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Single-cell RNA sequencing of human kidney
A comprehensive cellular anatomy of normal human kidney is crucial to address the cellular origins of renal disease and renal cancer. Some kidney diseases may be cell type-specific, especially renal tubular cells. To investigate the classification and transcriptomic information of the human kidney,...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6940381/ https://www.ncbi.nlm.nih.gov/pubmed/31896769 http://dx.doi.org/10.1038/s41597-019-0351-8 |
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author | Liao, Jinling Yu, Zhenyuan Chen, Yang Bao, Mengying Zou, Chunlin Zhang, Haiying Liu, Deyun Li, Tianyu Zhang, Qingyun Li, Jiaping Cheng, Jiwen Mo, Zengnan |
author_facet | Liao, Jinling Yu, Zhenyuan Chen, Yang Bao, Mengying Zou, Chunlin Zhang, Haiying Liu, Deyun Li, Tianyu Zhang, Qingyun Li, Jiaping Cheng, Jiwen Mo, Zengnan |
author_sort | Liao, Jinling |
collection | PubMed |
description | A comprehensive cellular anatomy of normal human kidney is crucial to address the cellular origins of renal disease and renal cancer. Some kidney diseases may be cell type-specific, especially renal tubular cells. To investigate the classification and transcriptomic information of the human kidney, we rapidly obtained a single-cell suspension of the kidney and conducted single-cell RNA sequencing (scRNA-seq). Here, we present the scRNA-seq data of 23,366 high-quality cells from the kidneys of three human donors. In this dataset, we show 10 clusters of normal human renal cells. Due to the high quality of single-cell transcriptomic information, proximal tubule (PT) cells were classified into three subtypes and collecting ducts cells into two subtypes. Collectively, our data provide a reliable reference for studies on renal cell biology and kidney disease. |
format | Online Article Text |
id | pubmed-6940381 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-69403812020-01-06 Single-cell RNA sequencing of human kidney Liao, Jinling Yu, Zhenyuan Chen, Yang Bao, Mengying Zou, Chunlin Zhang, Haiying Liu, Deyun Li, Tianyu Zhang, Qingyun Li, Jiaping Cheng, Jiwen Mo, Zengnan Sci Data Data Descriptor A comprehensive cellular anatomy of normal human kidney is crucial to address the cellular origins of renal disease and renal cancer. Some kidney diseases may be cell type-specific, especially renal tubular cells. To investigate the classification and transcriptomic information of the human kidney, we rapidly obtained a single-cell suspension of the kidney and conducted single-cell RNA sequencing (scRNA-seq). Here, we present the scRNA-seq data of 23,366 high-quality cells from the kidneys of three human donors. In this dataset, we show 10 clusters of normal human renal cells. Due to the high quality of single-cell transcriptomic information, proximal tubule (PT) cells were classified into three subtypes and collecting ducts cells into two subtypes. Collectively, our data provide a reliable reference for studies on renal cell biology and kidney disease. Nature Publishing Group UK 2020-01-02 /pmc/articles/PMC6940381/ /pubmed/31896769 http://dx.doi.org/10.1038/s41597-019-0351-8 Text en © The Author(s) 2020 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Liao, Jinling Yu, Zhenyuan Chen, Yang Bao, Mengying Zou, Chunlin Zhang, Haiying Liu, Deyun Li, Tianyu Zhang, Qingyun Li, Jiaping Cheng, Jiwen Mo, Zengnan Single-cell RNA sequencing of human kidney |
title | Single-cell RNA sequencing of human kidney |
title_full | Single-cell RNA sequencing of human kidney |
title_fullStr | Single-cell RNA sequencing of human kidney |
title_full_unstemmed | Single-cell RNA sequencing of human kidney |
title_short | Single-cell RNA sequencing of human kidney |
title_sort | single-cell rna sequencing of human kidney |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6940381/ https://www.ncbi.nlm.nih.gov/pubmed/31896769 http://dx.doi.org/10.1038/s41597-019-0351-8 |
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