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A single-nucleus RNA-sequencing pipeline to decipher the molecular anatomy and pathophysiology of human kidneys
Defining cellular and molecular identities within the kidney is necessary to understand its organization and function in health and disease. Here we demonstrate a reproducible method with minimal artifacts for single-nucleus Droplet-based RNA sequencing (snDrop-Seq) that we use to resolve thirty dis...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6597610/ https://www.ncbi.nlm.nih.gov/pubmed/31249312 http://dx.doi.org/10.1038/s41467-019-10861-2 |
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author | Lake, Blue B. Chen, Song Hoshi, Masato Plongthongkum, Nongluk Salamon, Diane Knoten, Amanda Vijayan, Anitha Venkatesh, Ramakrishna Kim, Eric H. Gao, Derek Gaut, Joseph Zhang, Kun Jain, Sanjay |
author_facet | Lake, Blue B. Chen, Song Hoshi, Masato Plongthongkum, Nongluk Salamon, Diane Knoten, Amanda Vijayan, Anitha Venkatesh, Ramakrishna Kim, Eric H. Gao, Derek Gaut, Joseph Zhang, Kun Jain, Sanjay |
author_sort | Lake, Blue B. |
collection | PubMed |
description | Defining cellular and molecular identities within the kidney is necessary to understand its organization and function in health and disease. Here we demonstrate a reproducible method with minimal artifacts for single-nucleus Droplet-based RNA sequencing (snDrop-Seq) that we use to resolve thirty distinct cell populations in human adult kidney. We define molecular transition states along more than ten nephron segments spanning two major kidney regions. We further delineate cell type-specific expression of genes associated with chronic kidney disease, diabetes and hypertension, providing insight into possible targeted therapies. This includes expression of a hypertension-associated mechano-sensory ion channel in mesangial cells, and identification of proximal tubule cell populations defined by pathogenic expression signatures. Our fully optimized, quality-controlled transcriptomic profiling pipeline constitutes a tool for the generation of healthy and diseased molecular atlases applicable to clinical samples. |
format | Online Article Text |
id | pubmed-6597610 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-65976102019-07-01 A single-nucleus RNA-sequencing pipeline to decipher the molecular anatomy and pathophysiology of human kidneys Lake, Blue B. Chen, Song Hoshi, Masato Plongthongkum, Nongluk Salamon, Diane Knoten, Amanda Vijayan, Anitha Venkatesh, Ramakrishna Kim, Eric H. Gao, Derek Gaut, Joseph Zhang, Kun Jain, Sanjay Nat Commun Article Defining cellular and molecular identities within the kidney is necessary to understand its organization and function in health and disease. Here we demonstrate a reproducible method with minimal artifacts for single-nucleus Droplet-based RNA sequencing (snDrop-Seq) that we use to resolve thirty distinct cell populations in human adult kidney. We define molecular transition states along more than ten nephron segments spanning two major kidney regions. We further delineate cell type-specific expression of genes associated with chronic kidney disease, diabetes and hypertension, providing insight into possible targeted therapies. This includes expression of a hypertension-associated mechano-sensory ion channel in mesangial cells, and identification of proximal tubule cell populations defined by pathogenic expression signatures. Our fully optimized, quality-controlled transcriptomic profiling pipeline constitutes a tool for the generation of healthy and diseased molecular atlases applicable to clinical samples. Nature Publishing Group UK 2019-06-27 /pmc/articles/PMC6597610/ /pubmed/31249312 http://dx.doi.org/10.1038/s41467-019-10861-2 Text en © The Author(s) 2019 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/. |
spellingShingle | Article Lake, Blue B. Chen, Song Hoshi, Masato Plongthongkum, Nongluk Salamon, Diane Knoten, Amanda Vijayan, Anitha Venkatesh, Ramakrishna Kim, Eric H. Gao, Derek Gaut, Joseph Zhang, Kun Jain, Sanjay A single-nucleus RNA-sequencing pipeline to decipher the molecular anatomy and pathophysiology of human kidneys |
title | A single-nucleus RNA-sequencing pipeline to decipher the molecular anatomy and pathophysiology of human kidneys |
title_full | A single-nucleus RNA-sequencing pipeline to decipher the molecular anatomy and pathophysiology of human kidneys |
title_fullStr | A single-nucleus RNA-sequencing pipeline to decipher the molecular anatomy and pathophysiology of human kidneys |
title_full_unstemmed | A single-nucleus RNA-sequencing pipeline to decipher the molecular anatomy and pathophysiology of human kidneys |
title_short | A single-nucleus RNA-sequencing pipeline to decipher the molecular anatomy and pathophysiology of human kidneys |
title_sort | single-nucleus rna-sequencing pipeline to decipher the molecular anatomy and pathophysiology of human kidneys |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6597610/ https://www.ncbi.nlm.nih.gov/pubmed/31249312 http://dx.doi.org/10.1038/s41467-019-10861-2 |
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