorxiv.org/content/10.64898/2026.09.01.748518v1
AB  - Short-read sequencing-based single-cell transcriptomics represents the current gold standard for studying cellular transcriptomes but remains limited in its ability to resolve full-length transcript isoforms and splicing patterns. Long-read single-cell and single-nucleus RNA sequencing (LR sc/snRNA-seq) enables the transcriptome-wide characterization of full-length isoforms at cellular resolution, yet the relative performance of commercially available workflows remains insufficiently explored. Here, using nuclei extracted from a standardized multi-species benchmark sample and Oxford Nanopore Technologies long-read sequencing, we systematically benchmarked four LR snRNA-seq strategies: 10x Genomics 3', 10x Genomics 5', ArgenTag, and Parse Biosciences. Comparing transcriptome features qualitatively and quantitatively, as well as the concordance with matched short-read data and the ability to resolve cellular heterogeneity, we identified substantial method-specific differences in read length and yield, transcript coverage, isoform detection, and recovery of sample-specific biological information, with the 10x Genomics 3' and 5' assays emerging as the most balanced approaches for comprehensive isoform-resolved single-nucleus transcriptomics. Altogether, our study provides a systematic assessment of four commercially available workflows for performing LR snRNA-seq and highlights key methodological trade-offs related to distinct library preparation strategies, thus providing practical guidance for future isoform-resolved transcriptome studies at the single-nucleus level.
ER  -

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