Interrogations of single-cell RNA splicing landscapes with SCASL define new cell identities with physiological relevance
Abstract RNA splicing shapes the gene regulatory programs that underlie various physiological and disease processes. Here, we present the SCASL (single-cell clustering based on alternative splicing landscapes) method for interrogating the heterogeneity of RNA splicing with single-cell RNA-seq data....
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-03-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-024-46480-9 |
| _version_ | 1797266679795810304 |
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| author | Xianke Xiang Yao He Zemin Zhang Xuerui Yang |
| author_facet | Xianke Xiang Yao He Zemin Zhang Xuerui Yang |
| author_sort | Xianke Xiang |
| collection | DOAJ |
| description | Abstract RNA splicing shapes the gene regulatory programs that underlie various physiological and disease processes. Here, we present the SCASL (single-cell clustering based on alternative splicing landscapes) method for interrogating the heterogeneity of RNA splicing with single-cell RNA-seq data. SCASL resolves the issue of biased and sparse data coverage on single-cell RNA splicing and provides a new scheme for classifications of cell identities. With previously published datasets as examples, SCASL identifies new cell clusters indicating potentially precancerous and early-tumor stages in triple-negative breast cancer, illustrates cell lineages of embryonic liver development, and provides fine clusters of highly heterogeneous tumor-associated CD4 and CD8 T cells with functional and physiological relevance. Most of these findings are not readily available via conventional cell clustering based on single-cell gene expression data. Our study shows the potential of SCASL in revealing the intrinsic RNA splicing heterogeneity and generating biological insights into the dynamic and functional cell landscapes in complex tissues. |
| first_indexed | 2024-04-25T01:04:32Z |
| format | Article |
| id | doaj.art-17e839925038472bbcfd85fad800de35 |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-04-25T01:04:32Z |
| publishDate | 2024-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-17e839925038472bbcfd85fad800de352024-03-10T12:16:54ZengNature PortfolioNature Communications2041-17232024-03-0115111710.1038/s41467-024-46480-9Interrogations of single-cell RNA splicing landscapes with SCASL define new cell identities with physiological relevanceXianke Xiang0Yao He1Zemin Zhang2Xuerui Yang3MOE Key Laboratory of Bioinformatics, School of Life Sciences, Tsinghua UniversityBiomedical Pioneering Innovation Center and School of Life Sciences, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking UniversityBiomedical Pioneering Innovation Center and School of Life Sciences, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking UniversityMOE Key Laboratory of Bioinformatics, School of Life Sciences, Tsinghua UniversityAbstract RNA splicing shapes the gene regulatory programs that underlie various physiological and disease processes. Here, we present the SCASL (single-cell clustering based on alternative splicing landscapes) method for interrogating the heterogeneity of RNA splicing with single-cell RNA-seq data. SCASL resolves the issue of biased and sparse data coverage on single-cell RNA splicing and provides a new scheme for classifications of cell identities. With previously published datasets as examples, SCASL identifies new cell clusters indicating potentially precancerous and early-tumor stages in triple-negative breast cancer, illustrates cell lineages of embryonic liver development, and provides fine clusters of highly heterogeneous tumor-associated CD4 and CD8 T cells with functional and physiological relevance. Most of these findings are not readily available via conventional cell clustering based on single-cell gene expression data. Our study shows the potential of SCASL in revealing the intrinsic RNA splicing heterogeneity and generating biological insights into the dynamic and functional cell landscapes in complex tissues.https://doi.org/10.1038/s41467-024-46480-9 |
| spellingShingle | Xianke Xiang Yao He Zemin Zhang Xuerui Yang Interrogations of single-cell RNA splicing landscapes with SCASL define new cell identities with physiological relevance Nature Communications |
| title | Interrogations of single-cell RNA splicing landscapes with SCASL define new cell identities with physiological relevance |
| title_full | Interrogations of single-cell RNA splicing landscapes with SCASL define new cell identities with physiological relevance |
| title_fullStr | Interrogations of single-cell RNA splicing landscapes with SCASL define new cell identities with physiological relevance |
| title_full_unstemmed | Interrogations of single-cell RNA splicing landscapes with SCASL define new cell identities with physiological relevance |
| title_short | Interrogations of single-cell RNA splicing landscapes with SCASL define new cell identities with physiological relevance |
| title_sort | interrogations of single cell rna splicing landscapes with scasl define new cell identities with physiological relevance |
| url | https://doi.org/10.1038/s41467-024-46480-9 |
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