Li, S., Alexander, J., Kendall, J. et al. (19 more authors) (2025) Hybrid BAG-seq: DNA and RNA from the same single nucleus reveals interactions between genomic and transcriptomic landscapes in human tumor samples. Genome Biology, 26 (1). 314. ISSN: 1474-7596
Abstract
We introduce hybrid BAG-seq: a high-throughput, multi-omic method that simultaneously captures DNA and RNA from single nuclei. We apply this protocol to 65,499 single nuclei from samples of five uterine cancer patients and validate the clustering using RNA-only and DNA-only protocols from the same tissues. Multiple tumor genome or expression clusters are often present within a patient, with different tumor clones projecting into distinct or shared expression states, demonstrating nearly all possible genome-transcriptome correlations. We also identify mutant stroma with significant X chromosome loss in various cell types and patient-specific stromal subtypes exhibiting aberrant expression patterns.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/. |
Keywords: | Humans; Female; Transcriptome; Cell Nucleus; High-Throughput Nucleotide Sequencing; Genomics; Uterine Neoplasms; Gene Expression Profiling |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > School of Biosciences (Sheffield) > Department of Biomedical Science (Sheffield) |
Date Deposited: | 17 Oct 2025 10:36 |
Last Modified: | 17 Oct 2025 10:43 |
Status: | Published |
Publisher: | Springer Science and Business Media LLC |
Refereed: | Yes |
Identification Number: | 10.1186/s13059-025-03790-5 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:233053 |