Dissociation protocols used for sarcoma tissues bias the transcriptome observed in single-cell and single-nucleus RNA sequencing

用于肉瘤组织的解离方案会使单细胞和单核 RNA 测序中观察到的转录组产生偏差

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作者:Danh D Truong, Salah-Eddine Lamhamedi-Cherradi, Robert W Porter, Sandhya Krishnan, Jyothishmathi Swaminathan, Amber Gibson, Alexander J Lazar, J Andrew Livingston, Vidya Gopalakrishnan, Nancy Gordon, Najat C Daw, Nicholas E Navin, Richard Gorlick, Joseph A Ludwig

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. Classification of bulk tumors by their individual cellular constituents has also created new opportunities to generate single-cell atlases for many organs, cancers, and developmental models. Despite the tremendous promise of this technology, recent evidence studying epithelial tissues and diverse carcinomas suggests the

Conclusions

We highlighted transcriptional biases, including warm dissociation and gene-length biases, introduced by the dissociation method for various sarcoma subtypes. This work is the first to characterize how the dissociation methods used for sc/snRNA-seq may affect the interpretation of the molecular features in sarcoma PDXs.

Results

We systematically assessed dissociation methods across different sarcoma subtypes. We compared gene expression from single-cell and single-nucleus RNA-sequencing of 125,831 whole-cells and nuclei from ES, DSRCT, and OS PDXs. We detected warm dissociation artifacts in single-cell samples and gene length bias in single-nucleus samples. Classic sarcoma gene signatures were observed regardless of the dissociation method. In addition, we showed that dissociation method biases could be computationally corrected. Conclusions: We highlighted transcriptional biases, including warm dissociation and gene-length biases, introduced by the dissociation method for various sarcoma subtypes. This work is the first to characterize how the dissociation methods used for sc/snRNA-seq may affect the interpretation of the molecular features in sarcoma PDXs.

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