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

Blue B. Lake(University of California San Diego), Song Chen(University of California San Diego), Masato Hoshi(Washington University in St. Louis), Nongluk Plongthongkum(University of California San Diego), Diane Salamon(Washington University in St. Louis), Amanda Knoten(Washington University in St. Louis), Anitha Vijayan(Washington University in St. Louis), Ramakrishna Venkatesh(Washington University in St. Louis), Eric H. Kim(Washington University in St. Louis), Derek Gao(University of California San Diego), Joseph P. Gaut(Washington University in St. Louis), Kun Zhang(University of California San Diego), Sanjay Jain(Washington University in St. Louis)
Nature Communications
June 27, 2019
Cited by 298Open Access
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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.


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