Comparison of single‑nucleus and single‑cell transcriptomes in hepatocellular carcinoma tissue

Single-nucleus RNA sequencing (snRNA-seq) is a method used to analyze gene expression in cells for which isolation is complex, such as those in hepatocellular carcinoma (HCC) tissues. It constitutes an alternative to single-cell RNA sequencing (scRNA-seq) by analyzing the nucleus rather than the who...

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Veröffentlicht in:Molecular medicine reports 2022-11, Vol.26 (5), Article 339
Hauptverfasser: Wen, Pei, Tang, Xiaojie, Xu, Lin, Qu, Haixia
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Sprache:eng
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Zusammenfassung:Single-nucleus RNA sequencing (snRNA-seq) is a method used to analyze gene expression in cells for which isolation is complex, such as those in hepatocellular carcinoma (HCC) tissues. It constitutes an alternative to single-cell RNA sequencing (scRNA-seq) by analyzing the nucleus rather than the whole cell; however, whether it can completely replace scRNA-seq in HCC remains to be clarified. In the present study, scRNA-seq was compared with snRNA-seq in tumor tissue obtained from patients with HCC, using the 10X Genomics Chromium platform. Seurat was also used to process the data and compare the differences between the two sequencing methods in identifying different cell types. In the present study, the transcriptomes of 14,349 single nuclei and 9,504 single cells were obtained from the aforementioned HCC tissue. A total of 21 discrete cell clusters, including hepatocytes, endothelial cells, fibroblasts, B cells, T cells, natural killer cells and macrophages were identified. Notably, a high number of hepatocytes were detected using snRNA-seq, while an increased number of immunocytes were identified in the tumor microenvironment using scRNA-seq. Results of the present study provided a comprehensive image of human HCC at a single-cell resolution. Moreover, results of the present study further demonstrated that snRNA-seq may be adequate in replacing scRNA-seq in certain cases, and snRNA-seq performs at an improved level in hepatocyte sequencing. Combined use of the two sequencing methods may contribute to the study of intercellular interactions.
ISSN:1791-2997
1791-3004
DOI:10.3892/mmr.2022.12855