RT Journal Article SR Electronic T1 Dissociation protocols used for sarcoma tissues bias the transcriptome observed in single-cell and single-nucleus RNA sequencing JF bioRxiv FD Cold Spring Harbor Laboratory SP 2022.01.21.476982 DO 10.1101/2022.01.21.476982 A1 Danh D. Truong A1 Salah-Eddine Lamhamedi-Cherradi A1 Robert W. Porter A1 Sandhya Krishnan A1 Jyothishmathi Swaminathan A1 Amber L. Gibson A1 Alexander J. Lazar A1 John A. Livingston A1 Vidya Gopalakrishnan A1 Nancy Gordon A1 Najat C. Daw A1 Richard Gorlick A1 Joseph A. Ludwig YR 2022 UL http://biorxiv.org/content/early/2022/01/22/2022.01.21.476982.abstract AB Background Single-cell RNA-seq has emerged as an innovative technology used to study complex tissues and characterize cell types, states, and lineages at a single-cell level. Rapid adoption of this technology has led to a flurry of research creating single-cell atlases for many organs, cancers, and developmental models. Despite the tremendous success of this technology, sarcomas, rare cancers of mesenchymal origin, have not yet widely benefited from the adoption of single-cell RNA-seq. Due to their rarity, obtaining fresh clinical specimens is challenging. Single-nucleus RNA-seq could remove limitations from obtaining fresh tissue and enable immediate processing of archival tissue. However, biases may exist during dissociation of either fresh or frozen specimens that can hinder reproducible results and introduce technical or biological artifacts.Results To address these questions, we systematically assessed dissociation methods across different sarcoma subtypes. Here, we compare gene expression from single-cell and single-nucleus RNA-sequencing of 125,831 whole-cells and nuclei from Ewing’s sarcoma, desmoplastic small round cell tumor, and osteosarcoma patient-derived xenografts. We detected warm dissociation artifacts from single-cell samples and gene length bias in single-nucleus samples. Classic sarcoma gene signatures were observed regardless of dissociation method. Finally, we show that dissociation method biases can be computationally corrected.Conclusions We highlighted transcriptional biases, including warm dissociation and gene-length biases, introduced by any dissociation method for various sarcoma subtypes. This work will inform researchers on choice of dissociation method and careful interpretation of data due to dissociation biases.Competing Interest StatementThe authors have declared no competing interest.