A single-nucleus RNA-sequencing pipeline to decipher the molecular anatomy and pathophysiology of human kidneys

Blue B. Lake, Song Chen, Masato Hoshi, Nongluk Plongthongkum, Diane Salamon, Amanda Knoten, Anitha Vijayan, Ramakrishna Venkatesh, Eric H. Kim, Derek Gao, Joseph Gaut, Kun Zhang () and Sanjay Jain ()
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Blue B. Lake: University of California, San Diego
Masato Hoshi: Washington University School of Medicine
Nongluk Plongthongkum: University of California, San Diego
Diane Salamon: Washington University School of Medicine
Amanda Knoten: Washington University School of Medicine
Anitha Vijayan: Washington University School of Medicine
Ramakrishna Venkatesh: Washington University School of Medicine
Eric H. Kim: Washington University School of Medicine
Derek Gao: University of California, San Diego
Joseph Gaut: Washington University School of Medicine
Kun Zhang: University of California, San Diego
Sanjay Jain: Washington University School of Medicine

Nature Communications, 2019, vol. 10, issue 1, 1-15

Abstract: Abstract 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.

Date: 2019
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DOI: 10.1038/s41467-019-10861-2

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