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High throughput single cell long-read sequencing analyses of same-cell genotypes and phenotypes in human tumors
Single-cell nanopore sequencing of full-length mRNAs transforms single-cell multi-omics studies. However, challenges include high sequencing errors and dependence on short-reads and/or barcode whitelists. To address these, we develop scNanoGPS to calculate same-cell genotypes (mutations) and phenoty...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10336110/ https://www.ncbi.nlm.nih.gov/pubmed/37433798 http://dx.doi.org/10.1038/s41467-023-39813-7 |
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author | Shiau, Cheng-Kai Lu, Lina Kieser, Rachel Fukumura, Kazutaka Pan, Timothy Lin, Hsiao-Yun Yang, Jie Tong, Eric L. Lee, GaHyun Yan, Yuanqing Huse, Jason T. Gao, Ruli |
author_facet | Shiau, Cheng-Kai Lu, Lina Kieser, Rachel Fukumura, Kazutaka Pan, Timothy Lin, Hsiao-Yun Yang, Jie Tong, Eric L. Lee, GaHyun Yan, Yuanqing Huse, Jason T. Gao, Ruli |
author_sort | Shiau, Cheng-Kai |
collection | PubMed |
description | Single-cell nanopore sequencing of full-length mRNAs transforms single-cell multi-omics studies. However, challenges include high sequencing errors and dependence on short-reads and/or barcode whitelists. To address these, we develop scNanoGPS to calculate same-cell genotypes (mutations) and phenotypes (gene/isoform expressions) without short-read nor whitelist guidance. We apply scNanoGPS onto 23,587 long-read transcriptomes from 4 tumors and 2 cell-lines. Standalone, scNanoGPS deconvolutes error-prone long-reads into single-cells and single-molecules, and simultaneously accesses both phenotypes and genotypes of individual cells. Our analyses reveal that tumor and stroma/immune cells express distinct combination of isoforms (DCIs). In a kidney tumor, we identify 924 DCI genes involved in cell-type-specific functions such as PDE10A in tumor cells and CCL3 in lymphocytes. Transcriptome-wide mutation analyses identify many cell-type-specific mutations including VEGFA mutations in tumor cells and HLA-A mutations in immune cells, highlighting the critical roles of different mutant populations in tumors. Together, scNanoGPS facilitates applications of single-cell long-read sequencing technologies. |
format | Online Article Text |
id | pubmed-10336110 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-103361102023-07-13 High throughput single cell long-read sequencing analyses of same-cell genotypes and phenotypes in human tumors Shiau, Cheng-Kai Lu, Lina Kieser, Rachel Fukumura, Kazutaka Pan, Timothy Lin, Hsiao-Yun Yang, Jie Tong, Eric L. Lee, GaHyun Yan, Yuanqing Huse, Jason T. Gao, Ruli Nat Commun Article Single-cell nanopore sequencing of full-length mRNAs transforms single-cell multi-omics studies. However, challenges include high sequencing errors and dependence on short-reads and/or barcode whitelists. To address these, we develop scNanoGPS to calculate same-cell genotypes (mutations) and phenotypes (gene/isoform expressions) without short-read nor whitelist guidance. We apply scNanoGPS onto 23,587 long-read transcriptomes from 4 tumors and 2 cell-lines. Standalone, scNanoGPS deconvolutes error-prone long-reads into single-cells and single-molecules, and simultaneously accesses both phenotypes and genotypes of individual cells. Our analyses reveal that tumor and stroma/immune cells express distinct combination of isoforms (DCIs). In a kidney tumor, we identify 924 DCI genes involved in cell-type-specific functions such as PDE10A in tumor cells and CCL3 in lymphocytes. Transcriptome-wide mutation analyses identify many cell-type-specific mutations including VEGFA mutations in tumor cells and HLA-A mutations in immune cells, highlighting the critical roles of different mutant populations in tumors. Together, scNanoGPS facilitates applications of single-cell long-read sequencing technologies. Nature Publishing Group UK 2023-07-11 /pmc/articles/PMC10336110/ /pubmed/37433798 http://dx.doi.org/10.1038/s41467-023-39813-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, 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 changes were made. 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/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Shiau, Cheng-Kai Lu, Lina Kieser, Rachel Fukumura, Kazutaka Pan, Timothy Lin, Hsiao-Yun Yang, Jie Tong, Eric L. Lee, GaHyun Yan, Yuanqing Huse, Jason T. Gao, Ruli High throughput single cell long-read sequencing analyses of same-cell genotypes and phenotypes in human tumors |
title | High throughput single cell long-read sequencing analyses of same-cell genotypes and phenotypes in human tumors |
title_full | High throughput single cell long-read sequencing analyses of same-cell genotypes and phenotypes in human tumors |
title_fullStr | High throughput single cell long-read sequencing analyses of same-cell genotypes and phenotypes in human tumors |
title_full_unstemmed | High throughput single cell long-read sequencing analyses of same-cell genotypes and phenotypes in human tumors |
title_short | High throughput single cell long-read sequencing analyses of same-cell genotypes and phenotypes in human tumors |
title_sort | high throughput single cell long-read sequencing analyses of same-cell genotypes and phenotypes in human tumors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10336110/ https://www.ncbi.nlm.nih.gov/pubmed/37433798 http://dx.doi.org/10.1038/s41467-023-39813-7 |
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