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Publication
Bringing Renal Biopsy Interpretation Into the Molecular Age With Single-Cell RNA
Sequencing.
Authors
Malone AF, Wu H, Humphreys BD
Submitted By
Benjamin Humphreys on 1/23/2019
Status
Published
Journal
Seminars in nephrology
Year
2018
Date Published
1/1/2018
Volume : Pages
38 : 31 - 39
PubMed Reference
Abstract
The renal biopsy provides critical diagnostic and prognostic information to
clinicians including cases of acute kidney injury, chronic kidney disease, and
allograft dysfunction. Today, biopsy specimens are read using a combination of
light microscopy, electron microscopy, and indirect immunofluorescence, with a
limited number of antibodies. These techniques all were perfected decades ago
with only incremental changes since then. By contrast, recent advances in
single-cell genomics are transforming scientists' ability to characterize cells.
Rather than measure the expression of several genes at a time by
immunofluorescence, it now is possible to measure the expression of thousands of
genes in thousands of single cells simultaneously. Here, we argue that the
development of single-cell RNA sequencing offers an opportunity to describe
human kidney disease comprehensively at a cellular level. It is particularly
well suited for the analysis of immune cells, which are characterized by
multiple subtypes and changing functions depending on their environment. In this
review, we summarize the development of single-cell RNA sequencing
methodologies. We discuss how these approaches are being applied in other
organs, and the potential for this powerful technology to transform our
understanding of kidney disease once applied to the renal biopsy.
Investigators with authorship
Name
Institution
Benjamin Humphreys
Washington University in St Louis
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Please acknowledge all posters, manuscripts or scientific materials that were generated in part or whole using funds from the Diabetic Complications Consortium(看片视频) using the following text:
Financial support for this work provided by the NIDDK Diabetic Complications Consortium (RRID:SCR_001415, www.diacomp.org), grants DK076169 and DK115255
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